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1# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#     http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15
16"""A `Predictor` constructed from an `learn.python.estimator.Estimator`."""
17
18from __future__ import absolute_import
19from __future__ import division
20from __future__ import print_function
21
22from tensorflow.contrib.predictor import predictor
23from tensorflow.python.estimator import model_fn
24from tensorflow.python.framework import ops
25from tensorflow.python.saved_model import signature_constants
26from tensorflow.python.training import monitored_session
27
28
29def _get_signature_def(
30    serving_input_receiver, estimator, output_key=None):
31  """Construct a `SignatureDef` proto."""
32  if output_key is None:
33    output_key = signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY
34  # pylint: disable=protected-access
35  estimator_spec = estimator.model_fn(
36      serving_input_receiver.features, None, model_fn.ModeKeys.PREDICT,
37      estimator.config)
38  # pylint: enable=protected-access
39  export_outputs = estimator_spec.export_outputs
40  export_output = export_outputs.get(output_key)
41  if export_output is None:
42    raise KeyError('output_key must be one of {}; got {}'.format(
43        export_outputs.keys(), output_key))
44  return export_output.as_signature_def(serving_input_receiver.receiver_tensors)
45
46
47class CoreEstimatorPredictor(predictor.Predictor):
48  """A `Predictor` constructed from an `learn.python.estimator.Estimator`."""
49
50  def __init__(self,
51               estimator,
52               serving_input_receiver_fn,
53               output_key=None,
54               graph=None,
55               config=None):
56    """Initialize a `CoreEstimatorPredictor`.
57
58    Args:
59      estimator: an instance of `learn.python.estimator.Estimator`.
60      serving_input_receiver_fn: a function that takes no arguments and returns
61        an instance of `ServingInputReceiver` compatible with `estimator`.
62      output_key: Optional string specifying the export output to use. If
63        `None`, then `DEFAULT_SERVING_SIGNATURE_DEF_KEY` is used.
64      graph: Optional. The Tensorflow `graph` in which prediction should be
65        done.
66      config: `ConfigProto` proto used to configure the session.
67    """
68    self._graph = graph or ops.Graph()
69    with self._graph.as_default():
70      serving_input_receiver = serving_input_receiver_fn()
71      signature_def = _get_signature_def(
72          serving_input_receiver, estimator, output_key)
73      checkpoint_dir = estimator.model_dir
74      self._session = monitored_session.MonitoredSession(
75          session_creator=monitored_session.ChiefSessionCreator(
76              config=config,
77              checkpoint_dir=checkpoint_dir))
78
79    feed_tensor_info = signature_def.inputs
80    self._feed_tensors = {k: self._graph.get_tensor_by_name(v.name)
81                          for k, v in feed_tensor_info.items()}
82    fetch_tensor_info = signature_def.outputs
83    self._fetch_tensors = {k: self._graph.get_tensor_by_name(v.name)
84                           for k, v in fetch_tensor_info.items()}
85