BentoML makes moving trained ML models to production easy:
BentoML is a framework for serving, managing, and deploying machine learning models. It is aiming to bridge the gap between Data Science and DevOps, and enable teams to deliver prediction services in a fast, repeatable, and scalable way.
Before reading this example project, be sure to check out the Getting started guide to learn about the basic concepts in BentoML.
This example notebook is based on Fast AI v1 course v3 lesson one, training an image classifier with Fast AI that detect the different breed of cat and dog.
Make sure to use GPU runtime when running this notebook in Google Colab, you can set it in top menu: Runtime > Change Runtime Type > Hardware accelerator
.
%reload_ext autoreload
%autoreload 2
%matplotlib inline
!pip install -q bentoml 'fastai<=1.0.61'
from fastai.vision import *
from fastai.metrics import error_rate
path = untar_data(URLs.PETS)
path_anno = path/'annotations'
path_img = path/'images'
fnames = get_image_files(path_img)
fnames[:5]
[PosixPath('/Users/bozhaoyu/.fastai/data/oxford-iiit-pet/images/Egyptian_Mau_167.jpg'), PosixPath('/Users/bozhaoyu/.fastai/data/oxford-iiit-pet/images/pug_52.jpg'), PosixPath('/Users/bozhaoyu/.fastai/data/oxford-iiit-pet/images/basset_hound_112.jpg'), PosixPath('/Users/bozhaoyu/.fastai/data/oxford-iiit-pet/images/Siamese_193.jpg'), PosixPath('/Users/bozhaoyu/.fastai/data/oxford-iiit-pet/images/shiba_inu_122.jpg')]
#bs = 64
bs = 16 # uncomment this line if you run out of memory even after clicking Kernel->Restart
np.random.seed(2)
pat = r'/([^/]+)_\d+.jpg$'
data = ImageDataBunch.from_name_re(
path_img,
fnames,
pat,
num_workers=0,
ds_tfms=get_transforms(),
size=224,
bs=bs
).normalize(imagenet_stats)
/usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed "
data.show_batch(rows=3, figsize=(7,6))
Now we will start training the model. For demo purpose, we will only train for 1 epoch (1 cycle through all the data).
learn = cnn_learner(data, models.resnet34, metrics=error_rate)
learn.model
Sequential( (0): Sequential( (0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False) (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (2): ReLU(inplace=True) (3): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False) (4): Sequential( (0): BasicBlock( (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (1): BasicBlock( (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (2): BasicBlock( (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (5): Sequential( (0): BasicBlock( (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (downsample): Sequential( (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): BasicBlock( (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (2): BasicBlock( (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (3): BasicBlock( (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (6): Sequential( (0): BasicBlock( (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (downsample): Sequential( (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): BasicBlock( (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (2): BasicBlock( (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (3): BasicBlock( (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (4): BasicBlock( (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (5): BasicBlock( (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (7): Sequential( (0): BasicBlock( (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (downsample): Sequential( (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): BasicBlock( (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) (2): BasicBlock( (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) ) (1): Sequential( (0): AdaptiveConcatPool2d( (ap): AdaptiveAvgPool2d(output_size=1) (mp): AdaptiveMaxPool2d(output_size=1) ) (1): Flatten() (2): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (3): Dropout(p=0.25, inplace=False) (4): Linear(in_features=1024, out_features=512, bias=True) (5): ReLU(inplace=True) (6): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (7): Dropout(p=0.5, inplace=False) (8): Linear(in_features=512, out_features=37, bias=True) ) )
learn.fit_one_cycle(1)
epoch | train_loss | valid_loss | error_rate | time |
---|---|---|---|---|
0 | 0.724376 | 0.302155 | 0.106225 | 32:22 |
/usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed " /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. warnings.warn("The default behavior for interpolate/upsample with float scale_factor changed "
%%writefile pet_classification.py
from bentoml import BentoService, api, env, artifacts
from bentoml.frameworks.fastai import Fastai1ModelArtifact
from bentoml.adapters import ImageInput
from fastai.vision import Image, pil2tensor
import numpy as np
@env(pip_packages=['fastai'])
@artifacts([Fastai1ModelArtifact('pet_classifer')])
class PetClassification(BentoService):
@api(input=ImageInput(), batch=False)
def predict(self, image):
fastai_image = pil2tensor(image, np.float32)
fastai_image = Image(fastai_image)
result = self.artifacts.pet_classifer.predict(fastai_image)
return str(result)
Overwriting pet_classification.py
# 1) import the custom BentoService defined above
from pet_classification import PetClassification
# 2) `pack` it with required artifacts
service = PetClassification()
service.pack('pet_classifer', learn)
# 3) save your BentoSerivce
saved_path = service.save()
[2020-09-22 17:49:00,048] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle. [2020-09-22 17:49:00,214] INFO - Using default docker base image: `None` specified inBentoML config file or env var. User must make sure that the docker base image either has Python 3.7 or conda installed. [2020-09-22 17:49:00,218] WARNING - BentoML by default does not include spacy and torchvision package when using FastaiModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService [2020-09-22 17:49:00,221] WARNING - pip package requirement fastai already exist [2020-09-22 17:49:01,625] INFO - Detected non-PyPI-released BentoML installed, copying local BentoML modulefiles to target saved bundle path..
/usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages/setuptools/dist.py:476: UserWarning: Normalizing '0.9.0.pre+3.gcebf2015' to '0.9.0rc0+3.gcebf2015' normalized_version, warning: no previously-included files matching '*~' found anywhere in distribution warning: no previously-included files matching '*.pyo' found anywhere in distribution warning: no previously-included files matching '.git' found anywhere in distribution warning: no previously-included files matching '.ipynb_checkpoints' found anywhere in distribution warning: no previously-included files matching '__pycache__' found anywhere in distribution no previously-included directories found matching 'e2e_tests' no previously-included directories found matching 'tests' no previously-included directories found matching 'benchmark'
UPDATING BentoML-0.9.0rc0+3.gcebf2015/bentoml/_version.py set BentoML-0.9.0rc0+3.gcebf2015/bentoml/_version.py to '0.9.0.pre+3.gcebf2015' [2020-09-22 17:49:05,483] INFO - BentoService bundle 'PetClassification:20200922174900_F25F3F' saved to: /Users/bozhaoyu/bentoml/repository/PetClassification/20200922174900_F25F3F
To start a REST API model server with the BentoService saved above, use the bentoml serve command:
!bentoml serve PetClassification:latest
[2020-09-22 18:05:30,874] INFO - Getting latest version PetClassification:20200922174900_F25F3F [2020-09-22 18:05:30,875] INFO - Starting BentoML API server in development mode.. [2020-09-22 18:05:31,124] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle. [2020-09-22 18:05:31,139] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+3.gcebf2015 [2020-09-22 18:05:34,809] INFO - Using default docker base image: `None` specified inBentoML config file or env var. User must make sure that the docker base image either has Python 3.7 or conda installed. [2020-09-22 18:05:34,925] WARNING - BentoML by default does not include spacy and torchvision package when using FastaiModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService [2020-09-22 18:05:34,927] WARNING - pip package requirement fastai already exist * Serving Flask app "PetClassification" (lazy loading) * Environment: production WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Debug mode: off * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit) [2020-09-22 18:05:42,267] INFO - {'service_name': 'PetClassification', 'service_version': '20200922174900_F25F3F', 'api': 'predict', 'task': {'data': {'name': 'test.jpg'}, 'task_id': '60d8f815-e40c-4901-94e2-be01dd5aea91', 'http_headers': (('Host', 'localhost:5000'), ('User-Agent', 'curl/7.65.3'), ('Accept', '*/*'), ('Content-Length', '179115'), ('Content-Type', 'multipart/form-data; boundary=------------------------94662ac64c8ea5e1'), ('Expect', '100-continue'))}, 'result': {'data': '"(Category tensor(36), tensor(36), tensor([1.0797e-07, 8.9836e-07, 1.1527e-06, 8.1427e-09, 4.5582e-09, 1.3850e-07,\\n 2.5530e-07, 7.7388e-08, 1.4291e-08, 1.9044e-08, 2.4578e-07, 1.8761e-07,\\n 8.1688e-09, 6.6407e-08, 2.1143e-08, 2.6274e-07, 1.2610e-07, 4.0838e-07,\\n 1.0855e-07, 2.6197e-09, 2.5782e-08, 1.9102e-09, 1.6407e-07, 3.2818e-08,\\n 5.6539e-09, 1.3923e-08, 1.8689e-06, 3.3067e-07, 9.8042e-07, 8.2738e-09,\\n 1.8158e-08, 2.5630e-09, 2.3708e-06, 3.0268e-09, 9.2770e-08, 3.0787e-08,\\n 9.9999e-01]))"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': '60d8f815-e40c-4901-94e2-be01dd5aea91'} 127.0.0.1 - - [22/Sep/2020 18:05:42] "POST /predict HTTP/1.1" 200 - WARNING: Logging before flag parsing goes to stderr. I0922 18:05:42.268567 4588494272 _internal.py:122] 127.0.0.1 - - [22/Sep/2020 18:05:42] "POST /predict HTTP/1.1" 200 - ^C
If you are running this notebook from Google Colab, you can start the dev server with --run-with-ngrok
option, to gain acccess to the API endpoint via a public endpoint managed by ngrok:
!bentoml serve PetClassification:latest --run-with-ngrok
Open http://127.0.0.1:5000 to see more information about the REST APIs server in your browser.
Navigate to parent directory of the notebook(so you have reference to the test.jpg
image), and run the following curl
command to send the image to REST API server and get a prediction result:
curl -i \
--request POST \
--header "Content-Type: multipart/form-data" \
-F "image=@test.jpg" \
localhost:5000/predict
One common way of distributing this model API server for production deployment, is via Docker containers. And BentoML provides a convenient way to do that.
Note that docker is not available in Google Colab. You will need to download and run this notebook locally to try out this containerization with docker feature.
If you already have docker configured, simply run the follow command to product a docker container serving the IrisClassifier prediction service created above:
!bentoml containerize PetClassification:latest
[2020-09-22 18:07:15,056] INFO - Getting latest version PetClassification:20200922174900_F25F3F Found Bento: /Users/bozhaoyu/bentoml/repository/PetClassification/20200922174900_F25F3F [2020-09-22 18:07:15,098] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle. [2020-09-22 18:07:15,114] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+3.gcebf2015 Tag not specified, using tag parsed from BentoService: 'petclassification:20200922174900_F25F3F' Building Docker image petclassification:20200922174900_F25F3F from PetClassification:latest -we in here processed docker file (None, None) root in create archive /Users/bozhaoyu/bentoml/repository/PetClassification/20200922174900_F25F3F ['Dockerfile', 'MANIFEST.in', 'PetClassification', 'PetClassification/__init__.py', 'PetClassification/__pycache__', 'PetClassification/__pycache__/pet_classification.cpython-37.pyc', 'PetClassification/artifacts', 'PetClassification/artifacts/__init__.py', 'PetClassification/artifacts/pet_classifer.pkl', 'PetClassification/bentoml.yml', 'PetClassification/pet_classification.py', 'README.md', 'bentoml-init.sh', 'bentoml.yml', 'bundled_pip_dependencies', 'bundled_pip_dependencies/BentoML-0.9.0rc0+3.gcebf2015.tar.gz', 'docker-entrypoint.sh', 'environment.yml', 'python_version', 'requirements.txt', 'setup.py'] \about to build about to upgrade params check each param and update if use config proxy if buildargs if shmsize if labels if cache from if target if network_mode if squash if extra hosts is not None if platform is not None if isolcation is not None if context is not None setting auth {'Content-Type': 'application/tar'} |docker build <tempfile._TemporaryFileWrapper object at 0x7ff6cd574d30> {'t': 'petclassification:20200922174900_F25F3F', 'remote': None, 'q': False, 'nocache': False, 'rm': False, 'forcerm': False, 'pull': False, 'dockerfile': (None, None)} \docker response <Response [200]> context closes print responses Step 1/15 : FROM bentoml/model-server:0.9.0.pre ---> a25066aa8b0e Step 2/15 : ARG EXTRA_PIP_INSTALL_ARGS= ---> Using cache ---> 315719b8980e Step 3/15 : ENV EXTRA_PIP_INSTALL_ARGS $EXTRA_PIP_INSTALL_ARGS ---> Using cache ---> a3b6c8107d94 Step 4/15 : COPY environment.yml requirements.txt setup.sh* bentoml-init.sh python_version* /bento/ / ---> 620f679281bb Step 5/15 : WORKDIR /bento | ---> Running in 748311d8f81c \ ---> a8c99c4676f4 Step 6/15 : RUN chmod +x /bento/bentoml-init.sh ---> Running in 93992fc4d4e1 / ---> 8f59bfb17869 Step 7/15 : RUN if [ -f /bento/bentoml-init.sh ]; then bash -c /bento/bentoml-init.sh; fi ---> Running in 1e1ae04be7b0 -+++ dirname /bento/bentoml-init.sh ++ cd /bento ++ pwd -P + SAVED_BUNDLE_PATH=/bento + cd /bento + '[' -f ./setup.sh ']' + '[' -f ./python_version ']' ++ cat ./python_version + PY_VERSION_SAVED=3.7.3 + DESIRED_PY_VERSION=3.7 ++ python -c 'import sys; print(f"{sys.version_info.major}.{sys.version_info.minor}")' + CURRENT_PY_VERSION=3.7 + [[ 3.7 == \3\.\7 ]] + echo 'Python Version in docker base image 3.7 matches requirement python=3.7. Skipping.' Python Version in docker base image 3.7 matches requirement python=3.7. Skipping. Updating conda base environment with environment.yml + command -v conda + echo 'Updating conda base environment with environment.yml' + conda env update -n base -f ./environment.yml \Collecting package metadata (repodata.json): ...working... |done Solving environment: ...working... -done / Downloading and Extracting Packages certifi-2020.6.20 | 151 KB | | 0% certifi-2020.6.20 | 151 KB | # | 11% certifi-2020.6.20 | 151 KB | ########## | 100% certifi-2020.6.20 | 151 KB | ########## | 100% openssl-1.1.1h | 2.1 MB | | 0% openssl-1.1.1h | 2.1 MB | #1 | 12% openssl-1.1.1h | 2.1 MB | #####4 | 55% openssl-1.1.1h | 2.1 MB | ########## | 100% openssl-1.1.1h | 2.1 MB | ########## | 100% python_abi-3.7 | 4 KB | | 0% python_abi-3.7 | 4 KB | ########## | 100% cffi-1.14.3 | 223 KB | | 0% cffi-1.14.3 | 223 KB | ########## | 100% cffi-1.14.3 | 223 KB | ########## | 100% libffi-3.2.1 | 47 KB | | 0% libffi-3.2.1 | 47 KB | ########## | 100% ca-certificates-2020 | 145 KB | | 0% ca-certificates-2020 | 145 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1)) (0.15.87) Requirement already satisfied: humanfriendly in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (8.2) Requirement already satisfied: click>=7.0 in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (7.1.2) |Requirement already satisfied: python-dateutil<3.0.0,>=2.7.3 in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (2.8.1) Requirement already satisfied: python-json-logger in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.1.11) Requirement already satisfied: boto3 in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.15.2) Requirement already satisfied: prometheus-client in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.8.0) Requirement already satisfied: packaging in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (20.4) Requirement already satisfied: gunicorn in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (20.0.4) Requirement already satisfied: configparser in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (5.0.0) Requirement already satisfied: numpy in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.19.2) Requirement already satisfied: py-zipkin in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.20.0) Requirement already satisfied: protobuf>=3.6.0 in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (3.13.0) \Collecting bottleneck - Downloading Bottleneck-1.3.2.tar.gz (88 kB) Installing build dependencies: started / Installing build dependencies: finished with status 'done' Getting requirements to build wheel: started - Getting requirements to build wheel: finished with status 'done' Preparing wheel metadata: started \ Preparing wheel metadata: finished with status 'done' /Collecting Pillow Downloading Pillow-7.2.0-cp37-cp37m-manylinux1_x86_64.whl (2.2 MB) |Collecting pandas Downloading pandas-1.1.2-cp37-cp37m-manylinux1_x86_64.whl (10.5 MB) |Collecting fastprogress>=0.2.1 Downloading fastprogress-1.0.0-py3-none-any.whl (12 kB) |Collecting scipy Downloading scipy-1.5.2-cp37-cp37m-manylinux1_x86_64.whl (25.9 MB) -Collecting spacy>=2.0.18; python_version < "3.8" / Downloading spacy-2.3.2-cp37-cp37m-manylinux1_x86_64.whl (9.9 MB) -Collecting beautifulsoup4 Downloading beautifulsoup4-4.9.1-py3-none-any.whl (115 kB) |Collecting numexpr Downloading numexpr-2.7.1-cp37-cp37m-manylinux1_x86_64.whl (162 kB) \Collecting pyyaml - Downloading PyYAML-5.3.1.tar.gz (269 kB) -Collecting matplotlib / Downloading matplotlib-3.3.2-cp37-cp37m-manylinux1_x86_64.whl (11.6 MB) -Collecting nvidia-ml-py3 Downloading nvidia-ml-py3-7.352.0.tar.gz (19 kB) -Collecting torchvision Downloading torchvision-0.7.0-cp37-cp37m-manylinux1_x86_64.whl (5.9 MB) -Collecting future Downloading future-0.18.2.tar.gz (829 kB) /Requirement already satisfied: async-timeout<4.0,>=3.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (3.0.1) Requirement already satisfied: yarl<2.0,>=1.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.5.1) Requirement already satisfied: attrs>=17.3.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (20.2.0) |Requirement already satisfied: chardet<4.0,>=2.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (3.0.4) Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.25.10) Requirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (2.10) Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from sqlalchemy-utils<0.36.8->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.15.0) Requirement already satisfied: Jinja2>=2.10.1 in /opt/conda/lib/python3.7/site-packages (from flask->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (2.11.2) Requirement already satisfied: Werkzeug>=0.15 in /opt/conda/lib/python3.7/site-packages (from flask->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.0.1) Requirement already satisfied: itsdangerous>=0.24 in /opt/conda/lib/python3.7/site-packages (from flask->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.1.0) Requirement already satisfied: python-editor>=0.3 in /opt/conda/lib/python3.7/site-packages (from alembic->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.0.4) Requirement already satisfied: Mako in /opt/conda/lib/python3.7/site-packages (from alembic->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.1.3) Requirement already satisfied: setuptools in /opt/conda/lib/python3.7/site-packages (from cerberus->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (49.6.0.post20200814) Requirement already satisfied: websocket-client>=0.32.0 in /opt/conda/lib/python3.7/site-packages (from docker->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.57.0) Requirement already satisfied: botocore<1.19.0,>=1.18.2 in /opt/conda/lib/python3.7/site-packages (from boto3->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.18.2) Requirement already satisfied: s3transfer<0.4.0,>=0.3.0 in /opt/conda/lib/python3.7/site-packages (from boto3->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.3.3) Requirement already satisfied: jmespath<1.0.0,>=0.7.1 in /opt/conda/lib/python3.7/site-packages (from boto3->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.10.0) Requirement already satisfied: pyparsing>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (2.4.7) Requirement already satisfied: thriftpy2>=0.4.0 in /opt/conda/lib/python3.7/site-packages (from py-zipkin->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.4.11) -Collecting pytz>=2017.2 / Downloading pytz-2020.1-py2.py3-none-any.whl (510 kB) |Collecting blis<0.5.0,>=0.4.0 \ Downloading blis-0.4.1-cp37-cp37m-manylinux1_x86_64.whl (3.7 MB) |Collecting preshed<3.1.0,>=3.0.2 \ Downloading preshed-3.0.2-cp37-cp37m-manylinux1_x86_64.whl (118 kB) -Collecting catalogue<1.1.0,>=0.0.7 Downloading catalogue-1.0.0-py2.py3-none-any.whl (7.7 kB) Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /opt/conda/lib/python3.7/site-packages (from spacy>=2.0.18; python_version < "3.8"->fastai==1.0.61->-r ./requirements.txt (line 2)) (4.48.2) /Collecting murmurhash<1.1.0,>=0.28.0 Downloading murmurhash-1.0.2-cp37-cp37m-manylinux1_x86_64.whl (19 kB) |Collecting wasabi<1.1.0,>=0.4.0 Downloading wasabi-0.8.0-py3-none-any.whl (23 kB) \Collecting cymem<2.1.0,>=2.0.2 Downloading cymem-2.0.3-cp37-cp37m-manylinux1_x86_64.whl (32 kB) -Collecting plac<1.2.0,>=0.9.6 Downloading plac-1.1.3-py2.py3-none-any.whl (20 kB) /Collecting srsly<1.1.0,>=1.0.2 | Downloading srsly-1.0.2-cp37-cp37m-manylinux1_x86_64.whl (185 kB) /Collecting thinc==7.4.1 Downloading thinc-7.4.1-cp37-cp37m-manylinux1_x86_64.whl (2.1 MB) -Collecting soupsieve>1.2 Downloading soupsieve-2.0.1-py3-none-any.whl (32 kB) /Collecting cycler>=0.10 Downloading cycler-0.10.0-py2.py3-none-any.whl (6.5 kB) |Collecting kiwisolver>=1.0.1 Downloading kiwisolver-1.2.0-cp37-cp37m-manylinux1_x86_64.whl (88 kB) Requirement already satisfied: typing-extensions>=3.7.4; python_version < "3.8" in /opt/conda/lib/python3.7/site-packages (from yarl<2.0,>=1.0->aiohttp->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (3.7.4.3) Requirement already satisfied: MarkupSafe>=0.23 in /opt/conda/lib/python3.7/site-packages (from Jinja2>=2.10.1->flask->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.1.1) Requirement already satisfied: ply<4.0,>=3.4 in /opt/conda/lib/python3.7/site-packages (from thriftpy2>=0.4.0->py-zipkin->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (3.11) \Collecting importlib-metadata>=0.20; python_version < "3.8" - Downloading importlib_metadata-2.0.0-py2.py3-none-any.whl (31 kB) /Collecting zipp>=0.5 Downloading zipp-3.2.0-py3-none-any.whl (5.1 kB) Building wheels for collected packages: bottleneck, pyyaml, nvidia-ml-py3, future Building wheel for bottleneck (PEP 517): started | Building wheel for bottleneck (PEP 517): finished with status 'done' Created wheel for bottleneck: filename=Bottleneck-1.3.2-cp37-cp37m-linux_x86_64.whl size=386274 sha256=88121d9f7b0fa037534f41e261612790cb42c837f1abf65623b9510346a64409 Stored in directory: /tmp/pip-ephem-wheel-cache-f6i4rnbq/wheels/87/85/9c/a325c89ff0498660ef8a335fb4b3912939c273ea4f094af29f Building wheel for pyyaml (setup.py): started \ Building wheel for pyyaml (setup.py): finished with status 'done' Created wheel for pyyaml: filename=PyYAML-5.3.1-cp37-cp37m-linux_x86_64.whl size=44619 sha256=2eb2a99a7fa65346e6d4893f856b6f82387be995421c4afd79152d65c689c749 Stored in directory: /tmp/pip-ephem-wheel-cache-f6i4rnbq/wheels/5e/03/1e/e1e954795d6f35dfc7b637fe2277bff021303bd9570ecea653 Building wheel for nvidia-ml-py3 (setup.py): started | Building wheel for nvidia-ml-py3 (setup.py): finished with status 'done' Created wheel for nvidia-ml-py3: filename=nvidia_ml_py3-7.352.0-py3-none-any.whl size=19191 sha256=645e7135884f4003044530a970eaeeb9766c911b02092aefc465f270ba1e34a6 Stored in directory: /tmp/pip-ephem-wheel-cache-f6i4rnbq/wheels/df/99/da/c34f202dc8fd1dffd35e0ecf1a7d7f8374ca05fbcbaf974b83 Building wheel for future (setup.py): started - Building wheel for future (setup.py): finished with status 'done' Created wheel for future: filename=future-0.18.2-py3-none-any.whl size=491059 sha256=cc1fcb02bd96cb1aec99e45cadda53dd7fe0289172d314d22e62006ab62a66ef Stored in directory: /tmp/pip-ephem-wheel-cache-f6i4rnbq/wheels/56/b0/fe/4410d17b32f1f0c3cf54cdfb2bc04d7b4b8f4ae377e2229ba0 Successfully built bottleneck pyyaml nvidia-ml-py3 future \Installing collected packages: bottleneck, Pillow, pytz, pandas, fastprogress, scipy, future, torch, blis, murmurhash, cymem, preshed, zipp, importlib-metadata, catalogue, wasabi, plac, srsly, thinc, spacy, soupsieve, beautifulsoup4, numexpr, pyyaml, cycler, kiwisolver, matplotlib, nvidia-ml-py3, torchvision, fastai, imageio |Successfully installed Pillow-7.2.0 beautifulsoup4-4.9.1 blis-0.4.1 bottleneck-1.3.2 catalogue-1.0.0 cycler-0.10.0 cymem-2.0.3 fastai-1.0.61 fastprogress-1.0.0 future-0.18.2 imageio-2.5.0 importlib-metadata-2.0.0 kiwisolver-1.2.0 matplotlib-3.3.2 murmurhash-1.0.2 numexpr-2.7.1 nvidia-ml-py3-7.352.0 pandas-1.1.2 plac-1.1.3 preshed-3.0.2 pytz-2020.1 pyyaml-5.3.1 scipy-1.5.2 soupsieve-2.0.1 spacy-2.3.2 srsly-1.0.2 thinc-7.4.1 torch-1.6.0 torchvision-0.7.0 wasabi-0.8.0 zipp-3.2.0 | ---> e75835a54407 Step 8/15 : COPY . /bento | ---> e25fabebfe7b Step 9/15 : RUN if [ -d /bento/bundled_pip_dependencies ]; then pip install -U bundled_pip_dependencies/* ;fi ---> Running in c36ac282169e |Processing ./bundled_pip_dependencies/BentoML-0.9.0rc0+3.gcebf2015.tar.gz / Installing build dependencies: started / Installing build dependencies: finished with status 'done' Getting requirements to build wheel: started | Getting requirements to build wheel: finished with status 'done' Preparing wheel metadata: started - Preparing wheel metadata: finished with status 'done' |Requirement already satisfied, skipping upgrade: sqlalchemy>=1.3.0 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.3.19) Requirement already satisfied, skipping upgrade: configparser in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (5.0.0) Requirement already satisfied, skipping upgrade: protobuf>=3.6.0 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (3.13.0) Requirement already satisfied, skipping upgrade: boto3 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.15.2) Requirement already satisfied, skipping upgrade: flask in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.1.2) Requirement already satisfied, skipping upgrade: prometheus-client in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.8.0) Requirement already satisfied, skipping upgrade: alembic in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.4.3) Requirement already satisfied, skipping upgrade: tabulate in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.8.7) Requirement already satisfied, skipping upgrade: gunicorn in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (20.0.4) Requirement already satisfied, skipping upgrade: py-zipkin in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.20.0) Requirement already satisfied, skipping upgrade: humanfriendly in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (8.2) \Requirement already satisfied, skipping upgrade: python-dateutil<3.0.0,>=2.7.3 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (2.8.1) Requirement already satisfied, skipping upgrade: psutil in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (5.7.2) Requirement already satisfied, skipping upgrade: grpcio<=1.27.2 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.27.2) Requirement already satisfied, skipping upgrade: requests in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (2.24.0) Requirement already satisfied, skipping upgrade: python-json-logger in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.1.11) Requirement already satisfied, skipping upgrade: aiohttp in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (3.6.2) Requirement already satisfied, skipping upgrade: cerberus in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.3.2) Requirement already satisfied, skipping upgrade: numpy in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.19.2) Requirement already satisfied, skipping upgrade: ruamel.yaml>=0.15.0 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.15.87) Requirement already satisfied, skipping upgrade: multidict in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (4.7.6) Requirement already satisfied, skipping upgrade: certifi in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (2020.6.20) Requirement already satisfied, skipping upgrade: click>=7.0 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (7.1.2) Requirement already satisfied, skipping upgrade: docker in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (4.3.1) Requirement already satisfied, skipping upgrade: packaging in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (20.4) Requirement already satisfied, skipping upgrade: sqlalchemy-utils<0.36.8 in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.36.7) -Requirement already satisfied, skipping upgrade: six>=1.9 in /opt/conda/lib/python3.7/site-packages (from protobuf>=3.6.0->BentoML==0.9.0rc0+3.gcebf2015) (1.15.0) Requirement already satisfied, skipping upgrade: setuptools in /opt/conda/lib/python3.7/site-packages (from protobuf>=3.6.0->BentoML==0.9.0rc0+3.gcebf2015) (49.6.0.post20200814) Requirement already satisfied, skipping upgrade: jmespath<1.0.0,>=0.7.1 in /opt/conda/lib/python3.7/site-packages (from boto3->BentoML==0.9.0rc0+3.gcebf2015) (0.10.0) Requirement already satisfied, skipping upgrade: botocore<1.19.0,>=1.18.2 in /opt/conda/lib/python3.7/site-packages (from boto3->BentoML==0.9.0rc0+3.gcebf2015) (1.18.2) Requirement already satisfied, skipping upgrade: s3transfer<0.4.0,>=0.3.0 in /opt/conda/lib/python3.7/site-packages (from boto3->BentoML==0.9.0rc0+3.gcebf2015) (0.3.3) /Requirement already satisfied, skipping upgrade: Jinja2>=2.10.1 in /opt/conda/lib/python3.7/site-packages (from flask->BentoML==0.9.0rc0+3.gcebf2015) (2.11.2) Requirement already satisfied, skipping upgrade: itsdangerous>=0.24 in /opt/conda/lib/python3.7/site-packages (from flask->BentoML==0.9.0rc0+3.gcebf2015) (1.1.0) Requirement already satisfied, skipping upgrade: Werkzeug>=0.15 in /opt/conda/lib/python3.7/site-packages (from flask->BentoML==0.9.0rc0+3.gcebf2015) (1.0.1) Requirement already satisfied, skipping upgrade: python-editor>=0.3 in /opt/conda/lib/python3.7/site-packages (from alembic->BentoML==0.9.0rc0+3.gcebf2015) (1.0.4) Requirement already satisfied, skipping upgrade: Mako in /opt/conda/lib/python3.7/site-packages (from alembic->BentoML==0.9.0rc0+3.gcebf2015) (1.1.3) Requirement already satisfied, skipping upgrade: thriftpy2>=0.4.0 in /opt/conda/lib/python3.7/site-packages (from py-zipkin->BentoML==0.9.0rc0+3.gcebf2015) (0.4.11) Requirement already satisfied, skipping upgrade: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->BentoML==0.9.0rc0+3.gcebf2015) (1.25.10) Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from requests->BentoML==0.9.0rc0+3.gcebf2015) (3.0.4) Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->BentoML==0.9.0rc0+3.gcebf2015) (2.10) Requirement already satisfied, skipping upgrade: attrs>=17.3.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->BentoML==0.9.0rc0+3.gcebf2015) (20.2.0) Requirement already satisfied, skipping upgrade: yarl<2.0,>=1.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->BentoML==0.9.0rc0+3.gcebf2015) (1.5.1) Requirement already satisfied, skipping upgrade: async-timeout<4.0,>=3.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->BentoML==0.9.0rc0+3.gcebf2015) (3.0.1) Requirement already satisfied, skipping upgrade: websocket-client>=0.32.0 in /opt/conda/lib/python3.7/site-packages (from docker->BentoML==0.9.0rc0+3.gcebf2015) (0.57.0) |Requirement already satisfied, skipping upgrade: pyparsing>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging->BentoML==0.9.0rc0+3.gcebf2015) (2.4.7) Requirement already satisfied, skipping upgrade: MarkupSafe>=0.23 in /opt/conda/lib/python3.7/site-packages (from Jinja2>=2.10.1->flask->BentoML==0.9.0rc0+3.gcebf2015) (1.1.1) Requirement already satisfied, skipping upgrade: ply<4.0,>=3.4 in /opt/conda/lib/python3.7/site-packages (from thriftpy2>=0.4.0->py-zipkin->BentoML==0.9.0rc0+3.gcebf2015) (3.11) Requirement already satisfied, skipping upgrade: typing-extensions>=3.7.4; python_version < "3.8" in /opt/conda/lib/python3.7/site-packages (from yarl<2.0,>=1.0->aiohttp->BentoML==0.9.0rc0+3.gcebf2015) (3.7.4.3) Building wheels for collected packages: BentoML Building wheel for BentoML (PEP 517): started | Building wheel for BentoML (PEP 517): finished with status 'done' Created wheel for BentoML: filename=BentoML-0.9.0rc0+3.gcebf2015-py3-none-any.whl size=3064091 sha256=79250e21b71f04efb1fd86188407884c15041f511160f3c6b1c9113e6b72c79d Stored in directory: /root/.cache/pip/wheels/a0/45/41/62152db705af4ff47e7a3d6abf6247986eef4aa1b94a58d3b9 Successfully built BentoML -Installing collected packages: BentoML Attempting uninstall: BentoML Found existing installation: BentoML 0.9.0rc0 | Uninstalling BentoML-0.9.0rc0: - Successfully uninstalled BentoML-0.9.0rc0 /Successfully installed BentoML-0.9.0rc0+3.gcebf2015 | ---> 4356037cff29 Step 10/15 : ENV PORT 5000 ---> Running in 441be054cda4 \ ---> 32a586ff17ff Step 11/15 : EXPOSE $PORT - ---> Running in 8de4ab9267ff / ---> b8fe98623e2a Step 12/15 : COPY docker-entrypoint.sh /usr/local/bin/ | ---> 5d1f6bfef6b4 Step 13/15 : RUN chmod +x /usr/local/bin/docker-entrypoint.sh \ ---> Running in ebf4403d6e3d - ---> 560393532aa9 Step 14/15 : ENTRYPOINT [ "docker-entrypoint.sh" ] / ---> Running in d0a576ce4ce9 | ---> d266b4444454 Step 15/15 : CMD ["bentoml", "serve-gunicorn", "/bento"] ---> Running in d7b225b03c60 \ ---> 1b0a26d38dc7 Successfully built 1b0a26d38dc7 -Successfully tagged petclassification:20200922174900_F25F3F Finished building petclassification:20200922174900_F25F3F from PetClassification:latest
Start a container with the docker image built in the previous step:
!docker run -p 5000:5000 PetClassification/20200122122128_513734
bentoml.load is the API for loading a BentoML packaged model in python:
from bentoml import load
service = load(saved_path)
print(service.predict(data.get(0)))
[2019-09-17 15:20:59,886] WARNING - Module `pet_classification` already loaded, using existing imported module. (Category Egyptian_Mau, tensor(5), tensor([8.1198e-05, 4.7572e-03, 8.4651e-06, 7.2410e-04, 4.4823e-04, 9.9232e-01, 1.2686e-04, 8.9391e-06, 3.2297e-05, 2.6294e-04, 1.2570e-05, 1.7887e-04, 2.3823e-05, 1.0635e-05, 3.7823e-06, 2.6734e-05, 4.9237e-05, 3.0513e-05, 5.5845e-05, 7.1444e-05, 3.7852e-04, 1.9912e-05, 4.3253e-06, 2.8950e-05, 7.1766e-06, 5.2756e-06, 1.9716e-05, 2.6185e-06, 9.0641e-05, 1.7248e-05, 9.3070e-06, 3.1759e-05, 7.4544e-05, 1.3818e-05, 2.7183e-05, 1.8018e-05, 1.3240e-05]))
BentoML cli supports loading and running a packaged model from CLI. With the DataframeInput adapter, the CLI command supports reading input Dataframe data from CLI argument or local csv or json files:
!bentoml run PetClassification:latest predict --input-file test.jpg
[2020-01-22 12:50:18,951] WARNING - BentoML local changes detected - Local BentoML repository including all code changes will be bundled together with the BentoService bundle. When used with docker, the base docker image will be default to same version as last PyPI release at version: 0.5.8. You can also force bentoml to use a specific version for deploying your BentoService bundle, by setting the config 'core/bentoml_deploy_version' to a pinned version or your custom BentoML on github, e.g.:'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}' [2020-01-22 12:50:18,964] WARNING - Saved BentoService bundle version mismatch: loading BentoServie bundle create with BentoML version 0.5.8, but loading from BentoML version 0.5.8+23.g1dd72d3 [2020-01-22 12:50:22,038] WARNING - BentoML local changes detected - Local BentoML repository including all code changes will be bundled together with the BentoService bundle. When used with docker, the base docker image will be default to same version as last PyPI release at version: 0.5.8. You can also force bentoml to use a specific version for deploying your BentoService bundle, by setting the config 'core/bentoml_deploy_version' to a pinned version or your custom BentoML on github, e.g.:'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}' [2020-01-22 12:50:22,157] WARNING - BentoML local changes detected - Local BentoML repository including all code changes will be bundled together with the BentoService bundle. When used with docker, the base docker image will be default to same version as last PyPI release at version: 0.5.8. You can also force bentoml to use a specific version for deploying your BentoService bundle, by setting the config 'core/bentoml_deploy_version' to a pinned version or your custom BentoML on github, e.g.:'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}' (Category yorkshire_terrier, tensor(36), tensor([6.5418e-06, 1.1117e-06, 1.4023e-06, 1.2001e-06, 1.4748e-07, 5.9564e-08, 1.6650e-06, 1.6947e-06, 1.4603e-07, 8.4881e-08, 8.7069e-07, 3.1522e-07, 7.8667e-08, 3.8861e-07, 1.8602e-06, 8.0380e-06, 6.4890e-07, 5.7006e-06, 3.4203e-06, 6.0791e-08, 1.5988e-07, 1.5740e-07, 8.2322e-06, 1.0582e-06, 2.8686e-07, 3.3809e-07, 2.8787e-05, 6.6988e-08, 8.7025e-06, 2.5589e-07, 1.6868e-07, 1.1191e-07, 3.5333e-06, 2.2819e-07, 7.3852e-07, 5.6413e-07, 9.9991e-01]))
If you are at a small team with limited engineering or DevOps resources, try out automated deployment with BentoML CLI, currently supporting AWS Lambda, AWS SageMaker, and Azure Functions:
If the cloud platform you are working with is not on the list above, try out these step-by-step guide on manually deploying BentoML packaged model to cloud platforms:
Lastly, if you have a DevOps or ML Engineering team who's operating a Kubernetes or OpenShift cluster, use the following guides as references for implementating your deployment strategy: