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.
FastText is a library for efficient learning of word representations and sentence classification.
The goal of text classification is to assign documents (such as emails, posts, text messages, product reviews, etc...) to one or multiple categories. Such categories can be review scores, spam v.s. non-spam, or the language in which the document was typed. Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels).
As an example, it builds a classifier which automatically classifies stackexchange questions about cooking into one of several possible tags, such as pot
, bowl
or baking
.
This example notebook is base on the guide from fasttext: https://fasttext.cc/docs/en/supervised-tutorial.html
%reload_ext autoreload
%autoreload 2
%matplotlib inline
import warnings
warnings.filterwarnings("ignore")
!pip install -q bentoml "fasttext==0.9.2"
Requirement already satisfied: fasttext in /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages (0.9.2) Requirement already satisfied: numpy in /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages (from fasttext) (1.16.4) Requirement already satisfied: pybind11>=2.2 in /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages (from fasttext) (2.5.0) Requirement already satisfied: setuptools>=0.7.0 in /usr/local/anaconda3/envs/dev-py3/lib/python3.7/site-packages (from fasttext) (45.1.0.post20200119)
!curl https://dl.fbaipublicfiles.com/fasttext/data/cooking.stackexchange.tar.gz --output cooking.stackexchange.tar.gz && tar xvzf cooking.stackexchange.tar.gz
% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 446k 100 446k 0 0 466k 0 --:--:-- --:--:-- --:--:-- 465k x cooking.stackexchange.id x cooking.stackexchange.txt x readme.txt
!head cooking.stackexchange.txt
__label__sauce __label__cheese How much does potato starch affect a cheese sauce recipe? __label__food-safety __label__acidity Dangerous pathogens capable of growing in acidic environments __label__cast-iron __label__stove How do I cover up the white spots on my cast iron stove? __label__restaurant Michelin Three Star Restaurant; but if the chef is not there __label__knife-skills __label__dicing Without knife skills, how can I quickly and accurately dice vegetables? __label__storage-method __label__equipment __label__bread What's the purpose of a bread box? __label__baking __label__food-safety __label__substitutions __label__peanuts how to seperate peanut oil from roasted peanuts at home? __label__chocolate American equivalent for British chocolate terms __label__baking __label__oven __label__convection Fan bake vs bake __label__sauce __label__storage-lifetime __label__acidity __label__mayonnaise Regulation and balancing of readymade packed mayonnaise and other sauces
!head -n 12404 cooking.stackexchange.txt > cooking.train
!tail -n 3000 cooking.stackexchange.txt > cooking.valid
import fasttext
model = fasttext.train_supervised(input="cooking.train")
%%writefile text_classification.py
from bentoml import env, artifacts, BentoService, api
from bentoml.frameworks.fasttext import FasttextModelArtifact
from bentoml.adapters import JsonInput
@env(infer_pip_packages=True)
@artifacts([FasttextModelArtifact('model')])
class FasttextClassification(BentoService):
@api(input=JsonInput(), batch=True)
def predict(self, json_list):
input = [i['text'] for i in json_list]
result = self.artifacts.model.predict(input)
# return top result
prediction_result = [i[0].replace('__label__', '') for i in result[0]]
return prediction_result
Writing text_classification.py
from text_classification import FasttextClassification
svc = FasttextClassification()
svc.pack('model', model)
saved_path = svc.save()
[2020-09-22 12:09:52,940] 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 12:09:53,839] 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 12:09:55,087] INFO - Detected non-PyPI-released BentoML installed, copying local BentoML modulefiles to target saved bundle path..
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 12:10:00,091] INFO - BentoService bundle 'FasttextClassification:20200922120954_28C4D0' saved to: /Users/bozhaoyu/bentoml/repository/FasttextClassification/20200922120954_28C4D0
To start a REST API model server with the BentoService saved above, use the bentoml serve command:
!bentoml serve {saved_path}
[2020-09-22 12:11:58,505] INFO - Starting BentoML API server in development mode.. [2020-09-22 12:11:58,967] 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 12:11:58,981] 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 12:11:59,380] 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. Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar. * Serving Flask app "FasttextClassification" (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 12:12:17,344] INFO - {'service_name': 'FasttextClassification', 'service_version': '20200922120954_28C4D0', 'api': 'predict', 'task': {'data': '{"text": "Which baking dish is best to bake a banana bread ?"}', 'task_id': '81e679d6-5cab-48c5-9ce2-b486cbf7c6c7', 'http_headers': (('Host', 'localhost:5000'), ('User-Agent', 'curl/7.65.3'), ('Accept', '*/*'), ('Content-Type', 'application/json'), ('Content-Length', '62'))}, 'result': {'data': '"baking"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': '81e679d6-5cab-48c5-9ce2-b486cbf7c6c7'} 127.0.0.1 - - [22/Sep/2020 12:12:17] "POST /predict HTTP/1.1" 200 - WARNING: Logging before flag parsing goes to stderr. I0922 12:12:17.346314 4676050368 _internal.py:122] 127.0.0.1 - - [22/Sep/2020 12:12:17] "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 FasttextClassification:latest --run-with-ngrok
[2020-09-22 12:11:20,296] INFO - Getting latest version FasttextClassification:20200922120954_28C4D0 [2020-09-22 12:11:20,297] INFO - Starting BentoML API server in development mode.. [2020-09-22 12:11:20,550] 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 12:11:20,564] 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 12:11:20,902] 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. Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar. * Serving Flask app "FasttextClassification" (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) Exception in thread Thread-1: Traceback (most recent call last): File "/usr/local/anaconda3/envs/dev-py3/lib/python3.7/threading.py", line 917, in _bootstrap_inner self.run() File "/usr/local/anaconda3/envs/dev-py3/lib/python3.7/threading.py", line 1166, in run self.function(*self.args, **self.kwargs) File "/Users/bozhaoyu/src/bento/bentoml/utils/flask_ngrok.py", line 90, in start_ngrok ngrok_address = _run_ngrok(port) File "/Users/bozhaoyu/src/bento/bentoml/utils/flask_ngrok.py", line 39, in _run_ngrok os.chmod(executable, 0o777) FileNotFoundError: [Errno 2] No such file or directory: '/var/folders/kn/xnc9k74x03567n1mx2tfqnpr0000gn/T/ngrok/ngrok' 127.0.0.1 - - [22/Sep/2020 12:11:29] "GET / HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /swagger_static/swagger-ui.css HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /swagger_static/swagger-ui-bundle.js HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /docs.json HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /favicon.ico HTTP/1.1" 404 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET //favicon.ico HTTP/1.1" 308 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET / HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /swagger_static/swagger-ui.css HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /swagger_static/swagger-ui-bundle.js HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:30] "GET /docs.json HTTP/1.1" 200 - 127.0.0.1 - - [22/Sep/2020 12:11:31] "GET /favicon.ico HTTP/1.1" 404 - ^C
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 -X POST \
http://localhost:5000/predict \
-H 'Content-Type: application/json' \
-d '{"text": "Which baking dish is best to bake a banana bread ?"}'
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 FasttextClassification:latest
[2020-09-22 12:13:07,456] INFO - Getting latest version FasttextClassification:20200922120954_28C4D0 Found Bento: /Users/bozhaoyu/bentoml/repository/FasttextClassification/20200922120954_28C4D0 [2020-09-22 12:13:07,495] 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 12:13:07,511] 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: 'fasttextclassification:20200922120954_28C4D0' Building Docker image fasttextclassification:20200922120954_28C4D0 from FasttextClassification:latest -we in here processed docker file (None, None) root in create archive /Users/bozhaoyu/bentoml/repository/FasttextClassification/20200922120954_28C4D0 ['Dockerfile', 'FasttextClassification', 'FasttextClassification/__init__.py', 'FasttextClassification/__pycache__', 'FasttextClassification/__pycache__/text_classification.cpython-37.pyc', 'FasttextClassification/artifacts', 'FasttextClassification/artifacts/__init__.py', 'FasttextClassification/artifacts/model', 'FasttextClassification/bentoml.yml', 'FasttextClassification/text_classification.py', 'MANIFEST.in', '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 0x7ffe4d5b5d68> {'t': 'fasttextclassification:20200922120954_28C4D0', '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= \ ---> Running in e09cbc5bfce1 - ---> fc6e47d06522 Step 3/15 : ENV EXTRA_PIP_INSTALL_ARGS $EXTRA_PIP_INSTALL_ARGS / ---> Running in 232b8623b0b9 | ---> db8172e98571 Step 4/15 : COPY environment.yml requirements.txt setup.sh* bentoml-init.sh python_version* /bento/ / ---> c41f172d737b Step 5/15 : WORKDIR /bento | ---> Running in 1e1c28b0fd29 \ ---> 61863d5599df Step 6/15 : RUN chmod +x /bento/bentoml-init.sh ---> Running in 0bf14a8a8cdf / ---> 3bba73c15b1a Step 7/15 : RUN if [ -f /bento/bentoml-init.sh ]; then bash -c /bento/bentoml-init.sh; fi ---> Running in cfa5c292d12e -+++ 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. + command -v conda + echo 'Updating conda base environment with environment.yml' + conda env update -n base -f ./environment.yml Updating conda base environment with environment.yml \Collecting package metadata (repodata.json): ...working... -done Solving environment: ...working... -done / Downloading and Extracting Packages pip-20.2.3 | 1.1 MB | | 0% pip-20.2.3 | 1.1 MB | 1 | 1% pip-20.2.3 | 1.1 MB | #####1 | 51% pip-20.2.3 | 1.1 MB | ########## | 100% pip-20.2.3 | 1.1 MB | ########## | 100% python_abi-3.7 | 4 KB | | 0% python_abi-3.7 | 4 KB | ########## | 100% python-3.7.9 | 45.3 MB | | 0% python-3.7.9 | 45.3 MB | | 0% python-3.7.9 | 45.3 MB | 1 | 2% python-3.7.9 | 45.3 MB | 4 | 4% python-3.7.9 | 45.3 MB | 6 | 7% python-3.7.9 | 45.3 MB | 9 | 9% python-3.7.9 | 45.3 MB | #2 | 12% python-3.7.9 | 45.3 MB | #5 | 15% python-3.7.9 | 45.3 MB | #8 | 19% python-3.7.9 | 45.3 MB | ##2 | 22% python-3.7.9 | 45.3 MB | ##5 | 26% python-3.7.9 | 45.3 MB | ##9 | 29% python-3.7.9 | 45.3 MB | 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/opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (0.8.7) 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) 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: 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: psutil in /opt/conda/lib/python3.7/site-packages (from bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (5.7.2) Requirement already satisfied: pybind11>=2.2 in /opt/conda/lib/python3.7/site-packages (from fasttext==0.9.2->-r ./requirements.txt (line 2)) (2.5.0) Requirement already satisfied: setuptools>=0.7.0 in /opt/conda/lib/python3.7/site-packages (from fasttext==0.9.2->-r ./requirements.txt (line 2)) (49.6.0.post20200814) Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.7/site-packages (from python-dateutil<3.0.0,>=2.7.3->bentoml==0.9.0.pre->-r ./requirements.txt (line 1)) (1.15.0) 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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) -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) Building wheels for collected packages: fasttext Building wheel for fasttext (setup.py): started - Building wheel for fasttext (setup.py): finished with status 'done' Created wheel for fasttext: filename=fasttext-0.9.2-cp37-cp37m-linux_x86_64.whl size=4441002 sha256=c9a69b2133d5b1c05b68f9be59d9e74583689c299224445f20de0dcfc227432a Stored in directory: /tmp/pip-ephem-wheel-cache-sx8v7vyg/wheels/4e/ca/bf/b020d2be95f7641801a6597a29c8f4f19e38f9c02a345bab9b Successfully built fasttext /Installing collected packages: fasttext \Successfully installed fasttext-0.9.2 \ ---> a90f620bbe4d Step 8/15 : COPY . /bento \ ---> 5d2abfb72a02 Step 9/15 : RUN if [ -d /bento/bundled_pip_dependencies ]; then pip install -U bundled_pip_dependencies/* ;fi ---> Running in 1f2cf07c7029 |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: numpy in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.19.2) -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: alembic in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (1.4.3) 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: aiohttp in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (3.6.2) 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: 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: 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: tabulate in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (0.8.7) 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: packaging in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (20.4) 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: configparser in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (5.0.0) 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: 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: multidict in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (4.7.6) 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: 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: certifi in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (2020.6.20) 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: docker in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (4.3.1) |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: humanfriendly in /opt/conda/lib/python3.7/site-packages (from BentoML==0.9.0rc0+3.gcebf2015) (8.2) 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: 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: six in /opt/conda/lib/python3.7/site-packages (from sqlalchemy-utils<0.36.8->BentoML==0.9.0rc0+3.gcebf2015) (1.15.0) 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: 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: setuptools>=3.0 in /opt/conda/lib/python3.7/site-packages (from gunicorn->BentoML==0.9.0rc0+3.gcebf2015) (49.6.0.post20200814) 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: 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: 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: chardet<4.0,>=2.0 in /opt/conda/lib/python3.7/site-packages (from aiohttp->BentoML==0.9.0rc0+3.gcebf2015) (3.0.4) 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: MarkupSafe>=0.9.2 in /opt/conda/lib/python3.7/site-packages (from Mako->alembic->BentoML==0.9.0rc0+3.gcebf2015) (1.1.1) 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) 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) 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=0bd361a45c83e2bb80aa10347199c1fd71684e3a1389eec1208f54b4297c1140 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 / ---> 860b9bec3b35 Step 10/15 : ENV PORT 5000 | ---> Running in c2743985d5de \ ---> c3f39fdc8450 Step 11/15 : EXPOSE $PORT ---> Running in 0733c7dcfea4 - ---> bd7997accbc4 Step 12/15 : COPY docker-entrypoint.sh /usr/local/bin/ | ---> 71c57d9f3c42 Step 13/15 : RUN chmod +x /usr/local/bin/docker-entrypoint.sh \ ---> Running in 8e7c893f2534 / ---> e1c5868e8975 Step 14/15 : ENTRYPOINT [ "docker-entrypoint.sh" ] ---> Running in 033db21d262e | ---> 24858e5a145c Step 15/15 : CMD ["bentoml", "serve-gunicorn", "/bento"] ---> Running in b1700521fdb7 \ ---> e35ff263b52f Successfully built e35ff263b52f -Successfully tagged fasttextclassification:20200922120954_28C4D0 Finished building fasttextclassification:20200922120954_28C4D0 from FasttextClassification:latest
!docker run --rm -p5000:5000 fasttextclassification:20200922120954_28C4D0
[2020-09-22 19:17:58,674] INFO - Starting BentoML API server in production mode.. [2020-09-22 19:17:59,100] INFO - get_gunicorn_num_of_workers: 3, calculated by cpu count [2020-09-22 19:17:59 +0000] [1] [INFO] Starting gunicorn 20.0.4 [2020-09-22 19:17:59 +0000] [1] [INFO] Listening at: http://0.0.0.0:5000 (1) [2020-09-22 19:17:59 +0000] [1] [INFO] Using worker: sync [2020-09-22 19:17:59 +0000] [11] [INFO] Booting worker with pid: 11 [2020-09-22 19:17:59 +0000] [12] [INFO] Booting worker with pid: 12 [2020-09-22 19:17:59 +0000] [13] [INFO] Booting worker with pid: 13 [2020-09-22 19:17:59,365] WARNING - Using BentoML not from official PyPI release. In order to find the same version of BentoML when deploying your BentoService, you must set the 'core/bentoml_deploy_version' config to a http/git location of your BentoML fork, e.g.: 'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}' [2020-09-22 19:17:59,387] 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 19:17:59,387] WARNING - Saved BentoService Python version mismatch: loading BentoService bundle created with Python version 3.7.3, but current environment version is 3.7.9. [2020-09-22 19:17:59,394] WARNING - Using BentoML not from official PyPI release. In order to find the same version of BentoML when deploying your BentoService, you must set the 'core/bentoml_deploy_version' config to a http/git location of your BentoML fork, e.g.: 'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}' [2020-09-22 19:17:59,420] 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 19:17:59,422] WARNING - Saved BentoService Python version mismatch: loading BentoService bundle created with Python version 3.7.3, but current environment version is 3.7.9. [2020-09-22 19:17:59,500] WARNING - Using BentoML not from official PyPI release. In order to find the same version of BentoML when deploying your BentoService, you must set the 'core/bentoml_deploy_version' config to a http/git location of your BentoML fork, e.g.: 'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}' [2020-09-22 19:17:59,528] 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 19:17:59,529] WARNING - Saved BentoService Python version mismatch: loading BentoService bundle created with Python version 3.7.3, but current environment version is 3.7.9. [2020-09-22 19:18:08,246] INFO - {'service_name': 'FasttextClassification', 'service_version': '20200922120954_28C4D0', 'api': 'predict', 'task': {'data': '{"text": "Which baking dish is best to bake a banana bread ?"}', 'task_id': '307d893e-df06-44c9-bba4-1098a6c34cea', 'http_headers': (('Host', 'localhost:5000'), ('User-Agent', 'curl/7.65.3'), ('Accept', '*/*'), ('Content-Type', 'application/json'), ('Content-Length', '62'))}, 'result': {'data': '"baking"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': '307d893e-df06-44c9-bba4-1098a6c34cea'} ^C [2020-09-22 19:18:15 +0000] [1] [INFO] Handling signal: int Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar. [2020-09-22 19:18:15 +0000] [11] [INFO] Worker exiting (pid: 11) Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar. [2020-09-22 19:18:15 +0000] [13] [INFO] Worker exiting (pid: 13) Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar. [2020-09-22 19:18:15 +0000] [12] [INFO] Worker exiting (pid: 12)
bentoml.load is the API for loading a BentoML packaged model in python:
from bentoml import load
svc = load(saved_path)
print(svc.predict([{"text": "which baking dish is the best?"}]))
[2020-09-22 12:18:22,256] 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 12:18:22,257] WARNING - Module `text_classification` already loaded, using existing imported module. [2020-09-22 12:18:22,278] WARNING - pip package requirement fasttext already exist ['baking']
Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar.
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 FasttextClassification:latest predict --input '{"text": "Which baking dish is best to bake a banana bread ?"}'
[2020-09-22 12:18:42,572] INFO - Getting latest version FasttextClassification:20200922120954_28C4D0 [2020-09-22 12:18:42,609] 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 12:18:42,623] 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 12:18:43,064] 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. Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar. [2020-09-22 12:18:47,361] INFO - {'service_name': 'FasttextClassification', 'service_version': '20200922120954_28C4D0', 'api': 'predict', 'task': {'data': '{"text": "Which baking dish is best to bake a banana bread ?"}', 'task_id': '54edf965-1d7d-4eb9-929c-c7d0d0e21732', 'cli_args': ('--input {"text": "Which baking dish is best to bake a banana bread ?"}',)}, 'result': {'data': '"baking"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': '54edf965-1d7d-4eb9-929c-c7d0d0e21732'} "baking"
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: