| /external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
| D | extenders_test.py | 39 def input_fn(): function
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)
92 estimator.evaluate(input_fn=input_fn)
95 input_fn = get_input_fn(x=[[[0.]]], y=[[[1]]])
107 estimator.train(input_fn=input_fn)
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | linear_test.py | 82 def input_fn(): function
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
122 classifier.fit(input_fn=input_fn, steps=100)
123 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
124 classifier.fit(input_fn=input_fn, steps=200)
125 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
[all …]
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| D | svm_test.py | 33 def input_fn(): function
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
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
104 svm_classifier.fit(input_fn=input_fn, steps=30)
105 metrics = svm_classifier.evaluate(input_fn=input_fn, steps=1)
114 def input_fn(): function
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| D | 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)
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| D | debug_test.py | 63 def input_fn(): function
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))
[all …]
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| D | 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)
395 classifier.fit(input_fn=_input_fn, steps=50)
397 scores = classifier.evaluate(input_fn=_input_fn, steps=1)
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| D | estimators_test.py | 44 def input_fn(): function
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
110 estimator.fit(input_fn=input_fn, steps=1)
111 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
115 input_fn=input_fn,
125 def input_fn(): function
151 estimator_with_fe_fn.fit(input_fn=input_fn, steps=1)
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| D | composable_model_test.py | 122 def input_fn(): function
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
163 classifier.fit(input_fn=input_fn, steps=1000)
164 loss1 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
165 classifier.fit(input_fn=input_fn, steps=2000)
166 loss2 = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
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| D | kmeans_test.py | 73 def input_fn(self, member in KMeansTestBase
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)
176 input_fn=self.input_fn(batch_size=self.num_points), steps=1)
195 input_fn=self.input_fn(),
199 input_fn=self.input_fn(batch_size=self.num_points), steps=1)
207 kmeans.predict_cluster_idx(input_fn=self.input_fn(
213 input_fn=lambda: (constant_op.constant(points), None), steps=1)
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| D | dnn.py | 389 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None, argument
416 input_fn=input_fn,
421 input_fn=input_fn,
430 def predict_classes(self, x=None, input_fn=None, batch_size=None, argument
451 input_fn=input_fn,
465 input_fn=None, argument
486 input_fn=input_fn,
497 input_fn=None, argument
511 input_fn=input_fn or default_input_fn,
662 input_fn=None, argument
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| D | estimator.py | 92 def _verify_input_args(x, y, input_fn, feed_fn, batch_size): argument
94 if input_fn is None:
110 def _get_input_fn(x, y, input_fn, feed_fn, batch_size, shuffle=False, epochs=1): argument
128 _verify_input_args(x, y, input_fn, feed_fn, batch_size)
129 if input_fn is not None:
130 return input_fn, feed_fn
141 def infer_real_valued_columns_from_input_fn(input_fn): argument
157 features, _ = input_fn()
173 input_fn, _ = _get_input_fn(
174 x=x, y=None, input_fn=None, feed_fn=None, batch_size=None)
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| D | svm.py | 155 def predict_classes(self, x=None, input_fn=None, batch_size=None, argument
161 input_fn=input_fn,
172 def predict_proba(self, x=None, input_fn=None, batch_size=None, outputs=None, argument
178 input_fn=input_fn,
189 input_fn=None, default_batch_size=1, argument
195 input_fn=input_fn,
204 input_fn=None, argument
213 input_fn=input_fn or default_input_fn,
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| D | linear.py | 499 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None, argument
526 input_fn=input_fn,
531 input_fn=input_fn,
539 def predict_classes(self, x=None, input_fn=None, batch_size=None, argument
560 input_fn=input_fn,
571 def predict_proba(self, x=None, input_fn=None, batch_size=None, argument
591 input_fn=input_fn,
602 input_fn=None, argument
615 input_fn=input_fn or default_input_fn,
766 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None, argument
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| D | dnn_linear_combined.py | 707 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None, argument
734 input_fn=input_fn,
739 input_fn=input_fn,
747 def predict_classes(self, x=None, input_fn=None, batch_size=None, argument
768 input_fn=input_fn,
780 self, x=None, input_fn=None, batch_size=None, as_iterable=True): argument
799 input_fn=input_fn,
810 input_fn=None, argument
822 input_fn=input_fn or default_input_fn,
1019 input_fn=None, argument
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| D | dynamic_rnn_estimator_test.py | 271 def input_fn(): function
280 return input_fn
296 estimator_fn().fit(input_fn=get_input_fn(model_fn_lib.ModeKeys.TRAIN),
305 input_fn=get_input_fn(model_fn_lib.ModeKeys.INFER),
365 def input_fn(): function
386 return input_fn
405 sequence_estimator.fit(input_fn=train_input_fn, steps=train_steps)
408 input_fn=eval_input_fn, as_iterable=False)
425 def input_fn(): function
440 return input_fn
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| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/ |
| D | sdca_estimator_test.py | 36 def input_fn(): function
52 classifier.fit(input_fn=input_fn, steps=100)
53 loss = classifier.evaluate(input_fn=input_fn, steps=1)['loss']
61 def input_fn(): function
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
101 classifier.fit(input_fn=input_fn, steps=50)
102 metrics = classifier.evaluate(input_fn=input_fn, steps=1)
108 def input_fn(): function
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | gmm_test.py | 38 def input_fn(self, batch_size=None, points=None): member in 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),
114 gmm.fit(input_fn=self.input_fn(), steps=10)
115 score2 = gmm.score(input_fn=self.input_fn(batch_size=self.num_points),
124 gmm.fit(input_fn=self.input_fn(), steps=60)
133 input_fn=self.input_fn(points=points, batch_size=num_points)):
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| D | kmeans_test.py | 71 def input_fn(self, member in KMeansTestBase
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)
172 score2 = kmeans.score(input_fn=self.input_fn(batch_size=self.num_points))
191 input_fn=self.input_fn(),
194 score = kmeans.score(input_fn=self.input_fn(batch_size=self.num_points))
200 input_fn = self.input_fn(batch_size=num_points, points=points, num_epochs=1)
202 assignments = list(kmeans.predict_cluster_index(input_fn))
[all …]
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| D | wals_test.py | 82 def input_fn(self, np_matrix, batch_size, mode, member in WALSMatrixFactorizationTest
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)
280 input_fn = self.input_fn(np_matrix=self.input_matrix,
286 proj_input_fn = self.input_fn(
293 self._model.fit(input_fn=input_fn, steps=self.row_steps)
303 proj_input_fn = self.input_fn(
310 self._model.fit(input_fn=input_fn, steps=self.col_steps)
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| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| D | 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)
[all …]
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/ |
| D | pandas_io_test.py | 47 def callInputFnOnce(self, input_fn, session): argument
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)
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| /external/tensorflow/tensorflow/python/estimator/inputs/ |
| D | pandas_io_test.py | 50 def callInputFnOnce(self, input_fn, session): argument
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)
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| D | 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 …]
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| /external/tensorflow/tensorflow/python/estimator/ |
| D | training_test.py | 189 spec = training.TrainSpec(input_fn=lambda: 1)
190 self.assertEqual(1, spec.input_fn())
197 spec = training.TrainSpec(input_fn=lambda: 1, max_steps=2, hooks=hooks)
198 self.assertEqual(1, spec.input_fn())
204 training.TrainSpec(input_fn='invalid')
208 training.TrainSpec(input_fn=lambda: 1, max_steps=0)
212 training.TrainSpec(input_fn=lambda: 1, hooks=[_InvalidHook()])
220 spec = training.EvalSpec(input_fn=lambda: 1)
221 self.assertEqual(1, spec.input_fn())
235 input_fn=lambda: 1,
[all …]
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| /external/tensorflow/tensorflow/contrib/predictor/ |
| D | 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)
|