| /external/tensorflow/tensorflow/contrib/distribute/python/ |
| estimator_training_test.py | 15 """Tests that show Distribute Coordinator works with Estimator."""
42 from tensorflow.python.estimator import exporter as exporter_lib
43 from tensorflow.python.estimator import run_config as run_config_lib
44 from tensorflow.python.estimator import training as estimator_training
45 from tensorflow.python.estimator.canned import dnn_linear_combined
46 from tensorflow.python.estimator.canned import prediction_keys
47 from tensorflow.python.estimator.export import export as export_lib
162 estimator = self._get_estimator(train_distribute, eval_distribute,
196 estimator,
200 estimator.train(train_input_fn, max_steps=MAX_STEPS
[all...] |
| /external/tensorflow/tensorflow/contrib/boosted_trees/examples/ |
| boston.py | 44 from tensorflow.contrib.boosted_trees.estimator_batch.estimator import GradientBoostedDecisionTreeRegressor
53 # Main config - creates a TF Boosted Trees Estimator based on flags.
55 """Configures TF Boosted Trees estimator based on flags."""
64 # Create a TF Boosted trees regression estimator.
65 estimator = GradientBoostedDecisionTreeRegressor(
76 return estimator
93 train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
99 eval_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
117 estimator=_get_tfbt(output_dir, feature_columns),
|
| boston_combined.py | 62 # Create a DNNBoostedTreeCombinedRegressor estimator.
63 estimator = DNNBoostedTreeCombinedRegressor(
75 return estimator
83 train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
89 eval_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
101 estimator=_get_estimator(output_dir, feature_columns),
|
| binary_mnist.py | 41 from tensorflow.contrib.boosted_trees.estimator_batch.estimator import GradientBoostedDecisionTreeClassifier
74 # Main config - creates a TF Boosted Trees Estimator based on flags.
76 """Configures TF Boosted Trees estimator based on flags."""
88 # Create a TF Boosted trees estimator that can take in custom loss.
89 estimator = GradientBoostedDecisionTreeClassifier(
96 return estimator
106 estimator=_get_tfbt(output_dir),
|
| mnist.py | 42 from tensorflow.contrib.boosted_trees.estimator_batch.estimator import GradientBoostedDecisionTreeClassifier
69 # Main config - creates a TF Boosted Trees Estimator based on flags.
71 """Configures TF Boosted Trees estimator based on flags."""
89 # Create a TF Boosted trees estimator that can take in custom loss.
90 estimator = GradientBoostedDecisionTreeClassifier(
98 return estimator
108 estimator=_get_tfbt(output_dir),
|
| /external/tensorflow/tensorflow/contrib/gan/python/estimator/python/ |
| latent_gan_estimator_impl.py | 15 """Implements an estimator wrapper that allows training the input latent space.
17 This file implements a latent gan estimator that wraps around a previously
18 trained GAN. The latent gan estimator trains a single variable z, representing
20 z, the inpainting estimator can move around the latent z space towards
23 The latent gan estimator has a few key differences from a normal estimator.
25 First: the variables in the estimator should not be saved, as we are not
32 inpainter estimator will run.
54 config = tf.estimator.RunConfig()
57 estimator = latent_gan_estimator.get_latent_gan_estimator
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| svm.py | 15 """Support Vector Machine (SVM) Estimator (deprecated).
29 from tensorflow.contrib.learn.python.learn.estimators import estimator
41 class SVM(estimator.Estimator):
56 `Estimator` (where there is one process per worker) is the number of workers
65 estimator = SVM(
76 estimator.fit(input_fn=input_fn_train)
77 estimator.evaluate(input_fn=input_fn_eval)
78 estimator.predict(x=x)
105 """Constructs an `SVM` estimator object
[all...] |
| estimators_test.py | 29 from tensorflow.contrib.learn.python.learn.estimators import estimator as estimator_lib
68 estimator = estimator_lib.Estimator(
70 estimator.fit(input_fn=input_fn, steps=1)
71 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
74 metrics = estimator.evaluate(
108 estimator = estimator_lib.Estimator(
110 estimator.fit(input_fn=input_fn, steps=1)
111 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True)
[all...] |
| estimator_test.py | 15 """Tests for Estimator."""
44 from tensorflow.contrib.learn.python.learn.estimators import estimator
267 est = estimator.Estimator(model_fn=resource_constant_model_fn)
337 # TODO(ptucker): We have to roll our own mock since Estimator._get_arguments
350 est = estimator.Estimator(
365 # TODO(ptucker): We have to roll our own mock since Estimator._get_arguments
383 est = estimator.Estimator(
[all...] |
| __init__.py | 16 """An estimator is a rule for calculating an estimate of a given quantity (deprecated).
18 These classes are deprecated and replaced with `tf.estimator`.
30 ## Choosing the correct estimator
38 * `Estimator`: Use when you need a custom model.
49 * `Estimator`: Use when you need custom model for N class classification.
55 own custom estimator as described in the section below.
62 estimator.
64 Feature columns may vary based on the estimator used. So you can see which
65 feature columns are fed to each estimator in the below section.
89 ### Create the pre-canned estimator
[all...] |
| /external/tensorflow/tensorflow/contrib/predictor/ |
| testing_common.py | 23 from tensorflow.contrib.learn.python.learn.estimators import estimator as contrib_estimator
26 from tensorflow.python.estimator import estimator as core_estimator
27 from tensorflow.python.estimator import model_fn
28 from tensorflow.python.estimator.export import export_lib
29 from tensorflow.python.estimator.export import export_output
39 """Returns an `Estimator` that performs basic arithmetic.
42 core: if `True`, returns a `tensorflow.python.estimator.Estimator`.
43 Otherwise, returns a `tensorflow.contrib.learn.Estimator`
[all...] |
| /external/webrtc/webrtc/modules/remote_bitrate_estimator/tools/ |
| bwe_rtp.cc | 75 webrtc::RemoteBitrateEstimator** estimator,
113 // Setup the RTP header parser and the bitrate estimator.
116 if (estimator) {
119 *estimator =
125 *estimator =
|
| bwe_rtp_play.cc | 42 webrtc::RemoteBitrateEstimator* estimator; local
48 &parser, &estimator, &estimator_used)) {
53 rtc::scoped_ptr<webrtc::RemoteBitrateEstimator> rbe(estimator);
105 printf("Estimator used: %s\n", estimator_used.c_str());
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| main_estimator.py | 15 """Estimator workflow with RevNet train on CIFAR-10."""
31 """Function specifying the model that is required by the `tf.estimator` API.
40 An instance of `tf.estimator.EstimatorSpec`
50 if mode == tf.estimator.ModeKeys.TRAIN:
62 return tf.estimator.EstimatorSpec(mode=mode, loss=loss, train_op=train_op)
68 if mode == tf.estimator.ModeKeys.EVAL:
70 return tf.estimator.EstimatorSpec(
78 else: # mode == tf.estimator.ModeKeys.PREDICT
84 return tf.estimator.EstimatorSpec(
88 "classify": tf.estimator.export.PredictOutput(result
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| export_strategy.py | 49 export_fn: A function that writes an export, given an estimator, a
59 * `(estimator, export_path) -> export_path`
60 * `(estimator, export_path, checkpoint_path) -> export_path`
61 * `(estimator, export_path, checkpoint_path, eval_result) -> export_path`
62 * `(estimator, export_path, checkpoint_path, eval_result,
69 @deprecated(None, 'Please switch to tf.estimator.train_and_evaluate, and use '
70 'tf.estimator.Exporter.')
76 estimator,
80 """Exports the given Estimator to a specific format.
83 estimator: the Estimator to export
[all...] |
| monitors_test.py | 33 from tensorflow.python.estimator import estimator as core_estimator
319 @test.mock.patch.object(estimators, 'Estimator', autospec=True)
323 estimator = mock_estimator_class()
325 estimator.model_dir = model_dir
332 monitor.set_estimator(estimator)
338 @test.mock.patch.object(estimators, 'Estimator', autospec=True)
343 estimator = mock_estimator_class()
345 estimator.model_dir = model_dir
346 estimator.evaluate.return_value = {
[all...] |
| /external/tensorflow/tensorflow/contrib/timeseries/examples/ |
| multivariate.py | 50 estimator = tf.contrib.timeseries.StructuralEnsembleRegressor(
59 estimator.train(input_fn=train_input_fn, steps=training_steps)
61 current_state = estimator.evaluate(input_fn=evaluation_input_fn, steps=1)
68 input_receiver_fn = estimator.build_raw_serving_input_receiver_fn()
69 export_location = estimator.export_saved_model(export_directory,
|
| known_anomaly.py | 96 estimator, batch_size, window_size = estimator_fn(
114 estimator.train(input_fn=train_input_fn, steps=train_steps)
116 evaluation = estimator.evaluate(input_fn=evaluation_input_fn, steps=1)
122 (predictions,) = tuple(estimator.predict(
|
| lstm_test.py | 23 from tensorflow.python.estimator import estimator_lib
|
| predict.py | 15 """An example of training and predicting with a TFTS estimator."""
72 def train_and_predict(estimator, csv_file_name, training_steps):
80 estimator.train(input_fn=train_input_fn, steps=training_steps)
85 evaluation = estimator.evaluate(input_fn=evaluation_input_fn, steps=1)
87 (predictions,) = tuple(estimator.predict(
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/utils/ |
| export.py | 43 @deprecated('2017-03-25', 'Please use Estimator.export_savedmodel() instead.')
53 @deprecated('2017-03-25', 'Please use Estimator.export_savedmodel() instead.')
68 @deprecated('2017-03-25', 'Please use Estimator.export_savedmodel() instead.')
262 @deprecated('2017-03-25', 'Please use Estimator.export_savedmodel() instead.')
263 def _default_input_fn(estimator, examples):
264 """Creates default input parsing using Estimator's feature signatures."""
265 return estimator._get_feature_ops_from_example(examples)
268 @deprecated('2016-09-23', 'Please use Estimator.export_savedmodel() instead.')
269 def export_estimator(estimator,
275 """Deprecated, please use Estimator.export_savedmodel().""
[all...] |
| /external/tensorflow/tensorflow/python/data/experimental/kernel_tests/serialization/ |
| checkpoint_input_pipeline_hook_test.py | 33 from tensorflow_estimator.python.estimator import estimator
34 from tensorflow_estimator.python.estimator import model_fn
77 est = estimator.Estimator(model_fn=self._model_fn)
91 est = estimator.Estimator(model_fn=self._model_fn)
103 est = estimator.Estimator(model_fn=self._model_fn)
118 est = estimator.Estimator(model_fn=self._model_fn
[all...] |
| /external/tensorflow/tensorflow/core/grappler/costs/ |
| analytical_cost_estimator_test.cc | 97 AnalyticalCostEstimator estimator(cluster_.get(), /*use_static_shapes=*/true,
99 TF_ASSERT_OK(estimator.Initialize(item));
103 TF_ASSERT_OK(estimator.PredictCosts(item.graph, &run_metadata, &summary));
111 // TODO(http://b/70031255): Accurate estimator for RandomUniform op needed
112 // TODO(http://b/70031363): Accurate estimator for Softmax needed
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| estimator_test.py | 15 """Tests for GBDT estimator."""
23 from tensorflow.contrib.boosted_trees.estimator_batch import estimator
27 from tensorflow.python.estimator.canned import head as head_lib
28 from tensorflow.python.estimator.inputs import numpy_io
151 classifier = estimator.GradientBoostedDecisionTreeClassifier(
170 classifier = estimator.GradientBoostedDecisionTreeClassifier(
196 model = estimator.GradientBoostedDecisionTreeEstimator(
217 classifier = estimator.GradientBoostedDecisionTreeClassifier(
237 regressor = estimator.GradientBoostedDecisionTreeRegressor(
260 model = estimator.GradientBoostedDecisionTreeRanker
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| numpy_io.py | 26 from tensorflow.python.estimator.inputs.numpy_io import numpy_input_fn as core_numpy_input_fn
30 @deprecated(None, 'Use tf.compat.v1.estimator.inputs.numpy_input_fn.')
|
