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task.py
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task.py
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# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Executes model training"""
import sys
import os.path
import logging
import tensorflow as tf
from sklearn.externals import joblib
from sklearn.linear_model import LinearRegression
def get_dummy_data(n):
r = range(n)
X = [[x] for x in r]
Y = [2 * x + 1 for x in r]
return X, Y
def main():
logging.basicConfig()
model = LinearRegression()
X, Y = get_dummy_data(100)
model.fit(X, Y)
# The model name should remain 'model.joblib' for
# AI Platform to be able to create a model version.
model_name = os.path.join(sys.argv[1], 'model.joblib')
logging.info('Model will be saved to "%s..."', model_name)
temp_file = '/tmp/model.joblib'
joblib.dump(model, temp_file)
# Copy the temporary model file to its destination
with tf.io.gfile.GFile(temp_file, 'rb') as temp_file_object:
with tf.io.gfile.GFile(model_name, 'wb') as file_object:
file_object.write(temp_file_object.read())
logging.info('Model was saved')
if __name__ == '__main__':
main()