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Searched refs:TrainEvalFeatures (Results 1 – 22 of 22) sorted by relevance

/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/
Dinput_pipeline_test.py28 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
64 times = example.features.feature[TrainEvalFeatures.TIMES]
66 values = example.features.feature[TrainEvalFeatures.VALUES]
77 return {TrainEvalFeatures.TIMES: times,
78 TrainEvalFeatures.VALUES: values}
99 features[TrainEvalFeatures.TIMES].shape)
104 features[TrainEvalFeatures.TIMES][batch_position,
106 features[TrainEvalFeatures.TIMES][batch_position,
109 features[TrainEvalFeatures.VALUES].shape)
110 self.assertEqual("int64", features[TrainEvalFeatures.TIMES].dtype)
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Dinput_pipeline.py246 dataset_size = self._features[feature_keys.TrainEvalFeatures.TIMES].shape[1]
428 column_names=(feature_keys.TrainEvalFeatures.TIMES,
429 feature_keys.TrainEvalFeatures.VALUES),
455 if feature_keys.TrainEvalFeatures.TIMES not in column_names:
457 feature_keys.TrainEvalFeatures.TIMES))
458 if feature_keys.TrainEvalFeatures.VALUES not in column_names:
460 feature_keys.TrainEvalFeatures.VALUES))
467 if column_name == feature_keys.TrainEvalFeatures.TIMES) != 1:
470 "one is required.".format(feature_keys.TrainEvalFeatures.TIMES))
484 if column_name == feature_keys.TrainEvalFeatures.TIMES
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Dhead_test.py100 feature_keys.TrainEvalFeatures.TIMES:
102 feature_keys.TrainEvalFeatures.VALUES:
153 feature_keys.TrainEvalFeatures.TIMES: [[1, 2, 3], [7, 8, 9]],
154 feature_keys.TrainEvalFeatures.VALUES:
161 target = features[feature_keys.TrainEvalFeatures.VALUES][:, -1, 0]
203 feature_keys.TrainEvalFeatures.TIMES)):
205 features={feature_keys.TrainEvalFeatures.VALUES: [[[1.]]]},
213 feature_keys.TrainEvalFeatures.VALUES)):
215 features={feature_keys.TrainEvalFeatures.TIMES: [[1]]},
224 feature_keys.TrainEvalFeatures.TIMES)):
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Dar_model_test.py30 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
79 train_data = {TrainEvalFeatures.TIMES: time[0:split],
80 TrainEvalFeatures.VALUES: data[0:split]}
81 test_data = {TrainEvalFeatures.TIMES: time[split:],
82 TrainEvalFeatures.VALUES: data[split:]}
148 train_data_times = train_data[TrainEvalFeatures.TIMES]
149 train_data_values = train_data[TrainEvalFeatures.VALUES]
150 test_data_times = test_data[TrainEvalFeatures.TIMES]
151 test_data_values = test_data[TrainEvalFeatures.VALUES]
226 return ({TrainEvalFeatures.TIMES: [[1]],
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Dhead.py179 feature_keys.TrainEvalFeatures.TIMES,
183 if name == feature_keys.TrainEvalFeatures.VALUES:
239 feature_keys.TrainEvalFeatures.TIMES,
240 feature_keys.TrainEvalFeatures.VALUES))
302 if feature_keys.TrainEvalFeatures.VALUES not in features:
304 feature_keys.TrainEvalFeatures.VALUES))
324 feature_keys.TrainEvalFeatures.VALUES,
403 if feature_keys.TrainEvalFeatures.TIMES not in features:
405 feature_keys.TrainEvalFeatures.TIMES))
406 if feature_keys.TrainEvalFeatures.VALUES not in features:
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Destimators.py168 key=feature_keys.TrainEvalFeatures.TIMES, dtype=dtypes.int64)
170 key=feature_keys.TrainEvalFeatures.VALUES, dtype=values_input_dtype,
179 if key == feature_keys.TrainEvalFeatures.VALUES:
199 features[feature_keys.TrainEvalFeatures.TIMES] = array_ops.squeeze(
200 features[feature_keys.TrainEvalFeatures.TIMES], axis=-1)
201 features[feature_keys.TrainEvalFeatures.VALUES] = math_ops.cast(
202 features[feature_keys.TrainEvalFeatures.VALUES],
207 features[feature_keys.TrainEvalFeatures.TIMES])[0],
238 name=feature_keys.TrainEvalFeatures.TIMES,
241 placeholders[feature_keys.TrainEvalFeatures.TIMES] = time_placeholder
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Dmodel.py28 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
202 batch_size=array_ops.shape(features[TrainEvalFeatures.TIMES])[0])
543 outputs["observed"] = features[TrainEvalFeatures.VALUES]
548 prediction_times=features[TrainEvalFeatures.TIMES])
567 TrainEvalFeatures.TIMES,
568 TrainEvalFeatures.VALUES]}
609 times = math_ops.cast(features[TrainEvalFeatures.TIMES], dtype=dtypes.int64)
610 values = math_ops.cast(features[TrainEvalFeatures.VALUES], dtype=self.dtype)
616 if key not in [TrainEvalFeatures.TIMES,
617 TrainEvalFeatures.VALUES]})
Dstate_management_test.py71 times = features[feature_keys.TrainEvalFeatures.TIMES]
72 values = features[feature_keys.TrainEvalFeatures.VALUES]
107 feature_keys.TrainEvalFeatures.TIMES: times,
108 feature_keys.TrainEvalFeatures.VALUES: values
266 outputs["observed"] = features[feature_keys.TrainEvalFeatures.VALUES]
271 prediction_times=features[feature_keys.TrainEvalFeatures.TIMES])
282 features[feature_keys.TrainEvalFeatures.VALUES])
Dar_model.py26 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
515 if key not in [TrainEvalFeatures.TIMES,
516 TrainEvalFeatures.VALUES,
668 times = math_ops.cast(features[TrainEvalFeatures.TIMES], dtypes.int64)
669 values = math_ops.cast(features[TrainEvalFeatures.VALUES], dtype=self.dtype)
687 times_feature=TrainEvalFeatures.TIMES,
756 times = features[TrainEvalFeatures.TIMES]
760 if key not in [TrainEvalFeatures.TIMES,
761 TrainEvalFeatures.VALUES,
784 times.get_shape(), TrainEvalFeatures.TIMES))
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Dtest_utils.py24 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
64 times = features[TrainEvalFeatures.TIMES]
125 feature_dict[TrainEvalFeatures.VALUES] = math_ops.cast(
126 feature_dict[TrainEvalFeatures.VALUES], generative_model.dtype)
Dstate_management.py189 feature_keys.TrainEvalFeatures.VALUES]
194 prediction_times=features[feature_keys.TrainEvalFeatures.TIMES])
232 times = features[feature_keys.TrainEvalFeatures.TIMES]
Destimators_test.py61 feature_keys.TrainEvalFeatures.TIMES: times,
62 feature_keys.TrainEvalFeatures.VALUES: values,
248 feature_keys.TrainEvalFeatures.TIMES: times,
249 feature_keys.TrainEvalFeatures.VALUES: values,
Dfeature_keys.py46 class TrainEvalFeatures(Times, Values): class
Dmath_utils_test.py25 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
289 features = {TrainEvalFeatures.TIMES: times,
290 TrainEvalFeatures.VALUES: values}
Dmath_utils.py29 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
719 if (TrainEvalFeatures.TIMES in features
720 and TrainEvalFeatures.VALUES in features):
721 times = features[TrainEvalFeatures.TIMES]
722 values = features[TrainEvalFeatures.VALUES]
/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/
Dvarma_test.py24 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
44 TrainEvalFeatures.TIMES: constant_op.constant([[1, 2]]),
45 TrainEvalFeatures.VALUES: constant_op.constant([[[1.], [2.]]])
62 TrainEvalFeatures.TIMES: constant_op.constant([[1, 2]]),
63 TrainEvalFeatures.VALUES: constant_op.constant(
84 TrainEvalFeatures.TIMES: constant_op.constant([[1, 2]]),
85 TrainEvalFeatures.VALUES: constant_op.constant([[[1.], [2.]]])},
Dstate_space_model_test.py92 feature_keys.TrainEvalFeatures.TIMES:
94 feature_keys.TrainEvalFeatures.VALUES:
110 feature_keys.TrainEvalFeatures.TIMES:
112 feature_keys.TrainEvalFeatures.VALUES:
132 feature_keys.TrainEvalFeatures.TIMES: times,
133 feature_keys.TrainEvalFeatures.VALUES: values
136 times = features[feature_keys.TrainEvalFeatures.TIMES]
137 values = features[feature_keys.TrainEvalFeatures.VALUES]
140 feature_keys.TrainEvalFeatures.TIMES: times,
141 feature_keys.TrainEvalFeatures.VALUES: values
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Dstructural_ensemble_test.py28 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
47 return {TrainEvalFeatures.TIMES: numpy.reshape(time, [1, -1]),
48 TrainEvalFeatures.VALUES: numpy.reshape(
113 features = {TrainEvalFeatures.TIMES: times,
114 TrainEvalFeatures.VALUES: values,
138 features = {TrainEvalFeatures.TIMES: times,
139 TrainEvalFeatures.VALUES: values}
Dstate_space_model.py31 from tensorflow.contrib.timeseries.python.timeseries.feature_keys import TrainEvalFeatures
833 return {TrainEvalFeatures.TIMES: times,
834 TrainEvalFeatures.VALUES: observations}
/external/tensorflow/tensorflow/contrib/timeseries/examples/
Dmultivariate.py54 column_names=((tf.contrib.timeseries.TrainEvalFeatures.TIMES,)
55 + (tf.contrib.timeseries.TrainEvalFeatures.VALUES,) * 5))
88 tf.contrib.timeseries.TrainEvalFeatures.TIMES: current_prediction[
90 tf.contrib.timeseries.TrainEvalFeatures.VALUES: next_sample[
Dknown_anomaly.py105 column_names=(tf.contrib.timeseries.TrainEvalFeatures.TIMES,
106 tf.contrib.timeseries.TrainEvalFeatures.VALUES,
Dlstm.py210 column_names=((tf.contrib.timeseries.TrainEvalFeatures.TIMES,)
211 + (tf.contrib.timeseries.TrainEvalFeatures.VALUES,) * 5