Python Machine Learning 3rd Edition by Sebastian Raschka & Vahid Mirjalili, Packt Publishing Ltd. 2019
Code Repository: https://github.com/rasbt/python-machine-learning-book-3rd-edition
Code License: MIT License
Note that the optional watermark extension is a small IPython notebook plugin that I developed to make the code reproducible. You can just skip the following line(s).
%load_ext watermark
%watermark -a "Sebastian Raschka & Vahid Mirjalili" -u -d -p numpy,scipy,matplotlib,tensorflow
Sebastian Raschka & Vahid Mirjalili last updated: 2019-11-03 numpy 1.17.3 scipy 1.3.1 matplotlib 3.1.1 tensorflow 2.0.0
import numpy as np
import tensorflow as tf
import pandas as pd
from IPython.display import Image
tf.random.set_seed(1)
np.random.seed(1)
Image(filename='images/02.png', width=700)
dataset_path = tf.keras.utils.get_file("auto-mpg.data",
("http://archive.ics.uci.edu/ml/machine-learning-databases"
"/auto-mpg/auto-mpg.data"))
column_names = ['MPG', 'Cylinders', 'Displacement', 'Horsepower',
'Weight', 'Acceleration', 'ModelYear', 'Origin']
df = pd.read_csv(dataset_path, names=column_names,
na_values = "?", comment='\t',
sep=" ", skipinitialspace=True)
df.tail()
MPG | Cylinders | Displacement | Horsepower | Weight | Acceleration | ModelYear | Origin | |
---|---|---|---|---|---|---|---|---|
393 | 27.0 | 4 | 140.0 | 86.0 | 2790.0 | 15.6 | 82 | 1 |
394 | 44.0 | 4 | 97.0 | 52.0 | 2130.0 | 24.6 | 82 | 2 |
395 | 32.0 | 4 | 135.0 | 84.0 | 2295.0 | 11.6 | 82 | 1 |
396 | 28.0 | 4 | 120.0 | 79.0 | 2625.0 | 18.6 | 82 | 1 |
397 | 31.0 | 4 | 119.0 | 82.0 | 2720.0 | 19.4 | 82 | 1 |
print(df.isna().sum())
df = df.dropna()
df = df.reset_index(drop=True)
df.tail()
MPG 0 Cylinders 0 Displacement 0 Horsepower 6 Weight 0 Acceleration 0 ModelYear 0 Origin 0 dtype: int64
MPG | Cylinders | Displacement | Horsepower | Weight | Acceleration | ModelYear | Origin | |
---|---|---|---|---|---|---|---|---|
387 | 27.0 | 4 | 140.0 | 86.0 | 2790.0 | 15.6 | 82 | 1 |
388 | 44.0 | 4 | 97.0 | 52.0 | 2130.0 | 24.6 | 82 | 2 |
389 | 32.0 | 4 | 135.0 | 84.0 | 2295.0 | 11.6 | 82 | 1 |
390 | 28.0 | 4 | 120.0 | 79.0 | 2625.0 | 18.6 | 82 | 1 |
391 | 31.0 | 4 | 119.0 | 82.0 | 2720.0 | 19.4 | 82 | 1 |
import sklearn
import sklearn.model_selection
df_train, df_test = sklearn.model_selection.train_test_split(df, train_size=0.8)
train_stats = df_train.describe().transpose()
train_stats
count | mean | std | min | 25% | 50% | 75% | max | |
---|---|---|---|---|---|---|---|---|
MPG | 313.0 | 23.404153 | 7.666909 | 9.0 | 17.5 | 23.0 | 29.0 | 46.6 |
Cylinders | 313.0 | 5.402556 | 1.701506 | 3.0 | 4.0 | 4.0 | 8.0 | 8.0 |
Displacement | 313.0 | 189.512780 | 102.675646 | 68.0 | 104.0 | 140.0 | 260.0 | 455.0 |
Horsepower | 313.0 | 102.929712 | 37.919046 | 46.0 | 75.0 | 92.0 | 120.0 | 230.0 |
Weight | 313.0 | 2961.198083 | 848.602146 | 1613.0 | 2219.0 | 2755.0 | 3574.0 | 5140.0 |
Acceleration | 313.0 | 15.704473 | 2.725399 | 8.5 | 14.0 | 15.5 | 17.3 | 24.8 |
ModelYear | 313.0 | 75.929712 | 3.675305 | 70.0 | 73.0 | 76.0 | 79.0 | 82.0 |
Origin | 313.0 | 1.591054 | 0.807923 | 1.0 | 1.0 | 1.0 | 2.0 | 3.0 |
numeric_column_names = ['Cylinders', 'Displacement', 'Horsepower', 'Weight', 'Acceleration']
df_train_norm, df_test_norm = df_train.copy(), df_test.copy()
for col_name in numeric_column_names:
mean = train_stats.loc[col_name, 'mean']
std = train_stats.loc[col_name, 'std']
df_train_norm.loc[:, col_name] = (df_train_norm.loc[:, col_name] - mean)/std
df_test_norm.loc[:, col_name] = (df_test_norm.loc[:, col_name] - mean)/std
df_train_norm.tail()
MPG | Cylinders | Displacement | Horsepower | Weight | Acceleration | ModelYear | Origin | |
---|---|---|---|---|---|---|---|---|
203 | 28.0 | -0.824303 | -0.901020 | -0.736562 | -0.950031 | 0.255202 | 76 | 3 |
255 | 19.4 | 0.351127 | 0.413800 | -0.340982 | 0.293190 | 0.548737 | 78 | 1 |
72 | 13.0 | 1.526556 | 1.144256 | 0.713897 | 1.339617 | -0.625403 | 72 | 1 |
235 | 30.5 | -0.824303 | -0.891280 | -1.053025 | -1.072585 | 0.475353 | 77 | 1 |
37 | 14.0 | 1.526556 | 1.563051 | 1.636916 | 1.470420 | -1.359240 | 71 | 1 |
numeric_features = []
for col_name in numeric_column_names:
numeric_features.append(tf.feature_column.numeric_column(key=col_name))
numeric_features
[NumericColumn(key='Cylinders', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Displacement', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Horsepower', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Weight', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Acceleration', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None)]
feature_year = tf.feature_column.numeric_column(key="ModelYear")
bucketized_features = []
bucketized_features.append(tf.feature_column.bucketized_column(
source_column=feature_year,
boundaries=[73, 76, 79]))
print(bucketized_features)
[BucketizedColumn(source_column=NumericColumn(key='ModelYear', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), boundaries=(73, 76, 79))]
feature_origin = tf.feature_column.categorical_column_with_vocabulary_list(
key='Origin',
vocabulary_list=[1, 2, 3])
categorical_indicator_features = []
categorical_indicator_features.append(tf.feature_column.indicator_column(feature_origin))
print(categorical_indicator_features)
[IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(key='Origin', vocabulary_list=(1, 2, 3), dtype=tf.int64, default_value=-1, num_oov_buckets=0))]
def train_input_fn(df_train, batch_size=8):
df = df_train.copy()
train_x, train_y = df, df.pop('MPG')
dataset = tf.data.Dataset.from_tensor_slices((dict(train_x), train_y))
# shuffle, repeat, and batch the examples
return dataset.shuffle(1000).repeat().batch(batch_size)
## inspection
ds = train_input_fn(df_train_norm)
batch = next(iter(ds))
print('Keys:', batch[0].keys())
print('Batch Model Years:', batch[0]['ModelYear'])
Keys: dict_keys(['Cylinders', 'Displacement', 'Horsepower', 'Weight', 'Acceleration', 'ModelYear', 'Origin']) Batch Model Years: tf.Tensor([82 78 76 72 78 73 70 78], shape=(8,), dtype=int32)
all_feature_columns = (numeric_features +
bucketized_features +
categorical_indicator_features)
print(all_feature_columns)
[NumericColumn(key='Cylinders', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Displacement', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Horsepower', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Weight', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Acceleration', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), BucketizedColumn(source_column=NumericColumn(key='ModelYear', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), boundaries=(73, 76, 79)), IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(key='Origin', vocabulary_list=(1, 2, 3), dtype=tf.int64, default_value=-1, num_oov_buckets=0))]
regressor = tf.estimator.DNNRegressor(
feature_columns=all_feature_columns,
hidden_units=[32, 10],
model_dir='models/autompg-dnnregressor/')
INFO:tensorflow:Using default config. INFO:tensorflow:Using config: {'_model_dir': 'models/autompg-dnnregressor/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true graph_options { rewrite_options { meta_optimizer_iterations: ONE } } , '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f47c054d650>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}
EPOCHS = 1000
BATCH_SIZE = 8
total_steps = EPOCHS * int(np.ceil(len(df_train) / BATCH_SIZE))
print('Training Steps:', total_steps)
regressor.train(
input_fn=lambda:train_input_fn(df_train_norm, batch_size=BATCH_SIZE),
steps=total_steps)
Training Steps: 40000 WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version. Instructions for updating: If using Keras pass *_constraint arguments to layers. WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version. Instructions for updating: Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts. INFO:tensorflow:Calling model_fn. WARNING:tensorflow:Layer dnn is casting an input tensor from dtype float64 to the layer's dtype of float32, which is new behavior in TensorFlow 2. The layer has dtype float32 because it's dtype defaults to floatx. If you intended to run this layer in float32, you can safely ignore this warning. If in doubt, this warning is likely only an issue if you are porting a TensorFlow 1.X model to TensorFlow 2. To change all layers to have dtype float64 by default, call `tf.keras.backend.set_floatx('float64')`. To change just this layer, pass dtype='float64' to the layer constructor. If you are the author of this layer, you can disable autocasting by passing autocast=False to the base Layer constructor. WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_core/python/feature_column/feature_column_v2.py:4276: IndicatorColumn._variable_shape (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version. Instructions for updating: The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead. WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_core/python/feature_column/feature_column_v2.py:4331: VocabularyListCategoricalColumn._num_buckets (from tensorflow.python.feature_column.feature_column_v2) is deprecated and will be removed in a future version. Instructions for updating: The old _FeatureColumn APIs are being deprecated. Please use the new FeatureColumn APIs instead. WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/head/regression_head.py:156: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_core/python/keras/optimizer_v2/adagrad.py:108: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version. Instructions for updating: Call initializer instance with the dtype argument instead of passing it to the constructor INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Create CheckpointSaverHook. INFO:tensorflow:Graph was finalized. INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Saving checkpoints for 0 into models/autompg-dnnregressor/model.ckpt. INFO:tensorflow:loss = 610.1284, step = 0 INFO:tensorflow:global_step/sec: 448.416 INFO:tensorflow:loss = 712.06726, step = 100 (0.225 sec) INFO:tensorflow:global_step/sec: 585.712 INFO:tensorflow:loss = 822.8959, step = 200 (0.170 sec) INFO:tensorflow:global_step/sec: 648.546 INFO:tensorflow:loss = 710.2063, step = 300 (0.154 sec) INFO:tensorflow:global_step/sec: 648.579 INFO:tensorflow:loss = 583.29407, step = 400 (0.154 sec) INFO:tensorflow:global_step/sec: 643.959 INFO:tensorflow:loss = 582.77167, step = 500 (0.155 sec) INFO:tensorflow:global_step/sec: 645.776 INFO:tensorflow:loss = 649.7673, step = 600 (0.155 sec) INFO:tensorflow:global_step/sec: 572.456 INFO:tensorflow:loss = 396.41064, step = 700 (0.175 sec) INFO:tensorflow:global_step/sec: 566.38 INFO:tensorflow:loss = 669.36633, step = 800 (0.177 sec) INFO:tensorflow:global_step/sec: 566.658 INFO:tensorflow:loss = 632.7246, step = 900 (0.177 sec) INFO:tensorflow:global_step/sec: 617.634 INFO:tensorflow:loss = 758.34875, step = 1000 (0.162 sec) INFO:tensorflow:global_step/sec: 620.319 INFO:tensorflow:loss = 392.08755, step = 1100 (0.161 sec) INFO:tensorflow:global_step/sec: 564.039 INFO:tensorflow:loss = 476.3385, step = 1200 (0.177 sec) INFO:tensorflow:global_step/sec: 572.083 INFO:tensorflow:loss = 506.0124, step = 1300 (0.175 sec) INFO:tensorflow:global_step/sec: 567.277 INFO:tensorflow:loss = 577.36475, step = 1400 (0.176 sec) INFO:tensorflow:global_step/sec: 565.847 INFO:tensorflow:loss = 393.88156, step = 1500 (0.177 sec) INFO:tensorflow:global_step/sec: 566.604 INFO:tensorflow:loss = 635.9873, step = 1600 (0.177 sec) INFO:tensorflow:global_step/sec: 586.154 INFO:tensorflow:loss = 423.8427, step = 1700 (0.171 sec) INFO:tensorflow:global_step/sec: 647.064 INFO:tensorflow:loss = 498.0647, step = 1800 (0.155 sec) INFO:tensorflow:global_step/sec: 648.755 INFO:tensorflow:loss = 283.3813, step = 1900 (0.154 sec) INFO:tensorflow:global_step/sec: 666.887 INFO:tensorflow:loss = 405.86353, step = 2000 (0.150 sec) INFO:tensorflow:global_step/sec: 652.271 INFO:tensorflow:loss = 501.8705, step = 2100 (0.153 sec) INFO:tensorflow:global_step/sec: 644.585 INFO:tensorflow:loss = 304.44452, step = 2200 (0.155 sec) INFO:tensorflow:global_step/sec: 649.773 INFO:tensorflow:loss = 422.43158, step = 2300 (0.154 sec) INFO:tensorflow:global_step/sec: 653.582 INFO:tensorflow:loss = 365.81732, step = 2400 (0.153 sec) INFO:tensorflow:global_step/sec: 655.929 INFO:tensorflow:loss = 402.35364, step = 2500 (0.152 sec) INFO:tensorflow:global_step/sec: 657.293 INFO:tensorflow:loss = 479.02838, step = 2600 (0.152 sec) INFO:tensorflow:global_step/sec: 612.069 INFO:tensorflow:loss = 361.15582, step = 2700 (0.163 sec) INFO:tensorflow:global_step/sec: 645.744 INFO:tensorflow:loss = 379.43427, step = 2800 (0.155 sec) INFO:tensorflow:global_step/sec: 568.614 INFO:tensorflow:loss = 320.28763, step = 2900 (0.176 sec) INFO:tensorflow:global_step/sec: 638.986 INFO:tensorflow:loss = 385.37427, step = 3000 (0.156 sec) INFO:tensorflow:global_step/sec: 656.466 INFO:tensorflow:loss = 512.6961, step = 3100 (0.152 sec) INFO:tensorflow:global_step/sec: 568.927 INFO:tensorflow:loss = 316.60834, step = 3200 (0.176 sec) INFO:tensorflow:global_step/sec: 564.392 INFO:tensorflow:loss = 273.2796, step = 3300 (0.177 sec) INFO:tensorflow:global_step/sec: 646.287 INFO:tensorflow:loss = 502.52917, step = 3400 (0.155 sec) INFO:tensorflow:global_step/sec: 651.162 INFO:tensorflow:loss = 349.2741, step = 3500 (0.154 sec) INFO:tensorflow:global_step/sec: 649.318 INFO:tensorflow:loss = 139.09305, step = 3600 (0.154 sec) INFO:tensorflow:global_step/sec: 653.045 INFO:tensorflow:loss = 198.39453, step = 3700 (0.153 sec) INFO:tensorflow:global_step/sec: 648.472 INFO:tensorflow:loss = 331.9128, step = 3800 (0.154 sec) INFO:tensorflow:global_step/sec: 643.694 INFO:tensorflow:loss = 345.54785, step = 3900 (0.155 sec) INFO:tensorflow:global_step/sec: 639.938 INFO:tensorflow:loss = 434.36136, step = 4000 (0.156 sec) INFO:tensorflow:global_step/sec: 654.364 INFO:tensorflow:loss = 271.73187, step = 4100 (0.153 sec) INFO:tensorflow:global_step/sec: 659.689 INFO:tensorflow:loss = 509.27518, step = 4200 (0.152 sec) INFO:tensorflow:global_step/sec: 657.273 INFO:tensorflow:loss = 317.50986, step = 4300 (0.152 sec) INFO:tensorflow:global_step/sec: 553.198 INFO:tensorflow:loss = 186.29042, step = 4400 (0.181 sec) INFO:tensorflow:global_step/sec: 557.877 INFO:tensorflow:loss = 368.4395, step = 4500 (0.179 sec) INFO:tensorflow:global_step/sec: 556.365 INFO:tensorflow:loss = 193.78143, step = 4600 (0.180 sec) INFO:tensorflow:global_step/sec: 570.239 INFO:tensorflow:loss = 441.1708, step = 4700 (0.175 sec) INFO:tensorflow:global_step/sec: 567.788 INFO:tensorflow:loss = 240.40808, step = 4800 (0.176 sec) INFO:tensorflow:global_step/sec: 587.168 INFO:tensorflow:loss = 319.34958, step = 4900 (0.170 sec) INFO:tensorflow:global_step/sec: 613.08 INFO:tensorflow:loss = 270.3896, step = 5000 (0.163 sec) INFO:tensorflow:global_step/sec: 615.585 INFO:tensorflow:loss = 154.97989, step = 5100 (0.162 sec) INFO:tensorflow:global_step/sec: 618.903 INFO:tensorflow:loss = 253.60646, step = 5200 (0.162 sec) INFO:tensorflow:global_step/sec: 613.373 INFO:tensorflow:loss = 250.14478, step = 5300 (0.163 sec) INFO:tensorflow:global_step/sec: 618.895 INFO:tensorflow:loss = 314.1364, step = 5400 (0.162 sec) INFO:tensorflow:global_step/sec: 615.247 INFO:tensorflow:loss = 287.53287, step = 5500 (0.163 sec) INFO:tensorflow:global_step/sec: 579.559 INFO:tensorflow:loss = 292.2387, step = 5600 (0.173 sec) INFO:tensorflow:global_step/sec: 564.426 INFO:tensorflow:loss = 224.04553, step = 5700 (0.177 sec) INFO:tensorflow:global_step/sec: 568.456 INFO:tensorflow:loss = 353.1428, step = 5800 (0.176 sec) INFO:tensorflow:global_step/sec: 563.157 INFO:tensorflow:loss = 335.3949, step = 5900 (0.177 sec) INFO:tensorflow:global_step/sec: 569.556 INFO:tensorflow:loss = 187.25581, step = 6000 (0.176 sec) INFO:tensorflow:global_step/sec: 560.625 INFO:tensorflow:loss = 207.89288, step = 6100 (0.178 sec) INFO:tensorflow:global_step/sec: 564.964 INFO:tensorflow:loss = 352.81, step = 6200 (0.177 sec) INFO:tensorflow:global_step/sec: 601.182 INFO:tensorflow:loss = 200.35771, step = 6300 (0.166 sec) INFO:tensorflow:global_step/sec: 624.884 INFO:tensorflow:loss = 148.6445, step = 6400 (0.160 sec) INFO:tensorflow:global_step/sec: 617.641 INFO:tensorflow:loss = 98.60468, step = 6500 (0.162 sec) INFO:tensorflow:global_step/sec: 565.054 INFO:tensorflow:loss = 272.97253, step = 6600 (0.177 sec) INFO:tensorflow:global_step/sec: 557.052 INFO:tensorflow:loss = 189.83186, step = 6700 (0.180 sec) INFO:tensorflow:global_step/sec: 559.404 INFO:tensorflow:loss = 177.83542, step = 6800 (0.179 sec) INFO:tensorflow:global_step/sec: 616.915 INFO:tensorflow:loss = 154.5396, step = 6900 (0.162 sec) INFO:tensorflow:global_step/sec: 586.968 INFO:tensorflow:loss = 312.20593, step = 7000 (0.170 sec) INFO:tensorflow:global_step/sec: 584.733 INFO:tensorflow:loss = 146.29216, step = 7100 (0.171 sec) INFO:tensorflow:global_step/sec: 645.786 INFO:tensorflow:loss = 175.46495, step = 7200 (0.155 sec) INFO:tensorflow:global_step/sec: 652.056 INFO:tensorflow:loss = 225.34903, step = 7300 (0.153 sec) INFO:tensorflow:global_step/sec: 642.788 INFO:tensorflow:loss = 203.46408, step = 7400 (0.155 sec) INFO:tensorflow:global_step/sec: 657.435 INFO:tensorflow:loss = 115.84112, step = 7500 (0.152 sec) INFO:tensorflow:global_step/sec: 650.413 INFO:tensorflow:loss = 222.01236, step = 7600 (0.154 sec) INFO:tensorflow:global_step/sec: 566.584 INFO:tensorflow:loss = 195.82758, step = 7700 (0.176 sec) INFO:tensorflow:global_step/sec: 635.592 INFO:tensorflow:loss = 135.50404, step = 7800 (0.157 sec) INFO:tensorflow:global_step/sec: 581.135 INFO:tensorflow:loss = 128.616, step = 7900 (0.172 sec) INFO:tensorflow:global_step/sec: 565.747 INFO:tensorflow:loss = 142.26901, step = 8000 (0.177 sec) INFO:tensorflow:global_step/sec: 564.354 INFO:tensorflow:loss = 186.27264, step = 8100 (0.177 sec) INFO:tensorflow:global_step/sec: 579.482 INFO:tensorflow:loss = 285.70624, step = 8200 (0.172 sec) INFO:tensorflow:global_step/sec: 565.625 INFO:tensorflow:loss = 119.08911, step = 8300 (0.177 sec) INFO:tensorflow:global_step/sec: 556.787 INFO:tensorflow:loss = 122.49934, step = 8400 (0.180 sec) INFO:tensorflow:global_step/sec: 615.835 INFO:tensorflow:loss = 179.74419, step = 8500 (0.162 sec) INFO:tensorflow:global_step/sec: 618.261 INFO:tensorflow:loss = 101.167206, step = 8600 (0.162 sec) INFO:tensorflow:global_step/sec: 616.308 INFO:tensorflow:loss = 233.63202, step = 8700 (0.162 sec) INFO:tensorflow:global_step/sec: 624.669 INFO:tensorflow:loss = 69.64491, step = 8800 (0.160 sec) INFO:tensorflow:global_step/sec: 618.563 INFO:tensorflow:loss = 127.40744, step = 8900 (0.162 sec) INFO:tensorflow:global_step/sec: 620.277 INFO:tensorflow:loss = 145.69806, step = 9000 (0.161 sec) INFO:tensorflow:global_step/sec: 579.132 INFO:tensorflow:loss = 172.43636, step = 9100 (0.173 sec) INFO:tensorflow:global_step/sec: 575.305 INFO:tensorflow:loss = 207.42215, step = 9200 (0.174 sec) INFO:tensorflow:global_step/sec: 613.089 INFO:tensorflow:loss = 132.4537, step = 9300 (0.163 sec) INFO:tensorflow:global_step/sec: 619.394 INFO:tensorflow:loss = 70.08789, step = 9400 (0.161 sec) INFO:tensorflow:global_step/sec: 613.773 INFO:tensorflow:loss = 62.70175, step = 9500 (0.163 sec) INFO:tensorflow:global_step/sec: 612.9 INFO:tensorflow:loss = 132.35649, step = 9600 (0.163 sec) INFO:tensorflow:global_step/sec: 615.735 INFO:tensorflow:loss = 109.410255, step = 9700 (0.163 sec) INFO:tensorflow:global_step/sec: 612.842 INFO:tensorflow:loss = 166.54138, step = 9800 (0.163 sec) INFO:tensorflow:global_step/sec: 589.04 INFO:tensorflow:loss = 97.47385, step = 9900 (0.170 sec) INFO:tensorflow:global_step/sec: 559.295 INFO:tensorflow:loss = 103.19119, step = 10000 (0.179 sec) INFO:tensorflow:global_step/sec: 560.623 INFO:tensorflow:loss = 85.13874, step = 10100 (0.178 sec) INFO:tensorflow:global_step/sec: 569.201 INFO:tensorflow:loss = 106.877075, step = 10200 (0.176 sec) INFO:tensorflow:global_step/sec: 581.087 INFO:tensorflow:loss = 176.70938, step = 10300 (0.172 sec) INFO:tensorflow:global_step/sec: 590.159 INFO:tensorflow:loss = 87.25897, step = 10400 (0.169 sec) INFO:tensorflow:global_step/sec: 640.17 INFO:tensorflow:loss = 92.061295, step = 10500 (0.156 sec) INFO:tensorflow:global_step/sec: 635.601 INFO:tensorflow:loss = 122.7544, step = 10600 (0.157 sec) INFO:tensorflow:global_step/sec: 642.358 INFO:tensorflow:loss = 58.609745, step = 10700 (0.156 sec) INFO:tensorflow:global_step/sec: 593.496 INFO:tensorflow:loss = 130.04077, step = 10800 (0.168 sec) INFO:tensorflow:global_step/sec: 591.825 INFO:tensorflow:loss = 139.86115, step = 10900 (0.169 sec) INFO:tensorflow:global_step/sec: 576.898 INFO:tensorflow:loss = 128.72388, step = 11000 (0.173 sec) INFO:tensorflow:global_step/sec: 567.129 INFO:tensorflow:loss = 82.31069, step = 11100 (0.176 sec) INFO:tensorflow:global_step/sec: 555.931 INFO:tensorflow:loss = 77.19307, step = 11200 (0.180 sec) INFO:tensorflow:global_step/sec: 569.253 INFO:tensorflow:loss = 84.63773, step = 11300 (0.176 sec) INFO:tensorflow:global_step/sec: 572.477 INFO:tensorflow:loss = 91.148834, step = 11400 (0.175 sec) INFO:tensorflow:global_step/sec: 571.016 INFO:tensorflow:loss = 41.38865, step = 11500 (0.175 sec) INFO:tensorflow:global_step/sec: 573.122 INFO:tensorflow:loss = 99.62012, step = 11600 (0.174 sec) INFO:tensorflow:global_step/sec: 650.055 INFO:tensorflow:loss = 55.67815, step = 11700 (0.154 sec) INFO:tensorflow:global_step/sec: 654.057 INFO:tensorflow:loss = 59.75948, step = 11800 (0.153 sec) INFO:tensorflow:global_step/sec: 654.278 INFO:tensorflow:loss = 60.011417, step = 11900 (0.153 sec) INFO:tensorflow:global_step/sec: 646.568 INFO:tensorflow:loss = 115.91528, step = 12000 (0.155 sec) INFO:tensorflow:global_step/sec: 568.138 INFO:tensorflow:loss = 73.505295, step = 12100 (0.176 sec) INFO:tensorflow:global_step/sec: 557.474 INFO:tensorflow:loss = 88.06746, step = 12200 (0.179 sec) INFO:tensorflow:global_step/sec: 560.304 INFO:tensorflow:loss = 85.41072, step = 12300 (0.179 sec) INFO:tensorflow:global_step/sec: 587.284 INFO:tensorflow:loss = 56.19171, step = 12400 (0.170 sec) INFO:tensorflow:global_step/sec: 637.918 INFO:tensorflow:loss = 64.24606, step = 12500 (0.157 sec) INFO:tensorflow:global_step/sec: 601.848 INFO:tensorflow:loss = 52.26082, step = 12600 (0.166 sec) INFO:tensorflow:global_step/sec: 664.047 INFO:tensorflow:loss = 52.31598, step = 12700 (0.151 sec) INFO:tensorflow:global_step/sec: 647.043 INFO:tensorflow:loss = 99.53073, step = 12800 (0.155 sec) INFO:tensorflow:global_step/sec: 649.28 INFO:tensorflow:loss = 85.73153, step = 12900 (0.154 sec) INFO:tensorflow:global_step/sec: 660.834 INFO:tensorflow:loss = 59.555412, step = 13000 (0.151 sec) INFO:tensorflow:global_step/sec: 653.213 INFO:tensorflow:loss = 69.10744, step = 13100 (0.153 sec) INFO:tensorflow:global_step/sec: 661.769 INFO:tensorflow:loss = 66.7493, step = 13200 (0.151 sec) INFO:tensorflow:global_step/sec: 653.19 INFO:tensorflow:loss = 50.434845, step = 13300 (0.153 sec) INFO:tensorflow:global_step/sec: 662.245 INFO:tensorflow:loss = 119.52582, step = 13400 (0.151 sec) INFO:tensorflow:global_step/sec: 651.11 INFO:tensorflow:loss = 39.486324, step = 13500 (0.154 sec) INFO:tensorflow:global_step/sec: 572.621 INFO:tensorflow:loss = 36.93599, step = 13600 (0.175 sec) INFO:tensorflow:global_step/sec: 556.868 INFO:tensorflow:loss = 35.120228, step = 13700 (0.180 sec) INFO:tensorflow:global_step/sec: 566.421 INFO:tensorflow:loss = 28.110342, step = 13800 (0.177 sec) INFO:tensorflow:global_step/sec: 570.946 INFO:tensorflow:loss = 50.28643, step = 13900 (0.175 sec) INFO:tensorflow:global_step/sec: 648.298 INFO:tensorflow:loss = 34.63925, step = 14000 (0.154 sec) INFO:tensorflow:global_step/sec: 661.018 INFO:tensorflow:loss = 75.51688, step = 14100 (0.151 sec) INFO:tensorflow:global_step/sec: 652.163 INFO:tensorflow:loss = 58.08398, step = 14200 (0.153 sec) INFO:tensorflow:global_step/sec: 650.281 INFO:tensorflow:loss = 43.38926, step = 14300 (0.154 sec) INFO:tensorflow:global_step/sec: 659.09 INFO:tensorflow:loss = 31.798458, step = 14400 (0.152 sec) INFO:tensorflow:global_step/sec: 642.84 INFO:tensorflow:loss = 50.548183, step = 14500 (0.155 sec) INFO:tensorflow:global_step/sec: 632.044 INFO:tensorflow:loss = 52.485527, step = 14600 (0.158 sec) INFO:tensorflow:global_step/sec: 615.95 INFO:tensorflow:loss = 46.583717, step = 14700 (0.162 sec) INFO:tensorflow:global_step/sec: 584.977 INFO:tensorflow:loss = 57.482048, step = 14800 (0.171 sec) INFO:tensorflow:global_step/sec: 557.703 INFO:tensorflow:loss = 28.527182, step = 14900 (0.179 sec) INFO:tensorflow:global_step/sec: 559.545 INFO:tensorflow:loss = 24.597378, step = 15000 (0.179 sec) INFO:tensorflow:global_step/sec: 611.333 INFO:tensorflow:loss = 67.47382, step = 15100 (0.164 sec) INFO:tensorflow:global_step/sec: 650.873 INFO:tensorflow:loss = 9.842392, step = 15200 (0.154 sec) INFO:tensorflow:global_step/sec: 645.772 INFO:tensorflow:loss = 38.127098, step = 15300 (0.155 sec) INFO:tensorflow:global_step/sec: 650.294 INFO:tensorflow:loss = 32.482162, step = 15400 (0.154 sec) INFO:tensorflow:global_step/sec: 647.809 INFO:tensorflow:loss = 21.738888, step = 15500 (0.154 sec) INFO:tensorflow:global_step/sec: 645.159 INFO:tensorflow:loss = 47.9902, step = 15600 (0.155 sec) INFO:tensorflow:global_step/sec: 640.936 INFO:tensorflow:loss = 71.79877, step = 15700 (0.156 sec) INFO:tensorflow:global_step/sec: 645.737 INFO:tensorflow:loss = 53.093693, step = 15800 (0.155 sec) INFO:tensorflow:global_step/sec: 566.742 INFO:tensorflow:loss = 35.7934, step = 15900 (0.176 sec) INFO:tensorflow:global_step/sec: 626.839 INFO:tensorflow:loss = 48.071213, step = 16000 (0.159 sec) INFO:tensorflow:global_step/sec: 654.178 INFO:tensorflow:loss = 23.8972, step = 16100 (0.153 sec) INFO:tensorflow:global_step/sec: 562.791 INFO:tensorflow:loss = 47.391075, step = 16200 (0.178 sec) INFO:tensorflow:global_step/sec: 653.972 INFO:tensorflow:loss = 33.310158, step = 16300 (0.153 sec) INFO:tensorflow:global_step/sec: 656.621 INFO:tensorflow:loss = 36.17897, step = 16400 (0.152 sec) INFO:tensorflow:global_step/sec: 639.331 INFO:tensorflow:loss = 29.826387, step = 16500 (0.156 sec) INFO:tensorflow:global_step/sec: 644.783 INFO:tensorflow:loss = 39.875584, step = 16600 (0.155 sec) INFO:tensorflow:global_step/sec: 641.618 INFO:tensorflow:loss = 62.336967, step = 16700 (0.156 sec) INFO:tensorflow:global_step/sec: 633.634 INFO:tensorflow:loss = 25.50624, step = 16800 (0.158 sec) INFO:tensorflow:global_step/sec: 613.129 INFO:tensorflow:loss = 26.36065, step = 16900 (0.163 sec) INFO:tensorflow:global_step/sec: 617.887 INFO:tensorflow:loss = 22.199059, step = 17000 (0.162 sec) INFO:tensorflow:global_step/sec: 636.057 INFO:tensorflow:loss = 35.419243, step = 17100 (0.157 sec) INFO:tensorflow:global_step/sec: 567.684 INFO:tensorflow:loss = 16.926636, step = 17200 (0.176 sec) INFO:tensorflow:global_step/sec: 552.403 INFO:tensorflow:loss = 41.73528, step = 17300 (0.181 sec) INFO:tensorflow:global_step/sec: 554.903 INFO:tensorflow:loss = 60.46621, step = 17400 (0.180 sec) INFO:tensorflow:global_step/sec: 606.698 INFO:tensorflow:loss = 9.7304735, step = 17500 (0.165 sec) INFO:tensorflow:global_step/sec: 629.775 INFO:tensorflow:loss = 23.861652, step = 17600 (0.159 sec) INFO:tensorflow:global_step/sec: 580.814 INFO:tensorflow:loss = 44.88912, step = 17700 (0.172 sec) INFO:tensorflow:global_step/sec: 557.919 INFO:tensorflow:loss = 21.361008, step = 17800 (0.179 sec) INFO:tensorflow:global_step/sec: 553.493 INFO:tensorflow:loss = 33.784424, step = 17900 (0.181 sec) INFO:tensorflow:global_step/sec: 560.444 INFO:tensorflow:loss = 20.45843, step = 18000 (0.178 sec) INFO:tensorflow:global_step/sec: 565.069 INFO:tensorflow:loss = 31.591064, step = 18100 (0.177 sec) INFO:tensorflow:global_step/sec: 562.811 INFO:tensorflow:loss = 13.793056, step = 18200 (0.178 sec) INFO:tensorflow:global_step/sec: 556.338 INFO:tensorflow:loss = 45.03756, step = 18300 (0.180 sec) INFO:tensorflow:global_step/sec: 556.655 INFO:tensorflow:loss = 11.519857, step = 18400 (0.180 sec) INFO:tensorflow:global_step/sec: 643.54 INFO:tensorflow:loss = 34.568317, step = 18500 (0.155 sec) INFO:tensorflow:global_step/sec: 649.191 INFO:tensorflow:loss = 44.755013, step = 18600 (0.154 sec) INFO:tensorflow:global_step/sec: 576.328 INFO:tensorflow:loss = 14.43598, step = 18700 (0.174 sec) INFO:tensorflow:global_step/sec: 564.586 INFO:tensorflow:loss = 10.982545, step = 18800 (0.177 sec) INFO:tensorflow:global_step/sec: 644.083 INFO:tensorflow:loss = 30.731411, step = 18900 (0.155 sec) INFO:tensorflow:global_step/sec: 643.407 INFO:tensorflow:loss = 19.440567, step = 19000 (0.155 sec) INFO:tensorflow:global_step/sec: 607.951 INFO:tensorflow:loss = 63.62726, step = 19100 (0.164 sec) INFO:tensorflow:global_step/sec: 573.549 INFO:tensorflow:loss = 13.900019, step = 19200 (0.175 sec) INFO:tensorflow:global_step/sec: 580.514 INFO:tensorflow:loss = 47.006104, step = 19300 (0.172 sec) INFO:tensorflow:global_step/sec: 642.58 INFO:tensorflow:loss = 12.699298, step = 19400 (0.155 sec) INFO:tensorflow:global_step/sec: 641.932 INFO:tensorflow:loss = 20.420689, step = 19500 (0.156 sec) INFO:tensorflow:global_step/sec: 641.287 INFO:tensorflow:loss = 11.957592, step = 19600 (0.156 sec) INFO:tensorflow:global_step/sec: 635.855 INFO:tensorflow:loss = 20.387909, step = 19700 (0.157 sec) INFO:tensorflow:global_step/sec: 641.552 INFO:tensorflow:loss = 63.668373, step = 19800 (0.156 sec) INFO:tensorflow:global_step/sec: 564.799 INFO:tensorflow:loss = 29.952385, step = 19900 (0.177 sec) INFO:tensorflow:global_step/sec: 561.545 INFO:tensorflow:loss = 3.468977, step = 20000 (0.178 sec) INFO:tensorflow:global_step/sec: 564.833 INFO:tensorflow:loss = 14.017977, step = 20100 (0.177 sec) INFO:tensorflow:global_step/sec: 559.31 INFO:tensorflow:loss = 23.940512, step = 20200 (0.179 sec) INFO:tensorflow:global_step/sec: 561.595 INFO:tensorflow:loss = 15.872161, step = 20300 (0.178 sec) INFO:tensorflow:global_step/sec: 557.326 INFO:tensorflow:loss = 41.10446, step = 20400 (0.179 sec) INFO:tensorflow:global_step/sec: 597.31 INFO:tensorflow:loss = 40.06671, step = 20500 (0.167 sec) INFO:tensorflow:global_step/sec: 615.561 INFO:tensorflow:loss = 40.576504, step = 20600 (0.162 sec) INFO:tensorflow:global_step/sec: 599.323 INFO:tensorflow:loss = 9.951186, step = 20700 (0.167 sec) INFO:tensorflow:global_step/sec: 564.476 INFO:tensorflow:loss = 26.887535, step = 20800 (0.177 sec) INFO:tensorflow:global_step/sec: 558.206 INFO:tensorflow:loss = 22.223, step = 20900 (0.179 sec) INFO:tensorflow:global_step/sec: 558.813 INFO:tensorflow:loss = 26.191727, step = 21000 (0.179 sec) INFO:tensorflow:global_step/sec: 556.229 INFO:tensorflow:loss = 18.055063, step = 21100 (0.180 sec) INFO:tensorflow:global_step/sec: 554.705 INFO:tensorflow:loss = 17.920183, step = 21200 (0.180 sec) INFO:tensorflow:global_step/sec: 562.668 INFO:tensorflow:loss = 26.513557, step = 21300 (0.178 sec) INFO:tensorflow:global_step/sec: 640.564 INFO:tensorflow:loss = 21.903809, step = 21400 (0.156 sec) INFO:tensorflow:global_step/sec: 647.2 INFO:tensorflow:loss = 30.5953, step = 21500 (0.154 sec) INFO:tensorflow:global_step/sec: 638.928 INFO:tensorflow:loss = 27.62001, step = 21600 (0.157 sec) INFO:tensorflow:global_step/sec: 646.709 INFO:tensorflow:loss = 20.175642, step = 21700 (0.155 sec) INFO:tensorflow:global_step/sec: 648.56 INFO:tensorflow:loss = 4.968134, step = 21800 (0.154 sec) INFO:tensorflow:global_step/sec: 639.462 INFO:tensorflow:loss = 51.621918, step = 21900 (0.156 sec) INFO:tensorflow:global_step/sec: 640.555 INFO:tensorflow:loss = 32.733124, step = 22000 (0.156 sec) INFO:tensorflow:global_step/sec: 633.889 INFO:tensorflow:loss = 11.014718, step = 22100 (0.158 sec) INFO:tensorflow:global_step/sec: 630.786 INFO:tensorflow:loss = 14.58586, step = 22200 (0.159 sec) INFO:tensorflow:global_step/sec: 563.225 INFO:tensorflow:loss = 8.891371, step = 22300 (0.177 sec) INFO:tensorflow:global_step/sec: 560.618 INFO:tensorflow:loss = 38.58745, step = 22400 (0.178 sec) INFO:tensorflow:global_step/sec: 556.76 INFO:tensorflow:loss = 22.485962, step = 22500 (0.180 sec) INFO:tensorflow:global_step/sec: 563.099 INFO:tensorflow:loss = 15.741159, step = 22600 (0.178 sec) INFO:tensorflow:global_step/sec: 557.673 INFO:tensorflow:loss = 15.188747, step = 22700 (0.179 sec) INFO:tensorflow:global_step/sec: 589.91 INFO:tensorflow:loss = 22.645355, step = 22800 (0.169 sec) INFO:tensorflow:global_step/sec: 556.956 INFO:tensorflow:loss = 12.435162, step = 22900 (0.180 sec) INFO:tensorflow:global_step/sec: 558.367 INFO:tensorflow:loss = 28.399435, step = 23000 (0.179 sec) INFO:tensorflow:global_step/sec: 554.499 INFO:tensorflow:loss = 29.847202, step = 23100 (0.180 sec) INFO:tensorflow:global_step/sec: 557.706 INFO:tensorflow:loss = 24.096184, step = 23200 (0.179 sec) INFO:tensorflow:global_step/sec: 633.393 INFO:tensorflow:loss = 29.605507, step = 23300 (0.158 sec) INFO:tensorflow:global_step/sec: 638.07 INFO:tensorflow:loss = 6.675656, step = 23400 (0.157 sec) INFO:tensorflow:global_step/sec: 645.546 INFO:tensorflow:loss = 8.849547, step = 23500 (0.155 sec) INFO:tensorflow:global_step/sec: 641.03 INFO:tensorflow:loss = 22.545252, step = 23600 (0.156 sec) INFO:tensorflow:global_step/sec: 648.982 INFO:tensorflow:loss = 32.837273, step = 23700 (0.154 sec) INFO:tensorflow:global_step/sec: 652.554 INFO:tensorflow:loss = 23.164417, step = 23800 (0.153 sec) INFO:tensorflow:global_step/sec: 645.183 INFO:tensorflow:loss = 20.617609, step = 23900 (0.155 sec) INFO:tensorflow:global_step/sec: 650.653 INFO:tensorflow:loss = 14.767559, step = 24000 (0.154 sec) INFO:tensorflow:global_step/sec: 635.294 INFO:tensorflow:loss = 38.283543, step = 24100 (0.157 sec) INFO:tensorflow:global_step/sec: 644.853 INFO:tensorflow:loss = 44.3748, step = 24200 (0.155 sec) INFO:tensorflow:global_step/sec: 637.927 INFO:tensorflow:loss = 40.130806, step = 24300 (0.157 sec) INFO:tensorflow:global_step/sec: 636.607 INFO:tensorflow:loss = 13.896637, step = 24400 (0.157 sec) INFO:tensorflow:global_step/sec: 640.791 INFO:tensorflow:loss = 15.867412, step = 24500 (0.156 sec) INFO:tensorflow:global_step/sec: 643.12 INFO:tensorflow:loss = 27.252453, step = 24600 (0.155 sec) INFO:tensorflow:global_step/sec: 637.837 INFO:tensorflow:loss = 10.193189, step = 24700 (0.157 sec) INFO:tensorflow:global_step/sec: 558.504 INFO:tensorflow:loss = 7.39489, step = 24800 (0.179 sec) INFO:tensorflow:global_step/sec: 552.473 INFO:tensorflow:loss = 43.868538, step = 24900 (0.181 sec) INFO:tensorflow:global_step/sec: 557.42 INFO:tensorflow:loss = 39.280296, step = 25000 (0.179 sec) INFO:tensorflow:global_step/sec: 557.644 INFO:tensorflow:loss = 32.257843, step = 25100 (0.179 sec) INFO:tensorflow:global_step/sec: 552.62 INFO:tensorflow:loss = 15.869023, step = 25200 (0.181 sec) INFO:tensorflow:global_step/sec: 596.984 INFO:tensorflow:loss = 14.115913, step = 25300 (0.167 sec) INFO:tensorflow:global_step/sec: 562.627 INFO:tensorflow:loss = 10.347841, step = 25400 (0.178 sec) INFO:tensorflow:global_step/sec: 555.116 INFO:tensorflow:loss = 28.828302, step = 25500 (0.180 sec) INFO:tensorflow:global_step/sec: 562.795 INFO:tensorflow:loss = 21.246841, step = 25600 (0.178 sec) INFO:tensorflow:global_step/sec: 626.387 INFO:tensorflow:loss = 9.311673, step = 25700 (0.160 sec) INFO:tensorflow:global_step/sec: 645.753 INFO:tensorflow:loss = 24.5037, step = 25800 (0.155 sec) INFO:tensorflow:global_step/sec: 646.638 INFO:tensorflow:loss = 16.885513, step = 25900 (0.155 sec) INFO:tensorflow:global_step/sec: 647.599 INFO:tensorflow:loss = 17.163336, step = 26000 (0.154 sec) INFO:tensorflow:global_step/sec: 637.261 INFO:tensorflow:loss = 19.075056, step = 26100 (0.157 sec) INFO:tensorflow:global_step/sec: 630.96 INFO:tensorflow:loss = 15.663348, step = 26200 (0.159 sec) INFO:tensorflow:global_step/sec: 648.268 INFO:tensorflow:loss = 18.120064, step = 26300 (0.154 sec) INFO:tensorflow:global_step/sec: 647.007 INFO:tensorflow:loss = 41.735718, step = 26400 (0.155 sec) INFO:tensorflow:global_step/sec: 646.607 INFO:tensorflow:loss = 17.466406, step = 26500 (0.155 sec) INFO:tensorflow:global_step/sec: 645.538 INFO:tensorflow:loss = 27.561075, step = 26600 (0.155 sec) INFO:tensorflow:global_step/sec: 641.795 INFO:tensorflow:loss = 9.69916, step = 26700 (0.156 sec) INFO:tensorflow:global_step/sec: 631.119 INFO:tensorflow:loss = 83.92375, step = 26800 (0.158 sec) INFO:tensorflow:global_step/sec: 639.714 INFO:tensorflow:loss = 16.178406, step = 26900 (0.156 sec) INFO:tensorflow:global_step/sec: 637.172 INFO:tensorflow:loss = 14.685428, step = 27000 (0.157 sec) INFO:tensorflow:global_step/sec: 637.822 INFO:tensorflow:loss = 16.487114, step = 27100 (0.157 sec) INFO:tensorflow:global_step/sec: 626.523 INFO:tensorflow:loss = 6.233879, step = 27200 (0.160 sec) INFO:tensorflow:global_step/sec: 562.631 INFO:tensorflow:loss = 25.59382, step = 27300 (0.178 sec) INFO:tensorflow:global_step/sec: 588.092 INFO:tensorflow:loss = 7.877035, step = 27400 (0.170 sec) INFO:tensorflow:global_step/sec: 625.747 INFO:tensorflow:loss = 26.259216, step = 27500 (0.160 sec) INFO:tensorflow:global_step/sec: 607.397 INFO:tensorflow:loss = 18.831963, step = 27600 (0.165 sec) INFO:tensorflow:global_step/sec: 614.569 INFO:tensorflow:loss = 10.519957, step = 27700 (0.163 sec) INFO:tensorflow:global_step/sec: 610.519 INFO:tensorflow:loss = 29.63565, step = 27800 (0.164 sec) INFO:tensorflow:global_step/sec: 617.845 INFO:tensorflow:loss = 15.680868, step = 27900 (0.162 sec) INFO:tensorflow:global_step/sec: 610.635 INFO:tensorflow:loss = 31.339779, step = 28000 (0.164 sec) INFO:tensorflow:global_step/sec: 610.08 INFO:tensorflow:loss = 16.819326, step = 28100 (0.164 sec) INFO:tensorflow:global_step/sec: 616.965 INFO:tensorflow:loss = 1.2390225, step = 28200 (0.162 sec) INFO:tensorflow:global_step/sec: 614.248 INFO:tensorflow:loss = 18.569372, step = 28300 (0.163 sec) INFO:tensorflow:global_step/sec: 631.205 INFO:tensorflow:loss = 69.872086, step = 28400 (0.159 sec) INFO:tensorflow:global_step/sec: 647.207 INFO:tensorflow:loss = 7.713742, step = 28500 (0.154 sec) INFO:tensorflow:global_step/sec: 650.569 INFO:tensorflow:loss = 8.96863, step = 28600 (0.154 sec) INFO:tensorflow:global_step/sec: 635.145 INFO:tensorflow:loss = 8.195501, step = 28700 (0.157 sec) INFO:tensorflow:global_step/sec: 639.996 INFO:tensorflow:loss = 7.895544, step = 28800 (0.156 sec) INFO:tensorflow:global_step/sec: 634.209 INFO:tensorflow:loss = 9.781753, step = 28900 (0.158 sec) INFO:tensorflow:global_step/sec: 642.806 INFO:tensorflow:loss = 23.838917, step = 29000 (0.156 sec) INFO:tensorflow:global_step/sec: 639.762 INFO:tensorflow:loss = 13.926859, step = 29100 (0.156 sec) INFO:tensorflow:global_step/sec: 635.524 INFO:tensorflow:loss = 20.532545, step = 29200 (0.157 sec) INFO:tensorflow:global_step/sec: 641.009 INFO:tensorflow:loss = 15.29386, step = 29300 (0.156 sec) INFO:tensorflow:global_step/sec: 636.193 INFO:tensorflow:loss = 9.65447, step = 29400 (0.157 sec) INFO:tensorflow:global_step/sec: 636.497 INFO:tensorflow:loss = 17.778759, step = 29500 (0.157 sec) INFO:tensorflow:global_step/sec: 638.647 INFO:tensorflow:loss = 53.59935, step = 29600 (0.157 sec) INFO:tensorflow:global_step/sec: 641.218 INFO:tensorflow:loss = 1.7887146, step = 29700 (0.156 sec) INFO:tensorflow:global_step/sec: 632.812 INFO:tensorflow:loss = 9.185707, step = 29800 (0.158 sec) INFO:tensorflow:global_step/sec: 636.626 INFO:tensorflow:loss = 2.0348744, step = 29900 (0.157 sec) INFO:tensorflow:global_step/sec: 641.384 INFO:tensorflow:loss = 39.938457, step = 30000 (0.156 sec) INFO:tensorflow:global_step/sec: 636.928 INFO:tensorflow:loss = 35.079205, step = 30100 (0.157 sec) INFO:tensorflow:global_step/sec: 631.889 INFO:tensorflow:loss = 11.830448, step = 30200 (0.158 sec) INFO:tensorflow:global_step/sec: 629.569 INFO:tensorflow:loss = 7.7222857, step = 30300 (0.159 sec) INFO:tensorflow:global_step/sec: 629.26 INFO:tensorflow:loss = 5.0043783, step = 30400 (0.159 sec) INFO:tensorflow:global_step/sec: 633.129 INFO:tensorflow:loss = 28.834631, step = 30500 (0.158 sec) INFO:tensorflow:global_step/sec: 560.8 INFO:tensorflow:loss = 49.048584, step = 30600 (0.178 sec) INFO:tensorflow:global_step/sec: 630.476 INFO:tensorflow:loss = 12.857588, step = 30700 (0.159 sec) INFO:tensorflow:global_step/sec: 576.142 INFO:tensorflow:loss = 18.584694, step = 30800 (0.174 sec) INFO:tensorflow:global_step/sec: 554.342 INFO:tensorflow:loss = 30.525942, step = 30900 (0.180 sec) INFO:tensorflow:global_step/sec: 567.578 INFO:tensorflow:loss = 33.63379, step = 31000 (0.176 sec) INFO:tensorflow:global_step/sec: 560.022 INFO:tensorflow:loss = 14.771801, step = 31100 (0.178 sec) INFO:tensorflow:global_step/sec: 558.288 INFO:tensorflow:loss = 3.7000563, step = 31200 (0.179 sec) INFO:tensorflow:global_step/sec: 625.088 INFO:tensorflow:loss = 3.9122221, step = 31300 (0.160 sec) INFO:tensorflow:global_step/sec: 619.433 INFO:tensorflow:loss = 13.096632, step = 31400 (0.161 sec) INFO:tensorflow:global_step/sec: 630.211 INFO:tensorflow:loss = 35.163918, step = 31500 (0.159 sec) INFO:tensorflow:global_step/sec: 641.753 INFO:tensorflow:loss = 18.955883, step = 31600 (0.156 sec) INFO:tensorflow:global_step/sec: 642.018 INFO:tensorflow:loss = 24.371445, step = 31700 (0.156 sec) INFO:tensorflow:global_step/sec: 654.459 INFO:tensorflow:loss = 10.686918, step = 31800 (0.153 sec) INFO:tensorflow:global_step/sec: 648.877 INFO:tensorflow:loss = 10.00495, step = 31900 (0.154 sec) INFO:tensorflow:global_step/sec: 636.379 INFO:tensorflow:loss = 34.196156, step = 32000 (0.157 sec) INFO:tensorflow:global_step/sec: 639.306 INFO:tensorflow:loss = 17.267265, step = 32100 (0.156 sec) INFO:tensorflow:global_step/sec: 628.14 INFO:tensorflow:loss = 3.5982966, step = 32200 (0.159 sec) INFO:tensorflow:global_step/sec: 654.144 INFO:tensorflow:loss = 22.826725, step = 32300 (0.153 sec) INFO:tensorflow:global_step/sec: 656.323 INFO:tensorflow:loss = 18.253302, step = 32400 (0.152 sec) INFO:tensorflow:global_step/sec: 652.179 INFO:tensorflow:loss = 19.89624, step = 32500 (0.153 sec) INFO:tensorflow:global_step/sec: 648.347 INFO:tensorflow:loss = 26.507126, step = 32600 (0.154 sec) INFO:tensorflow:global_step/sec: 639.534 INFO:tensorflow:loss = 9.670689, step = 32700 (0.156 sec) INFO:tensorflow:global_step/sec: 628.019 INFO:tensorflow:loss = 19.151632, step = 32800 (0.159 sec) INFO:tensorflow:global_step/sec: 645.71 INFO:tensorflow:loss = 11.301746, step = 32900 (0.155 sec) INFO:tensorflow:global_step/sec: 632.64 INFO:tensorflow:loss = 39.349358, step = 33000 (0.158 sec) INFO:tensorflow:global_step/sec: 644.028 INFO:tensorflow:loss = 32.2932, step = 33100 (0.155 sec) INFO:tensorflow:global_step/sec: 627.79 INFO:tensorflow:loss = 14.889015, step = 33200 (0.159 sec) INFO:tensorflow:global_step/sec: 646.24 INFO:tensorflow:loss = 41.704803, step = 33300 (0.155 sec) INFO:tensorflow:global_step/sec: 635.648 INFO:tensorflow:loss = 15.027176, step = 33400 (0.157 sec) INFO:tensorflow:global_step/sec: 646.35 INFO:tensorflow:loss = 12.243839, step = 33500 (0.155 sec) INFO:tensorflow:global_step/sec: 651.522 INFO:tensorflow:loss = 5.87178, step = 33600 (0.153 sec) INFO:tensorflow:global_step/sec: 650.649 INFO:tensorflow:loss = 16.51314, step = 33700 (0.154 sec) INFO:tensorflow:global_step/sec: 648.37 INFO:tensorflow:loss = 15.912634, step = 33800 (0.154 sec) INFO:tensorflow:global_step/sec: 645.818 INFO:tensorflow:loss = 6.8702297, step = 33900 (0.155 sec) INFO:tensorflow:global_step/sec: 637.876 INFO:tensorflow:loss = 9.3833275, step = 34000 (0.157 sec) INFO:tensorflow:global_step/sec: 635.339 INFO:tensorflow:loss = 6.315841, step = 34100 (0.157 sec) INFO:tensorflow:global_step/sec: 648.389 INFO:tensorflow:loss = 23.294544, step = 34200 (0.154 sec) INFO:tensorflow:global_step/sec: 626.389 INFO:tensorflow:loss = 14.866375, step = 34300 (0.160 sec) INFO:tensorflow:global_step/sec: 636.443 INFO:tensorflow:loss = 23.482327, step = 34400 (0.157 sec) INFO:tensorflow:global_step/sec: 646.709 INFO:tensorflow:loss = 5.9481287, step = 34500 (0.155 sec) INFO:tensorflow:global_step/sec: 648.761 INFO:tensorflow:loss = 10.6761265, step = 34600 (0.154 sec) INFO:tensorflow:global_step/sec: 638.862 INFO:tensorflow:loss = 4.912558, step = 34700 (0.157 sec) INFO:tensorflow:global_step/sec: 642.065 INFO:tensorflow:loss = 25.11901, step = 34800 (0.156 sec) INFO:tensorflow:global_step/sec: 612.919 INFO:tensorflow:loss = 8.14024, step = 34900 (0.163 sec) INFO:tensorflow:global_step/sec: 556.115 INFO:tensorflow:loss = 17.55474, step = 35000 (0.180 sec) INFO:tensorflow:global_step/sec: 553.651 INFO:tensorflow:loss = 5.6831026, step = 35100 (0.181 sec) INFO:tensorflow:global_step/sec: 563.169 INFO:tensorflow:loss = 12.501162, step = 35200 (0.177 sec) INFO:tensorflow:global_step/sec: 643.02 INFO:tensorflow:loss = 25.764713, step = 35300 (0.156 sec) INFO:tensorflow:global_step/sec: 644.011 INFO:tensorflow:loss = 10.363308, step = 35400 (0.155 sec) INFO:tensorflow:global_step/sec: 638.251 INFO:tensorflow:loss = 23.721325, step = 35500 (0.156 sec) INFO:tensorflow:global_step/sec: 640.312 INFO:tensorflow:loss = 13.199163, step = 35600 (0.156 sec) INFO:tensorflow:global_step/sec: 651.36 INFO:tensorflow:loss = 31.616188, step = 35700 (0.154 sec) INFO:tensorflow:global_step/sec: 613.686 INFO:tensorflow:loss = 5.4822397, step = 35800 (0.163 sec) INFO:tensorflow:global_step/sec: 618.484 INFO:tensorflow:loss = 9.069538, step = 35900 (0.162 sec) INFO:tensorflow:global_step/sec: 617.06 INFO:tensorflow:loss = 8.100636, step = 36000 (0.162 sec) INFO:tensorflow:global_step/sec: 615.627 INFO:tensorflow:loss = 16.85956, step = 36100 (0.162 sec) INFO:tensorflow:global_step/sec: 612.812 INFO:tensorflow:loss = 18.85649, step = 36200 (0.163 sec) INFO:tensorflow:global_step/sec: 616.103 INFO:tensorflow:loss = 13.850594, step = 36300 (0.162 sec) INFO:tensorflow:global_step/sec: 625.165 INFO:tensorflow:loss = 51.77982, step = 36400 (0.160 sec) INFO:tensorflow:global_step/sec: 641.928 INFO:tensorflow:loss = 21.499207, step = 36500 (0.156 sec) INFO:tensorflow:global_step/sec: 641.116 INFO:tensorflow:loss = 9.992126, step = 36600 (0.156 sec) INFO:tensorflow:global_step/sec: 646.039 INFO:tensorflow:loss = 11.250916, step = 36700 (0.155 sec) INFO:tensorflow:global_step/sec: 647.816 INFO:tensorflow:loss = 9.30033, step = 36800 (0.154 sec) INFO:tensorflow:global_step/sec: 648.269 INFO:tensorflow:loss = 4.329362, step = 36900 (0.154 sec) INFO:tensorflow:global_step/sec: 640.78 INFO:tensorflow:loss = 10.897452, step = 37000 (0.156 sec) INFO:tensorflow:global_step/sec: 645.487 INFO:tensorflow:loss = 9.148363, step = 37100 (0.155 sec) INFO:tensorflow:global_step/sec: 651.223 INFO:tensorflow:loss = 30.404154, step = 37200 (0.154 sec) INFO:tensorflow:global_step/sec: 641.637 INFO:tensorflow:loss = 14.910101, step = 37300 (0.156 sec) INFO:tensorflow:global_step/sec: 650.827 INFO:tensorflow:loss = 15.732323, step = 37400 (0.154 sec) INFO:tensorflow:global_step/sec: 652.423 INFO:tensorflow:loss = 12.93858, step = 37500 (0.153 sec) INFO:tensorflow:global_step/sec: 644.518 INFO:tensorflow:loss = 31.476284, step = 37600 (0.155 sec) INFO:tensorflow:global_step/sec: 644.811 INFO:tensorflow:loss = 12.837719, step = 37700 (0.155 sec) INFO:tensorflow:global_step/sec: 635.591 INFO:tensorflow:loss = 6.9836364, step = 37800 (0.157 sec) INFO:tensorflow:global_step/sec: 640.438 INFO:tensorflow:loss = 3.7009566, step = 37900 (0.156 sec) INFO:tensorflow:global_step/sec: 652.57 INFO:tensorflow:loss = 15.457409, step = 38000 (0.153 sec) INFO:tensorflow:global_step/sec: 641.224 INFO:tensorflow:loss = 15.640904, step = 38100 (0.156 sec) INFO:tensorflow:global_step/sec: 652.626 INFO:tensorflow:loss = 3.6458635, step = 38200 (0.153 sec) INFO:tensorflow:global_step/sec: 654.56 INFO:tensorflow:loss = 7.718712, step = 38300 (0.153 sec) INFO:tensorflow:global_step/sec: 645.262 INFO:tensorflow:loss = 17.353992, step = 38400 (0.155 sec) INFO:tensorflow:global_step/sec: 644.266 INFO:tensorflow:loss = 10.383542, step = 38500 (0.155 sec) INFO:tensorflow:global_step/sec: 646.131 INFO:tensorflow:loss = 19.498116, step = 38600 (0.155 sec) INFO:tensorflow:global_step/sec: 650.171 INFO:tensorflow:loss = 50.384224, step = 38700 (0.154 sec) INFO:tensorflow:global_step/sec: 649.759 INFO:tensorflow:loss = 5.805867, step = 38800 (0.154 sec) INFO:tensorflow:global_step/sec: 634.323 INFO:tensorflow:loss = 7.7724056, step = 38900 (0.158 sec) INFO:tensorflow:global_step/sec: 633.254 INFO:tensorflow:loss = 7.2014084, step = 39000 (0.158 sec) INFO:tensorflow:global_step/sec: 648.197 INFO:tensorflow:loss = 17.135563, step = 39100 (0.154 sec) INFO:tensorflow:global_step/sec: 651.45 INFO:tensorflow:loss = 26.166622, step = 39200 (0.153 sec) INFO:tensorflow:global_step/sec: 644.187 INFO:tensorflow:loss = 16.454807, step = 39300 (0.155 sec) INFO:tensorflow:global_step/sec: 645.437 INFO:tensorflow:loss = 25.390144, step = 39400 (0.155 sec) INFO:tensorflow:global_step/sec: 637.175 INFO:tensorflow:loss = 17.874966, step = 39500 (0.157 sec) INFO:tensorflow:global_step/sec: 632.669 INFO:tensorflow:loss = 11.231724, step = 39600 (0.158 sec) INFO:tensorflow:global_step/sec: 617.176 INFO:tensorflow:loss = 16.137482, step = 39700 (0.162 sec) INFO:tensorflow:global_step/sec: 609.228 INFO:tensorflow:loss = 20.8172, step = 39800 (0.164 sec) INFO:tensorflow:global_step/sec: 587.507 INFO:tensorflow:loss = 24.547935, step = 39900 (0.170 sec) INFO:tensorflow:Saving checkpoints for 40000 into models/autompg-dnnregressor/model.ckpt. INFO:tensorflow:Loss for final step: 43.661736.
<tensorflow_estimator.python.estimator.canned.dnn.DNNRegressorV2 at 0x7f47cde76a10>
reloaded_regressor = tf.estimator.DNNRegressor(
feature_columns=all_feature_columns,
hidden_units=[32, 10],
warm_start_from='models/autompg-dnnregressor/',
model_dir='models/autompg-dnnregressor/')
INFO:tensorflow:Using default config. INFO:tensorflow:Using config: {'_model_dir': 'models/autompg-dnnregressor/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true graph_options { rewrite_options { meta_optimizer_iterations: ONE } } , '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f47c054ddd0>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}
def eval_input_fn(df_test, batch_size=8):
df = df_test.copy()
test_x, test_y = df, df.pop('MPG')
dataset = tf.data.Dataset.from_tensor_slices((dict(test_x), test_y))
return dataset.batch(batch_size)
eval_results = reloaded_regressor.evaluate(
input_fn=lambda:eval_input_fn(df_test_norm, batch_size=8))
for key in eval_results:
print('{:15s} {}'.format(key, eval_results[key]))
print('Average-Loss {:.4f}'.format(eval_results['average_loss']))
INFO:tensorflow:Calling model_fn. WARNING:tensorflow:Layer dnn is casting an input tensor from dtype float64 to the layer's dtype of float32, which is new behavior in TensorFlow 2. The layer has dtype float32 because it's dtype defaults to floatx. If you intended to run this layer in float32, you can safely ignore this warning. If in doubt, this warning is likely only an issue if you are porting a TensorFlow 1.X model to TensorFlow 2. To change all layers to have dtype float64 by default, call `tf.keras.backend.set_floatx('float64')`. To change just this layer, pass dtype='float64' to the layer constructor. If you are the author of this layer, you can disable autocasting by passing autocast=False to the base Layer constructor. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2019-11-03T11:17:46Z INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from models/autompg-dnnregressor/model.ckpt-40000 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Finished evaluation at 2019-11-03-11:17:47 INFO:tensorflow:Saving dict for global step 40000: average_loss = 19.54804, global_step = 40000, label/mean = 23.611393, loss = 19.48917, prediction/mean = 21.74643 INFO:tensorflow:Saving 'checkpoint_path' summary for global step 40000: models/autompg-dnnregressor/model.ckpt-40000 average_loss 19.54804039001465 label/mean 23.611392974853516 loss 19.48917007446289 prediction/mean 21.746429443359375 global_step 40000 Average-Loss 19.5480
pred_res = regressor.predict(input_fn=lambda: eval_input_fn(df_test_norm, batch_size=8))
print(next(iter(pred_res)))
INFO:tensorflow:Calling model_fn. WARNING:tensorflow:Layer dnn is casting an input tensor from dtype float64 to the layer's dtype of float32, which is new behavior in TensorFlow 2. The layer has dtype float32 because it's dtype defaults to floatx. If you intended to run this layer in float32, you can safely ignore this warning. If in doubt, this warning is likely only an issue if you are porting a TensorFlow 1.X model to TensorFlow 2. To change all layers to have dtype float64 by default, call `tf.keras.backend.set_floatx('float64')`. To change just this layer, pass dtype='float64' to the layer constructor. If you are the author of this layer, you can disable autocasting by passing autocast=False to the base Layer constructor. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from models/autompg-dnnregressor/model.ckpt-40000 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. {'predictions': array([23.719353], dtype=float32)}
boosted_tree = tf.estimator.BoostedTreesRegressor(
feature_columns=all_feature_columns,
n_batches_per_layer=20,
n_trees=200)
boosted_tree.train(
input_fn=lambda:train_input_fn(df_train_norm, batch_size=BATCH_SIZE))
eval_results = boosted_tree.evaluate(
input_fn=lambda:eval_input_fn(df_test_norm, batch_size=8))
print(eval_results)
print('Average-Loss {:.4f}'.format(eval_results['average_loss']))
INFO:tensorflow:Using default config. WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpbzo1p2wi INFO:tensorflow:Using config: {'_model_dir': '/tmp/tmpbzo1p2wi', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true graph_options { rewrite_options { meta_optimizer_iterations: ONE } } , '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f47bc30b7d0>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1} INFO:tensorflow:Calling model_fn. WARNING:tensorflow:From /home/vahid/anaconda3/envs/tf2/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/canned/boosted_trees.py:214: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Create CheckpointSaverHook. WARNING:tensorflow:Issue encountered when serializing resources. Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore. '_Resource' object has no attribute 'name' INFO:tensorflow:Graph was finalized. INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. WARNING:tensorflow:Issue encountered when serializing resources. Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore. '_Resource' object has no attribute 'name' INFO:tensorflow:Saving checkpoints for 0 into /tmp/tmpbzo1p2wi/model.ckpt. WARNING:tensorflow:Issue encountered when serializing resources. Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore. '_Resource' object has no attribute 'name' INFO:tensorflow:loss = 402.19623, step = 0 WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize. WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize. WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize. WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize. WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize. INFO:tensorflow:loss = 289.26328, step = 80 (0.462 sec) INFO:tensorflow:global_step/sec: 157.704 INFO:tensorflow:loss = 93.58242, step = 180 (0.363 sec) INFO:tensorflow:global_step/sec: 422.808 INFO:tensorflow:loss = 45.606873, step = 280 (0.243 sec) INFO:tensorflow:global_step/sec: 416.715 INFO:tensorflow:loss = 19.545433, step = 380 (0.240 sec) INFO:tensorflow:global_step/sec: 416.626 INFO:tensorflow:loss = 6.4179554, step = 480 (0.245 sec) INFO:tensorflow:global_step/sec: 407.822 INFO:tensorflow:loss = 4.7701707, step = 580 (0.231 sec) INFO:tensorflow:global_step/sec: 408.05 INFO:tensorflow:loss = 4.569898, step = 680 (0.244 sec) INFO:tensorflow:global_step/sec: 420.57 INFO:tensorflow:loss = 2.5075686, step = 780 (0.249 sec) INFO:tensorflow:global_step/sec: 410.68 INFO:tensorflow:loss = 2.6939745, step = 880 (0.244 sec) INFO:tensorflow:global_step/sec: 411.964 INFO:tensorflow:loss = 1.5966964, step = 980 (0.248 sec) INFO:tensorflow:global_step/sec: 403.965 INFO:tensorflow:loss = 3.3678646, step = 1080 (0.250 sec) INFO:tensorflow:global_step/sec: 398.728 INFO:tensorflow:loss = 2.3181179, step = 1180 (0.238 sec) INFO:tensorflow:global_step/sec: 396.897 INFO:tensorflow:loss = 1.8086417, step = 1280 (0.250 sec) INFO:tensorflow:global_step/sec: 414.237 INFO:tensorflow:loss = 0.6904925, step = 1380 (0.246 sec) INFO:tensorflow:global_step/sec: 411.693 INFO:tensorflow:loss = 1.8734654, step = 1480 (0.250 sec) INFO:tensorflow:global_step/sec: 401.569 INFO:tensorflow:loss = 2.5979433, step = 1580 (0.254 sec) INFO:tensorflow:global_step/sec: 395.667 INFO:tensorflow:loss = 2.0128171, step = 1680 (0.256 sec) INFO:tensorflow:global_step/sec: 392.234 INFO:tensorflow:loss = 2.469627, step = 1780 (0.244 sec) INFO:tensorflow:global_step/sec: 386.751 INFO:tensorflow:loss = 0.87159, step = 1880 (0.253 sec) INFO:tensorflow:global_step/sec: 404.765 INFO:tensorflow:loss = 0.80283445, step = 1980 (0.254 sec) INFO:tensorflow:global_step/sec: 401.5 INFO:tensorflow:loss = 1.524719, step = 2080 (0.261 sec) INFO:tensorflow:global_step/sec: 385.878 INFO:tensorflow:loss = 1.0228136, step = 2180 (0.261 sec) INFO:tensorflow:global_step/sec: 382.386 INFO:tensorflow:loss = 1.0036705, step = 2280 (0.263 sec) INFO:tensorflow:global_step/sec: 382.23 INFO:tensorflow:loss = 1.0771171, step = 2380 (0.245 sec) INFO:tensorflow:global_step/sec: 388.433 INFO:tensorflow:loss = 0.9643565, step = 2480 (0.251 sec) INFO:tensorflow:global_step/sec: 409.442 INFO:tensorflow:loss = 1.4598124, step = 2580 (0.264 sec) INFO:tensorflow:global_step/sec: 382.398 INFO:tensorflow:loss = 0.7518444, step = 2680 (0.260 sec) INFO:tensorflow:global_step/sec: 387.657 INFO:tensorflow:loss = 0.71297884, step = 2780 (0.260 sec) INFO:tensorflow:global_step/sec: 387.516 INFO:tensorflow:loss = 0.21006158, step = 2880 (0.261 sec) INFO:tensorflow:global_step/sec: 380.228 INFO:tensorflow:loss = 0.64975756, step = 2980 (0.252 sec) INFO:tensorflow:global_step/sec: 375.953 INFO:tensorflow:loss = 0.3568688, step = 3080 (0.262 sec) INFO:tensorflow:global_step/sec: 394.311 INFO:tensorflow:loss = 1.0947809, step = 3180 (0.260 sec) INFO:tensorflow:global_step/sec: 389.576 INFO:tensorflow:loss = 0.38473517, step = 3280 (0.262 sec) INFO:tensorflow:global_step/sec: 383.038 INFO:tensorflow:loss = 0.37087482, step = 3380 (0.266 sec) INFO:tensorflow:global_step/sec: 377.258 INFO:tensorflow:loss = 0.37313935, step = 3480 (0.268 sec) INFO:tensorflow:global_step/sec: 375.779 INFO:tensorflow:loss = 0.6371509, step = 3580 (0.253 sec) INFO:tensorflow:global_step/sec: 376.039 INFO:tensorflow:loss = 0.6737277, step = 3680 (0.258 sec) INFO:tensorflow:global_step/sec: 397.449 INFO:tensorflow:loss = 0.22763562, step = 3780 (0.264 sec) INFO:tensorflow:global_step/sec: 379.907 INFO:tensorflow:loss = 0.70576984, step = 3880 (0.270 sec) INFO:tensorflow:global_step/sec: 375.692 INFO:tensorflow:loss = 0.32033288, step = 3980 (0.266 sec) INFO:tensorflow:global_step/sec: 376.935 INFO:tensorflow:loss = 0.5732076, step = 4080 (0.271 sec) INFO:tensorflow:global_step/sec: 369.125 INFO:tensorflow:loss = 0.22866802, step = 4180 (0.257 sec) INFO:tensorflow:global_step/sec: 370.509 INFO:tensorflow:loss = 0.27701426, step = 4280 (0.262 sec) INFO:tensorflow:global_step/sec: 388.812 INFO:tensorflow:loss = 0.2290253, step = 4380 (0.273 sec) INFO:tensorflow:global_step/sec: 373.834 INFO:tensorflow:loss = 0.24748756, step = 4480 (0.270 sec) INFO:tensorflow:global_step/sec: 373.023 INFO:tensorflow:loss = 0.2879139, step = 4580 (0.275 sec) INFO:tensorflow:global_step/sec: 364.77 INFO:tensorflow:loss = 0.28078204, step = 4680 (0.272 sec) INFO:tensorflow:global_step/sec: 368.265 INFO:tensorflow:loss = 0.1984863, step = 4780 (0.261 sec) INFO:tensorflow:global_step/sec: 363.698 INFO:tensorflow:loss = 0.31559613, step = 4880 (0.271 sec) INFO:tensorflow:global_step/sec: 377.83 INFO:tensorflow:loss = 0.2904449, step = 4980 (0.277 sec) INFO:tensorflow:global_step/sec: 363.8 INFO:tensorflow:loss = 0.28680754, step = 5080 (0.275 sec) INFO:tensorflow:global_step/sec: 367.857 INFO:tensorflow:loss = 0.374867, step = 5180 (0.274 sec) INFO:tensorflow:global_step/sec: 366.626 INFO:tensorflow:loss = 0.3683201, step = 5280 (0.280 sec) INFO:tensorflow:global_step/sec: 357.256 INFO:tensorflow:loss = 0.2899915, step = 5380 (0.265 sec) INFO:tensorflow:global_step/sec: 359.244 INFO:tensorflow:loss = 0.1280297, step = 5480 (0.268 sec) INFO:tensorflow:global_step/sec: 381.8 INFO:tensorflow:loss = 0.7579371, step = 5580 (0.274 sec) INFO:tensorflow:global_step/sec: 366.796 INFO:tensorflow:loss = 0.20086025, step = 5680 (0.278 sec) INFO:tensorflow:global_step/sec: 363.209 INFO:tensorflow:loss = 0.20468965, step = 5780 (0.282 sec) INFO:tensorflow:global_step/sec: 355.186 INFO:tensorflow:loss = 0.084839374, step = 5880 (0.284 sec) INFO:tensorflow:global_step/sec: 353.547 INFO:tensorflow:loss = 0.7841339, step = 5980 (0.268 sec) INFO:tensorflow:global_step/sec: 355.69 INFO:tensorflow:loss = 0.4825125, step = 6080 (0.270 sec) INFO:tensorflow:global_step/sec: 378.825 INFO:tensorflow:loss = 0.15031722, step = 6180 (0.278 sec) INFO:tensorflow:global_step/sec: 363.354 INFO:tensorflow:loss = 0.09604564, step = 6280 (0.281 sec) INFO:tensorflow:global_step/sec: 359.431 INFO:tensorflow:loss = 0.22453651, step = 6380 (0.281 sec) INFO:tensorflow:global_step/sec: 355.953 INFO:tensorflow:loss = 0.066752866, step = 6480 (0.287 sec) INFO:tensorflow:global_step/sec: 348.331 INFO:tensorflow:loss = 0.13314456, step = 6580 (0.275 sec) INFO:tensorflow:global_step/sec: 346.788 INFO:tensorflow:loss = 0.11664696, step = 6680 (0.281 sec) INFO:tensorflow:global_step/sec: 365.916 INFO:tensorflow:loss = 0.24780986, step = 6780 (0.280 sec) INFO:tensorflow:global_step/sec: 360.304 INFO:tensorflow:loss = 0.16076241, step = 6880 (0.289 sec) INFO:tensorflow:global_step/sec: 347.319 INFO:tensorflow:loss = 0.15068403, step = 6980 (0.290 sec) INFO:tensorflow:global_step/sec: 347.161 INFO:tensorflow:loss = 0.063347995, step = 7080 (0.288 sec) INFO:tensorflow:global_step/sec: 346.469 INFO:tensorflow:loss = 0.17705172, step = 7180 (0.279 sec) INFO:tensorflow:global_step/sec: 342.538 INFO:tensorflow:loss = 0.1235522, step = 7280 (0.283 sec) INFO:tensorflow:global_step/sec: 362.863 INFO:tensorflow:loss = 0.19375022, step = 7380 (0.283 sec) INFO:tensorflow:global_step/sec: 356.934 INFO:tensorflow:loss = 0.09878422, step = 7480 (0.285 sec) INFO:tensorflow:global_step/sec: 350.67 INFO:tensorflow:loss = 0.044014893, step = 7580 (0.288 sec) INFO:tensorflow:global_step/sec: 348.951 INFO:tensorflow:loss = 0.090123355, step = 7680 (0.292 sec) INFO:tensorflow:global_step/sec: 343.379 INFO:tensorflow:loss = 0.1411789, step = 7780 (0.277 sec) INFO:tensorflow:global_step/sec: 343.451 INFO:tensorflow:loss = 0.0606481, step = 7880 (0.286 sec) INFO:tensorflow:global_step/sec: 358.731 INFO:tensorflow:loss = 0.11701955, step = 7980 (0.293 sec) INFO:tensorflow:global_step/sec: 342.975 INFO:tensorflow:loss = 0.2144481, step = 8080 (0.299 sec) INFO:tensorflow:global_step/sec: 337.35 INFO:tensorflow:loss = 0.13061918, step = 8180 (0.301 sec) INFO:tensorflow:global_step/sec: 331.849 INFO:tensorflow:loss = 0.013081398, step = 8280 (0.298 sec) INFO:tensorflow:global_step/sec: 336.503 INFO:tensorflow:loss = 0.027076408, step = 8380 (0.286 sec) INFO:tensorflow:global_step/sec: 332.512 INFO:tensorflow:loss = 0.010121934, step = 8480 (0.293 sec) INFO:tensorflow:global_step/sec: 352.257 INFO:tensorflow:loss = 0.023727953, step = 8580 (0.294 sec) INFO:tensorflow:global_step/sec: 343.327 INFO:tensorflow:loss = 0.13345344, step = 8680 (0.296 sec) INFO:tensorflow:global_step/sec: 339.463 INFO:tensorflow:loss = 0.06767905, step = 8780 (0.298 sec) INFO:tensorflow:global_step/sec: 336.43 INFO:tensorflow:loss = 0.03239054, step = 8880 (0.299 sec) INFO:tensorflow:global_step/sec: 337.212 INFO:tensorflow:loss = 0.03417517, step = 8980 (0.288 sec) INFO:tensorflow:global_step/sec: 329.745 INFO:tensorflow:loss = 0.04349177, step = 9080 (0.295 sec) INFO:tensorflow:global_step/sec: 346.215 INFO:tensorflow:loss = 0.10747677, step = 9180 (0.297 sec) INFO:tensorflow:global_step/sec: 341.222 INFO:tensorflow:loss = 0.08463769, step = 9280 (0.302 sec) INFO:tensorflow:global_step/sec: 333.558 INFO:tensorflow:loss = 0.022979608, step = 9380 (0.303 sec) INFO:tensorflow:global_step/sec: 329.165 INFO:tensorflow:loss = 0.07760788, step = 9480 (0.310 sec) INFO:tensorflow:global_step/sec: 322.089 INFO:tensorflow:loss = 0.038779423, step = 9580 (0.292 sec) INFO:tensorflow:global_step/sec: 329.556 INFO:tensorflow:loss = 0.014404967, step = 9680 (0.297 sec) INFO:tensorflow:global_step/sec: 343.326 INFO:tensorflow:loss = 0.06990504, step = 9780 (0.305 sec) INFO:tensorflow:global_step/sec: 333.686 INFO:tensorflow:loss = 0.036858298, step = 9880 (0.305 sec) INFO:tensorflow:global_step/sec: 326.461 INFO:tensorflow:loss = 0.047570646, step = 9980 (0.312 sec) INFO:tensorflow:global_step/sec: 321.895 INFO:tensorflow:loss = 0.059428196, step = 10080 (0.309 sec) INFO:tensorflow:global_step/sec: 325.738 INFO:tensorflow:loss = 0.05054853, step = 10180 (0.293 sec) INFO:tensorflow:global_step/sec: 327.29 INFO:tensorflow:loss = 0.04085783, step = 10280 (0.300 sec) INFO:tensorflow:global_step/sec: 337.825 INFO:tensorflow:loss = 0.06833278, step = 10380 (0.309 sec) INFO:tensorflow:global_step/sec: 328.799 INFO:tensorflow:loss = 0.03984513, step = 10480 (0.309 sec) INFO:tensorflow:global_step/sec: 325.714 INFO:tensorflow:loss = 0.029430978, step = 10580 (0.313 sec) INFO:tensorflow:global_step/sec: 320.448 INFO:tensorflow:loss = 0.015103683, step = 10680 (0.310 sec) INFO:tensorflow:global_step/sec: 321.814 INFO:tensorflow:loss = 0.055365227, step = 10780 (0.303 sec) INFO:tensorflow:global_step/sec: 315.217 INFO:tensorflow:loss = 0.016110064, step = 10880 (0.316 sec) INFO:tensorflow:global_step/sec: 323.304 INFO:tensorflow:loss = 0.006240257, step = 10980 (0.315 sec) INFO:tensorflow:global_step/sec: 321.096 INFO:tensorflow:loss = 0.007149349, step = 11080 (0.321 sec) INFO:tensorflow:global_step/sec: 314.465 INFO:tensorflow:loss = 0.0066786045, step = 11180 (0.312 sec) INFO:tensorflow:global_step/sec: 320.341 INFO:tensorflow:loss = 0.025937172, step = 11280 (0.312 sec) INFO:tensorflow:global_step/sec: 321.417 INFO:tensorflow:loss = 0.016570274, step = 11380 (0.303 sec) INFO:tensorflow:global_step/sec: 317.392 INFO:tensorflow:loss = 0.0033354259, step = 11480 (0.308 sec) INFO:tensorflow:global_step/sec: 330.218 INFO:tensorflow:loss = 0.017488046, step = 11580 (0.314 sec) INFO:tensorflow:global_step/sec: 320.864 INFO:tensorflow:loss = 0.02159322, step = 11680 (0.322 sec) INFO:tensorflow:global_step/sec: 310.693 INFO:tensorflow:loss = 0.020893702, step = 11780 (0.323 sec) INFO:tensorflow:global_step/sec: 310.939 INFO:tensorflow:loss = 0.017859623, step = 11880 (0.326 sec) INFO:tensorflow:global_step/sec: 304.814 INFO:tensorflow:loss = 0.014102906, step = 11980 (0.310 sec) INFO:tensorflow:global_step/sec: 311.383 INFO:tensorflow:loss = 0.014420295, step = 12080 (0.316 sec) INFO:tensorflow:global_step/sec: 323.922 INFO:tensorflow:loss = 0.012980898, step = 12180 (0.323 sec) INFO:tensorflow:global_step/sec: 312.002 INFO:tensorflow:loss = 0.008047884, step = 12280 (0.324 sec) INFO:tensorflow:global_step/sec: 309.195 INFO:tensorflow:loss = 0.005332183, step = 12380 (0.328 sec) INFO:tensorflow:global_step/sec: 307.363 INFO:tensorflow:loss = 0.009909308, step = 12480 (0.331 sec) INFO:tensorflow:global_step/sec: 303.166 INFO:tensorflow:loss = 0.018593434, step = 12580 (0.310 sec) INFO:tensorflow:global_step/sec: 307.677 INFO:tensorflow:loss = 0.009453268, step = 12680 (0.318 sec) INFO:tensorflow:global_step/sec: 323.497 INFO:tensorflow:loss = 0.0074377223, step = 12780 (0.317 sec) INFO:tensorflow:global_step/sec: 318.278 INFO:tensorflow:loss = 0.0067944657, step = 12880 (0.326 sec) INFO:tensorflow:global_step/sec: 307.95 INFO:tensorflow:loss = 0.009621896, step = 12980 (0.332 sec) INFO:tensorflow:global_step/sec: 303.108 INFO:tensorflow:loss = 0.007392729, step = 13080 (0.329 sec) INFO:tensorflow:global_step/sec: 303.111 INFO:tensorflow:loss = 0.0070271464, step = 13180 (0.317 sec) INFO:tensorflow:global_step/sec: 302.852 INFO:tensorflow:loss = 0.01419846, step = 13280 (0.325 sec) INFO:tensorflow:global_step/sec: 311.988 INFO:tensorflow:loss = 0.00879844, step = 13380 (0.330 sec) INFO:tensorflow:global_step/sec: 307.168 INFO:tensorflow:loss = 0.0035331238, step = 13480 (0.333 sec) INFO:tensorflow:global_step/sec: 301.33 INFO:tensorflow:loss = 0.004036055, step = 13580 (0.334 sec) INFO:tensorflow:global_step/sec: 300.952 INFO:tensorflow:loss = 0.0021674812, step = 13680 (0.335 sec) INFO:tensorflow:global_step/sec: 298.644 INFO:tensorflow:loss = 0.0044945157, step = 13780 (0.318 sec) INFO:tensorflow:global_step/sec: 302.261 INFO:tensorflow:loss = 0.008261169, step = 13880 (0.328 sec) INFO:tensorflow:global_step/sec: 310.556 INFO:tensorflow:loss = 0.007413184, step = 13980 (0.337 sec) INFO:tensorflow:global_step/sec: 300.33 INFO:tensorflow:loss = 0.01038721, step = 14080 (0.331 sec) INFO:tensorflow:global_step/sec: 304.304 INFO:tensorflow:loss = 0.0020925598, step = 14180 (0.329 sec) INFO:tensorflow:global_step/sec: 303.857 INFO:tensorflow:loss = 0.0072769765, step = 14280 (0.337 sec) INFO:tensorflow:global_step/sec: 297.895 INFO:tensorflow:loss = 0.0018916101, step = 14380 (0.326 sec) INFO:tensorflow:global_step/sec: 294.092 INFO:tensorflow:loss = 0.0027799625, step = 14480 (0.327 sec) INFO:tensorflow:global_step/sec: 312.093 INFO:tensorflow:loss = 0.0037557913, step = 14580 (0.334 sec) INFO:tensorflow:global_step/sec: 301.829 INFO:tensorflow:loss = 0.0015468008, step = 14680 (0.334 sec) INFO:tensorflow:global_step/sec: 302.182 INFO:tensorflow:loss = 0.0018402252, step = 14780 (0.332 sec) INFO:tensorflow:global_step/sec: 301.447 INFO:tensorflow:loss = 0.0063510793, step = 14880 (0.339 sec) INFO:tensorflow:global_step/sec: 294.111 INFO:tensorflow:loss = 0.003960237, step = 14980 (0.327 sec) INFO:tensorflow:global_step/sec: 295.082 INFO:tensorflow:loss = 0.0021010689, step = 15080 (0.333 sec) INFO:tensorflow:global_step/sec: 306.512 INFO:tensorflow:loss = 0.0011556938, step = 15180 (0.338 sec) INFO:tensorflow:global_step/sec: 298.883 INFO:tensorflow:loss = 0.0009854774, step = 15280 (0.337 sec) INFO:tensorflow:global_step/sec: 299.258 INFO:tensorflow:loss = 0.0059409747, step = 15380 (0.333 sec) INFO:tensorflow:global_step/sec: 299.457 INFO:tensorflow:loss = 0.0022082897, step = 15480 (0.338 sec) INFO:tensorflow:global_step/sec: 298.035 INFO:tensorflow:loss = 0.0036195924, step = 15580 (0.323 sec) INFO:tensorflow:global_step/sec: 297.116 INFO:tensorflow:loss = 0.005268056, step = 15680 (0.332 sec) INFO:tensorflow:global_step/sec: 304.785 INFO:tensorflow:loss = 0.0021239321, step = 15780 (0.342 sec) INFO:tensorflow:global_step/sec: 298.12 INFO:tensorflow:loss = 0.0127066765, step = 15880 (0.339 sec) INFO:tensorflow:global_step/sec: 295.993 INFO:tensorflow:loss = 0.0021492667, step = 15980 (0.341 sec) INFO:tensorflow:global_step/sec: 293.45 INFO:tensorflow:loss = 0.003911408, step = 16080 (0.343 sec) INFO:tensorflow:global_step/sec: 291.821 INFO:tensorflow:loss = 0.004051245, step = 16180 (0.334 sec) INFO:tensorflow:global_step/sec: 287.44 INFO:tensorflow:loss = 0.0049018306, step = 16280 (0.342 sec) INFO:tensorflow:global_step/sec: 297.459 INFO:tensorflow:loss = 0.0026472202, step = 16380 (0.345 sec) INFO:tensorflow:global_step/sec: 293.164 INFO:tensorflow:loss = 0.0038542324, step = 16480 (0.348 sec) INFO:tensorflow:global_step/sec: 288.779 INFO:tensorflow:loss = 0.003773787, step = 16580 (0.346 sec) INFO:tensorflow:global_step/sec: 289.185 INFO:tensorflow:loss = 0.0026647656, step = 16680 (0.343 sec) INFO:tensorflow:global_step/sec: 291.876 INFO:tensorflow:loss = 0.0024704284, step = 16780 (0.334 sec) INFO:tensorflow:global_step/sec: 288.324 INFO:tensorflow:loss = 0.0034512142, step = 16880 (0.347 sec) INFO:tensorflow:global_step/sec: 292.507 INFO:tensorflow:loss = 0.0062024607, step = 16980 (0.346 sec) INFO:tensorflow:global_step/sec: 291.147 INFO:tensorflow:loss = 0.0022722099, step = 17080 (0.351 sec) INFO:tensorflow:global_step/sec: 287.208 INFO:tensorflow:loss = 0.0014444834, step = 17180 (0.352 sec) INFO:tensorflow:global_step/sec: 283.574 INFO:tensorflow:loss = 0.0074605285, step = 17280 (0.357 sec) INFO:tensorflow:global_step/sec: 281.604 INFO:tensorflow:loss = 0.003752734, step = 17380 (0.339 sec) INFO:tensorflow:global_step/sec: 283.366 INFO:tensorflow:loss = 0.0012563546, step = 17480 (0.342 sec) INFO:tensorflow:global_step/sec: 297.925 INFO:tensorflow:loss = 0.003298856, step = 17580 (0.347 sec) INFO:tensorflow:global_step/sec: 292.149 INFO:tensorflow:loss = 0.0021164892, step = 17680 (0.346 sec) INFO:tensorflow:global_step/sec: 289.272 INFO:tensorflow:loss = 0.0027668625, step = 17780 (0.350 sec) INFO:tensorflow:global_step/sec: 286.518 INFO:tensorflow:loss = 0.0038928108, step = 17880 (0.356 sec) INFO:tensorflow:global_step/sec: 280.948 INFO:tensorflow:loss = 0.00068626396, step = 17980 (0.340 sec) INFO:tensorflow:global_step/sec: 281.988 INFO:tensorflow:loss = 0.0011843208, step = 18080 (0.349 sec) INFO:tensorflow:global_step/sec: 292.284 INFO:tensorflow:loss = 0.0018866074, step = 18180 (0.351 sec) INFO:tensorflow:global_step/sec: 288.176 INFO:tensorflow:loss = 0.0005333081, step = 18280 (0.352 sec) INFO:tensorflow:global_step/sec: 285.166 INFO:tensorflow:loss = 0.0005375584, step = 18380 (0.360 sec) INFO:tensorflow:global_step/sec: 279.2 INFO:tensorflow:loss = 0.0067465273, step = 18480 (0.355 sec) INFO:tensorflow:global_step/sec: 280.193 INFO:tensorflow:loss = 0.0013988668, step = 18580 (0.344 sec) INFO:tensorflow:global_step/sec: 281.697 INFO:tensorflow:loss = 0.0014645823, step = 18680 (0.351 sec) INFO:tensorflow:global_step/sec: 288.122 INFO:tensorflow:loss = 0.0014383025, step = 18780 (0.360 sec) INFO:tensorflow:global_step/sec: 282.176 INFO:tensorflow:loss = 0.0014143193, step = 18880 (0.361 sec) INFO:tensorflow:global_step/sec: 277.737 INFO:tensorflow:loss = 0.0013943117, step = 18980 (0.357 sec) INFO:tensorflow:global_step/sec: 281.123 INFO:tensorflow:loss = 0.0006448065, step = 19080 (0.357 sec) INFO:tensorflow:global_step/sec: 281.612 INFO:tensorflow:loss = 0.0014809513, step = 19180 (0.348 sec) INFO:tensorflow:global_step/sec: 274.105 INFO:tensorflow:loss = 0.0008602524, step = 19280 (0.358 sec) INFO:tensorflow:global_step/sec: 285.319 INFO:tensorflow:loss = 0.0006964795, step = 19380 (0.363 sec) INFO:tensorflow:global_step/sec: 277.315 INFO:tensorflow:loss = 0.00035264163, step = 19480 (0.366 sec) INFO:tensorflow:global_step/sec: 274.599 INFO:tensorflow:loss = 0.0010025422, step = 19580 (0.367 sec) INFO:tensorflow:global_step/sec: 273.115 INFO:tensorflow:loss = 0.0007096651, step = 19680 (0.362 sec) INFO:tensorflow:global_step/sec: 276.323 INFO:tensorflow:loss = 0.0013329595, step = 19780 (0.351 sec) INFO:tensorflow:global_step/sec: 274.789 INFO:tensorflow:loss = 0.0008460893, step = 19880 (0.357 sec) INFO:tensorflow:global_step/sec: 283.638 INFO:tensorflow:loss = 0.0011283578, step = 19980 (0.368 sec) INFO:tensorflow:global_step/sec: 275.094 INFO:tensorflow:loss = 0.00089822686, step = 20080 (0.365 sec) INFO:tensorflow:global_step/sec: 275.392 INFO:tensorflow:loss = 0.0014473142, step = 20180 (0.364 sec) INFO:tensorflow:global_step/sec: 276.458 INFO:tensorflow:loss = 0.0008915104, step = 20280 (0.373 sec) INFO:tensorflow:global_step/sec: 268.018 INFO:tensorflow:loss = 0.0004781757, step = 20380 (0.353 sec) INFO:tensorflow:global_step/sec: 272.515 INFO:tensorflow:loss = 0.0004186085, step = 20480 (0.363 sec) INFO:tensorflow:global_step/sec: 280.449 INFO:tensorflow:loss = 0.0008953349, step = 20580 (0.364 sec) INFO:tensorflow:global_step/sec: 278.265 INFO:tensorflow:loss = 0.0015090622, step = 20680 (0.371 sec) INFO:tensorflow:global_step/sec: 270.082 INFO:tensorflow:loss = 0.0010438098, step = 20780 (0.374 sec) INFO:tensorflow:global_step/sec: 267.97 INFO:tensorflow:loss = 0.00050447625, step = 20880 (0.376 sec) INFO:tensorflow:global_step/sec: 267.517 INFO:tensorflow:loss = 0.00037436924, step = 20980 (0.364 sec) INFO:tensorflow:global_step/sec: 262.304 INFO:tensorflow:loss = 0.0005487846, step = 21080 (0.371 sec) INFO:tensorflow:global_step/sec: 276.63 INFO:tensorflow:loss = 0.0012135495, step = 21180 (0.372 sec) INFO:tensorflow:global_step/sec: 271.146 INFO:tensorflow:loss = 0.00050225714, step = 21280 (0.374 sec) INFO:tensorflow:global_step/sec: 266.848 INFO:tensorflow:loss = 0.0005835245, step = 21380 (0.380 sec) INFO:tensorflow:global_step/sec: 266.179 INFO:tensorflow:loss = 0.0004619556, step = 21480 (0.375 sec) INFO:tensorflow:global_step/sec: 266.419 INFO:tensorflow:loss = 0.00033856914, step = 21580 (0.363 sec) INFO:tensorflow:global_step/sec: 265.468 INFO:tensorflow:loss = 0.0008394742, step = 21680 (0.373 sec) INFO:tensorflow:global_step/sec: 272.316 INFO:tensorflow:loss = 0.00030781276, step = 21780 (0.374 sec) INFO:tensorflow:global_step/sec: 270.614 INFO:tensorflow:loss = 0.00032267775, step = 21880 (0.375 sec) INFO:tensorflow:global_step/sec: 266.912 INFO:tensorflow:loss = 0.00024132222, step = 21980 (0.378 sec) INFO:tensorflow:global_step/sec: 265.246 INFO:tensorflow:loss = 0.00028675678, step = 22080 (0.376 sec) INFO:tensorflow:global_step/sec: 266.509 INFO:tensorflow:loss = 0.0009781871, step = 22180 (0.365 sec) INFO:tensorflow:global_step/sec: 263.828 INFO:tensorflow:loss = 0.0010109144, step = 22280 (0.370 sec) INFO:tensorflow:global_step/sec: 274.649 INFO:tensorflow:loss = 0.00025149249, step = 22380 (0.378 sec) INFO:tensorflow:global_step/sec: 267.999 INFO:tensorflow:loss = 0.00020908765, step = 22480 (0.378 sec) INFO:tensorflow:global_step/sec: 265.322 INFO:tensorflow:loss = 0.0004320807, step = 22580 (0.384 sec) INFO:tensorflow:global_step/sec: 260.926 INFO:tensorflow:loss = 0.0002488165, step = 22680 (0.385 sec) INFO:tensorflow:global_step/sec: 259.177 INFO:tensorflow:loss = 0.0004015111, step = 22780 (0.376 sec) INFO:tensorflow:global_step/sec: 256.529 INFO:tensorflow:loss = 0.00037404272, step = 22880 (0.385 sec) INFO:tensorflow:global_step/sec: 264.999 INFO:tensorflow:loss = 0.00039812157, step = 22980 (0.387 sec) INFO:tensorflow:global_step/sec: 260.906 INFO:tensorflow:loss = 0.0005162174, step = 23080 (0.386 sec) INFO:tensorflow:global_step/sec: 259.663 INFO:tensorflow:loss = 0.00032000744, step = 23180 (0.387 sec) INFO:tensorflow:global_step/sec: 258.701 INFO:tensorflow:loss = 0.00025557584, step = 23280 (0.391 sec) INFO:tensorflow:global_step/sec: 255.811 INFO:tensorflow:loss = 0.00018507428, step = 23380 (0.372 sec) INFO:tensorflow:global_step/sec: 260.467 INFO:tensorflow:loss = 0.00010121861, step = 23480 (0.376 sec) INFO:tensorflow:global_step/sec: 271.391 INFO:tensorflow:loss = 0.00043678225, step = 23580 (0.381 sec) INFO:tensorflow:global_step/sec: 264.417 INFO:tensorflow:loss = 0.0002813889, step = 23680 (0.391 sec) INFO:tensorflow:global_step/sec: 257.244 INFO:tensorflow:loss = 9.453914e-05, step = 23780 (0.393 sec) INFO:tensorflow:global_step/sec: 254.353 INFO:tensorflow:loss = 0.0002390909, step = 23880 (0.390 sec) INFO:tensorflow:global_step/sec: 240.95 INFO:tensorflow:loss = 0.0008116873, step = 23980 (0.442 sec) INFO:tensorflow:global_step/sec: 229.283 INFO:tensorflow:Saving checkpoints for 24000 into /tmp/tmpbzo1p2wi/model.ckpt. WARNING:tensorflow:Issue encountered when serializing resources. Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore. '_Resource' object has no attribute 'name' INFO:tensorflow:Loss for final step: 0.00040755837. INFO:tensorflow:Calling model_fn. INFO:tensorflow:Done calling model_fn. INFO:tensorflow:Starting evaluation at 2019-11-03T11:19:05Z INFO:tensorflow:Graph was finalized. INFO:tensorflow:Restoring parameters from /tmp/tmpbzo1p2wi/model.ckpt-24000 INFO:tensorflow:Running local_init_op. INFO:tensorflow:Done running local_init_op. INFO:tensorflow:Finished evaluation at 2019-11-03-11:19:05 INFO:tensorflow:Saving dict for global step 24000: average_loss = 12.3817, global_step = 24000, label/mean = 23.611393, loss = 12.283247, prediction/mean = 22.392288 WARNING:tensorflow:Issue encountered when serializing resources. Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore. '_Resource' object has no attribute 'name' INFO:tensorflow:Saving 'checkpoint_path' summary for global step 24000: /tmp/tmpbzo1p2wi/model.ckpt-24000 {'average_loss': 12.3817, 'label/mean': 23.611393, 'loss': 12.283247, 'prediction/mean': 22.392288, 'global_step': 24000} Average-Loss 12.3817
Readers may ignore the next cell.
! python ../.convert_notebook_to_script.py --input ch14_part2.ipynb --output ch14_part2.py
[NbConvertApp] Converting notebook ch14_part2.ipynb to script [NbConvertApp] Writing 6364 bytes to ch14_part2.py