| /external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
| extenders_test.py | 39 def input_fn(): function in function:get_input_fn
46 return input_fn
52 input_fn = get_input_fn(
61 estimator.train(input_fn=input_fn)
62 metrics = estimator.evaluate(input_fn=input_fn)
79 input_fn = get_input_fn(x=[[[0.]]], y=[[[1]]])
91 estimator.train(input_fn=input_fn)
168 def input_fn(): function in function:ForwardFeaturesTest.test_forward_single_key
182 def input_fn(): function in function:ForwardFeaturesTest.test_forward_list
198 def input_fn(): function in function:ForwardFeaturesTest.test_forward_all
225 def input_fn(): function in function:ForwardFeaturesTest.test_key_should_be_in_features
238 def input_fn(): function in function:ForwardFeaturesTest.test_forwarded_feature_should_not_be_a_sparse_tensor
258 def input_fn(): function in function:ForwardFeaturesTest.test_predictions_should_be_dict
279 def input_fn(): function in function:ForwardFeaturesTest.test_should_not_conflict_with_existing_predictions
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| svm_test.py | 33 def input_fn(): function in function:SVMTest.testRealValuedFeaturesPerfectlySeparable
46 svm_classifier.fit(input_fn=input_fn, steps=30)
47 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
59 def input_fn(): function in function:SVMTest.testRealValuedFeaturesWithL2Regularization
72 svm_classifier.fit(input_fn=input_fn, steps=30)
73 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1
90 def input_fn(): function in function:SVMTest.testMultiDimensionalRealValuedFeaturesWithL2Regularization
114 def input_fn(): function in function:SVMTest.testRealValuedFeaturesWithMildL1Regularization
142 def input_fn(): function in function:SVMTest.testRealValuedFeaturesWithBigL1Regularization
170 def input_fn(): function in function:SVMTest.testSparseFeatures
197 def input_fn(): function in function:SVMTest.testBucketizedFeatures
221 def input_fn(): function in function:SVMTest.testMixedFeatures
[all...] |
| linear_test.py | 82 def input_fn(): function in function:LinearClassifierTest.testTrain
96 classifier.fit(input_fn=input_fn, steps=100)
97 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
98 classifier.fit(input_fn=input_fn, steps=200)
99 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
106 def input_fn() function in function:LinearClassifierTest.testJointTrain
445 def input_fn(num_epochs=None): function in function:LinearClassifierTest.testLogisticFractionalLabels
509 def input_fn(num_epochs=None): function in function:LinearClassifierTest.testTrainSaveLoad
625 def input_fn(): function in function:LinearClassifierTest.testExport
647 def input_fn(): function in function:LinearClassifierTest.testDisableCenteredBias
668 def input_fn(): function in function:LinearClassifierTest.testEnableCenteredBias
690 def input_fn(): function in function:LinearClassifierTest.testTrainOptimizerWithL1Reg
715 def input_fn(): function in function:LinearClassifierTest.testTrainWithMissingFeature
734 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerRealValuedFeatures
760 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerRealValuedFeatureWithHigherDimension
781 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerBucketizedFeatures
807 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerSparseFeatures
838 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerWeightedSparseFeatures
869 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerCrossedFeatures
902 def input_fn(): function in function:LinearClassifierTest.testSdcaOptimizerMixedFeatures
941 def input_fn(): function in function:LinearClassifierTest.testEval
986 def input_fn(): function in function:LinearRegressorTest.testRegression
1451 def input_fn(): function in function:LinearRegressorTest.testSdcaOptimizerRealValuedLinearFeatures
1476 def input_fn(): function in function:LinearRegressorTest.testSdcaOptimizerMixedFeaturesArbitraryWeights
1514 def input_fn(): function in function:LinearRegressorTest.testSdcaOptimizerSparseFeaturesWithL1Reg
1586 def input_fn(): function in function:LinearRegressorTest.testSdcaOptimizerBiasOnly
1619 def input_fn(): function in function:LinearRegressorTest.testSdcaOptimizerBiasAndOtherColumns
1681 def input_fn(): function in function:LinearRegressorTest.testSdcaOptimizerBiasAndOtherColumnsFabricatedCentered
1751 def input_fn(): function in function:LinearEstimatorTest.testLinearRegression
1777 def input_fn(): function in function:LinearEstimatorTest.testPoissonRegression
[all...] |
| estimators_test.py | 44 def input_fn(): function in function:FeatureEngineeringFunctionTest.testFeatureEngineeringFn
70 estimator.fit(input_fn=input_fn, steps=1)
71 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
75 input_fn=input_fn,
85 def input_fn(): function in function:FeatureEngineeringFunctionTest.testFeatureEngineeringFnWithSameName
110 estimator.fit(input_fn=input_fn, steps=1
125 def input_fn(): function in function:FeatureEngineeringFunctionTest.testNoneFeatureEngineeringFn
[all...] |
| composable_model_test.py | 122 def input_fn(): function in function:ComposableModelTest.testLinearModel
137 classifier.fit(input_fn=input_fn, steps=1000)
138 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
139 classifier.fit(input_fn=input_fn, steps=2000)
140 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
147 def input_fn() function in function:ComposableModelTest.testJointLinearModel
[all...] |
| debug_test.py | 63 def input_fn(): function in function:_input_fn_builder
70 return input_fn
97 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
100 input_fn=_input_fn_builder(test_features, None))
116 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
119 input_fn=_input_fn_builder(test_features, None))
133 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
136 input_fn=_input_fn_builder(test_features, None))
155 input_fn=_input_fn_builder(train_features, train_labels), steps=50)
158 input_fn=_input_fn_builder(test_features, None)
565 def input_fn(): function in function:DebugClassifierTest.testExport
[all...] |
| svm.py | 67 estimator.fit(input_fn=input_fn_train)
68 estimator.evaluate(input_fn=input_fn_eval)
120 labels which are the output of `input_fn` and
155 def predict_classes(self, x=None, input_fn=None, batch_size=None,
161 input_fn=input_fn,
172 def predict_proba(self, x=None, input_fn=None, batch_size=None, outputs=None,
178 input_fn=input_fn,
189 input_fn=None, default_batch_size=1
[all...] |
| dnn_linear_combined_test.py | 221 estimator.fit(input_fn=test_data.iris_input_multiclass_fn, steps=10)
224 estimator.evaluate(input_fn=test_data.iris_input_multiclass_fn, steps=10)
227 estimator.predict(input_fn=test_data.iris_input_multiclass_fn)
277 classifier.fit(input_fn=_input_fn, steps=2)
297 input_fn=test_data.iris_input_multiclass_fn, steps=100,
348 classifier.fit(input_fn=_input_fn_float_label, steps=50)
370 classifier.fit(input_fn=test_data.iris_input_logistic_fn, steps=100)
372 input_fn=test_data.iris_input_logistic_fn, steps=100)
420 classifier.fit(input_fn=_input_fn, steps=100)
421 scores = classifier.evaluate(input_fn=_input_fn, steps=100
901 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testExport
984 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testGlobalStepLinearOnly
1005 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testGlobalStepDNNOnly
1026 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testGlobalStepDNNLinearCombinedBug
1061 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testGlobalStepDNNLinearCombinedBugFixed
1086 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testLinearOnly
1120 def input_fn(): function in function:DNNLinearCombinedClassifierTest.testLinearOnlyOneFeature
1779 def input_fn(): function in function:FeatureEngineeringFunctionTest.testNoneFeatureEngineeringFn
[all...] |
| dnn_test.py | 212 dnn_estimator.fit(input_fn=_input_fn_train, steps=5)
213 scores = dnn_estimator.evaluate(input_fn=_input_fn_eval, steps=1)
287 classifier.fit(input_fn=_input_fn_float_label, steps=50)
303 input_fn = test_data.iris_input_logistic_fn
304 classifier.fit(input_fn=input_fn, steps=5)
305 scores = classifier.evaluate(input_fn=input_fn, steps=1)
327 classifier.fit(input_fn=_input_fn, steps=5)
328 scores = classifier.evaluate(input_fn=_input_fn, steps=1
970 def input_fn(): function in function:DNNClassifierTest.testExport
[all...] |
| debug.py | 34 classifier.fit(input_fn=input_fn_train)
37 loss = classifier.evaluate(input_fn=input_fn_eval)["loss"]
136 classifier.fit(input_fn=input_fn_train)
139 loss = classifier.evaluate(input_fn=input_fn_eval)["loss"]
177 labels which are the output of `input_fn` and returns
201 def predict_classes(self, input_fn=None, batch_size=None):
205 input_fn: Input function.
214 input_fn=input_fn, batch_size=batch_size, outputs=[key])
218 input_fn=None
[all...] |
| kmeans_test.py | 73 def input_fn(self, member in class:KMeansTestBase
78 """Returns an input_fn that randomly selects batches from given points."""
164 kmeans.fit(input_fn=self.input_fn(), steps=1)
170 kmeans.fit(input_fn=self.input_fn(), steps=1)
172 input_fn=self.input_fn(batch_size=self.num_points), steps=1)
174 kmeans.fit(input_fn=self.input_fn(), steps=steps
564 def input_fn(self): member in class:KMeansTestQueues
[all...] |
| dnn.py | 243 estimator.fit(input_fn=input_fn_train)
247 estimator.evaluate(input_fn=input_fn_eval)
252 estimator.predict_classes(input_fn=input_fn_predict)
267 estimator.fit(input_fn=input_fn_train)
271 estimator.evaluate(input_fn=input_fn_eval)
274 estimator.predict_classes(input_fn=input_fn_predict)
342 labels which are the output of `input_fn` and returns features and
389 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None,
398 input_fn: Input function. If set, x must be None.
416 input_fn=input_fn
[all...] |
| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/ |
| sdca_estimator_test.py | 36 def input_fn(): function in function:SDCALogisticClassifierTest.testRealValuedFeatures
52 classifier.fit(input_fn=input_fn, steps=100)
53 loss = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
59 # input_fn is identical to the one in testRealValuedFeatures where 2
61 def input_fn(): function in function:SDCALogisticClassifierTest.testRealValuedFeatureWithHigherDimension
74 classifier.fit(input_fn=input_fn, steps=100)
75 loss = classifier.evaluate(input_fn=input_fn, steps=1)['loss'
81 def input_fn(): function in function:SDCALogisticClassifierTest.testBucketizedFeatures
108 def input_fn(): function in function:SDCALogisticClassifierTest.testSparseFeatures
138 def input_fn(): function in function:SDCALogisticClassifierTest.testWeightedSparseFeatures
169 def input_fn(): function in function:SDCALogisticClassifierTest.testCrossedFeatures
201 def input_fn(): function in function:SDCALogisticClassifierTest.testMixedFeatures
253 def input_fn(): function in function:SDCALinearRegressorTest.testRealValuedLinearFeatures
277 def input_fn(): function in function:SDCALinearRegressorTest.testMixedFeaturesArbitraryWeights
317 def input_fn(): function in function:SDCALinearRegressorTest.testSdcaOptimizerSparseFeaturesWithL1Reg
387 def input_fn(): function in function:SDCALinearRegressorTest.testBiasOnly
418 def input_fn(): function in function:SDCALinearRegressorTest.testBiasAndOtherColumns
479 def input_fn(): function in function:SDCALinearRegressorTest.testBiasAndOtherColumnsFabricatedCentered
[all...] |
| /external/tensorflow/tensorflow/contrib/predictor/ |
| predictor_factories_test.py | 52 input_fn = testing_common.get_arithmetic_input_fn(core=False)
54 estimator, input_fn, output_alternative_key='sum')
58 input_fn = testing_common.get_arithmetic_input_fn(core=True)
60 predictor_factories.from_contrib_estimator(estimator, input_fn)
64 input_fn = testing_common.get_arithmetic_input_fn(core=True)
65 predictor_factories.from_estimator(estimator, input_fn)
69 input_fn = testing_common.get_arithmetic_input_fn(core=False)
71 predictor_factories.from_estimator(estimator, input_fn)
|
| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| kernel_estimators_test.py | 88 input_fn=_linearly_separable_binary_input_fn, steps=100)
91 input_fn=_linearly_separable_binary_input_fn, steps=1)
100 logreg_classifier.predict_proba(input_fn=
119 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
121 input_fn=_linearly_inseparable_binary_input_fn, steps=1)
125 input_fn=_linearly_inseparable_binary_input_fn, as_iterable=False)
141 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
143 input_fn=_linearly_inseparable_binary_input_fn, steps=1)
157 input_fn=_linearly_inseparable_binary_input_fn, steps=50)
171 input_fn=_linearly_inseparable_binary_input_fn, steps=50
194 def input_fn(): function in function:KernelLinearClassifierTest.testClassifierWithAndWithoutKernelsNoRealValuedColumns
[all...] |
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| gmm_test.py | 38 def input_fn(self, batch_size=None, points=None): member in class:GMMTest
68 clusterer.fit(input_fn=lambda: (constant_op.constant(self.points), None),
92 gmm.fit(input_fn=self.input_fn(), steps=0)
102 gmm.fit(input_fn=self.input_fn(), steps=0)
111 gmm.fit(input_fn=self.input_fn(), steps=1)
112 score1 = gmm.score(input_fn=self.input_fn(batch_size=self.num_points)
191 def input_fn(): function in function:GMMTest.test_random_input_large.get_input_fn
201 def input_fn(self): member in class:GMMTestQueues
[all...] |
| kmeans_test.py | 71 def input_fn(self, member in class:KMeansTestBase
76 """Returns an input_fn that randomly selects batches from given points."""
162 kmeans.train(input_fn=self.input_fn(), steps=1)
168 kmeans.train(input_fn=self.input_fn(), steps=1)
169 score1 = kmeans.score(input_fn=self.input_fn(batch_size=self.num_points))
171 kmeans.train(input_fn=self.input_fn(), steps=steps
556 def input_fn(self): member in class:KMeansTestQueues
[all...] |
| wals_test.py | 82 def input_fn(self, np_matrix, batch_size, mode, member in class:WALSMatrixFactorizationTest
85 """Returns an input_fn that selects row and col batches from np_matrix.
258 input_fn = self.input_fn(np_matrix=self.input_matrix,
262 self._model.fit(input_fn=input_fn, steps=self.row_steps)
269 input_fn = self.input_fn(np_matrix=self.input_matrix,
273 self._model.fit(input_fn=input_fn, steps=self.col_steps
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| pandas_io_test.py | 47 def callInputFnOnce(self, input_fn, session):
48 results = input_fn()
70 input_fn = pandas_io.pandas_input_fn(
73 features, target = self.callInputFnOnce(input_fn, session)
88 input_fn = pandas_io.pandas_input_fn(
91 results = input_fn()
117 input_fn = pandas_io.pandas_input_fn(
120 results = input_fn()
151 input_fn = pandas_io.pandas_input_fn(
154 features = self.callInputFnOnce(input_fn, session
[all...] |
| /external/tensorflow/tensorflow/python/estimator/inputs/ |
| pandas_io_test.py | 50 def callInputFnOnce(self, input_fn, session):
51 results = input_fn()
83 input_fn = pandas_io.pandas_input_fn(
86 features, target = self.callInputFnOnce(input_fn, session)
101 input_fn = pandas_io.pandas_input_fn(
104 results = input_fn()
130 input_fn = pandas_io.pandas_input_fn(
133 results = input_fn()
164 input_fn = pandas_io.pandas_input_fn(
167 features = self.callInputFnOnce(input_fn, session
[all...] |
| numpy_io_test.py | 40 input_fn = numpy_io.numpy_input_fn(
42 features, target = input_fn()
66 input_fn = numpy_io.numpy_input_fn(
68 features, target = input_fn()
91 input_fn = numpy_io.numpy_input_fn(
93 features, target = input_fn()
112 input_fn = numpy_io.numpy_input_fn(
114 features, target = input_fn()
148 input_fn = numpy_io.numpy_input_fn(
150 features, target = input_fn()
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/utils/ |
| input_fn_utils.py | 41 """A return type for an input_fn.
43 This return type is currently only supported for serving input_fn.
44 Training and eval input_fn should return a `(features, labels)` tuple.
53 the input placeholders (if any) that this input_fn expects to be fed.
54 Typically, this is used by a serving input_fn, which expects to be fed
60 """Build an input_fn appropriate for serving, expecting fed tf.Examples.
62 Creates an input_fn that expects a serialized tf.Example fed into a string
64 feature_spec, and returns all parsed Tensors as features. This input_fn is
73 An input_fn suitable for use in serving.
75 def input_fn() function in function:build_parsing_serving_input_fn
102 def input_fn(): function in function:build_default_serving_input_fn
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| trainable.py | 33 input_fn=None,
45 The training input samples for fitting the model. If set, `input_fn`
53 If set, `input_fn` must be `None`. Note: For classification, label
57 input_fn: Input function returning a tuple of:
60 If input_fn is set, `x`, `y`, and `batch_size` must be `None`.
67 dimension of `x`. Must be `None` if `input_fn` is provided.
|
| /external/tensorflow/tensorflow/examples/learn/ |
| iris.py | 53 def input_fn(file_name, num_data, batch_size, is_training): function
54 """Creates an input_fn required by Estimator train/evaluate."""
69 """The input_fn."""
104 train_input_fn = input_fn(IRIS_TRAINING, num_training_data, batch_size=32,
106 classifier.train(input_fn=train_input_fn, steps=400)
109 test_input_fn = input_fn(IRIS_TEST, num_test_data, batch_size=32,
111 scores = classifier.evaluate(input_fn=test_input_fn)
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| structural_ensemble_test.py | 79 estimator.train(input_fn=train_input_fn, max_steps=1)
80 first_evaluation = estimator.evaluate(input_fn=eval_input_fn, steps=1)
81 estimator.train(input_fn=train_input_fn, max_steps=3)
82 second_evaluation = estimator.evaluate(input_fn=eval_input_fn, steps=1)
119 regressor.train(input_fn=train_input_fn, steps=1)
122 evaluation = regressor.evaluate(input_fn=eval_input_fn, steps=1)
126 regressor.predict(input_fn=predict_input_fn)
143 regressor.train(input_fn=train_input_fn, steps=1)
146 evaluation = regressor.evaluate(input_fn=eval_input_fn, steps=1)
149 regressor.predict(input_fn=predict_input_fn
[all...] |
