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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""A `Predictor constructed from a `tf.contrib.learn.Estimator`."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.learn.python.learn.utils import saved_model_export_utils
from tensorflow.contrib.predictor import predictor
from tensorflow.python.framework import ops
from tensorflow.python.training import monitored_session
from tensorflow.python.training import saver
class ContribEstimatorPredictor(predictor.Predictor):
"""A `Predictor constructed from a `tf.contrib.learn.Estimator`."""
def __init__(self,
estimator,
prediction_input_fn,
input_alternative_key=None,
output_alternative_key=None,
graph=None,
config=None):
"""Initialize a `ContribEstimatorPredictor`.
Args:
estimator: an instance of `tf.contrib.learn.Estimator`.
prediction_input_fn: a function that takes no arguments and returns an
instance of `InputFnOps`.
input_alternative_key: Optional. Specify the input alternative used for
prediction.
output_alternative_key: Specify the output alternative used for
prediction. Not needed for single-headed models but required for
multi-headed models.
graph: Optional. The Tensorflow `graph` in which prediction should be
done.
config: `ConfigProto` proto used to configure the session.
"""
self._graph = graph or ops.Graph()
with self._graph.as_default():
input_fn_ops = prediction_input_fn()
# pylint: disable=protected-access
model_fn_ops = estimator._get_predict_ops(input_fn_ops.features)
# pylint: enable=protected-access
checkpoint_path = saver.latest_checkpoint(estimator.model_dir)
self._session = monitored_session.MonitoredSession(
session_creator=monitored_session.ChiefSessionCreator(
config=config,
checkpoint_filename_with_path=checkpoint_path))
input_alternative_key = (
input_alternative_key or
saved_model_export_utils.DEFAULT_INPUT_ALTERNATIVE_KEY)
input_alternatives, _ = saved_model_export_utils.get_input_alternatives(
input_fn_ops)
self._feed_tensors = input_alternatives[input_alternative_key]
(output_alternatives,
output_alternative_key) = saved_model_export_utils.get_output_alternatives(
model_fn_ops, output_alternative_key)
_, fetch_tensors = output_alternatives[output_alternative_key]
self._fetch_tensors = fetch_tensors
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