| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | partial_batch_padding_handler.py | 95 prediction = np.take(prediction_result,
99 if prediction.shape[0] == 1:
100 prediction = np.squeeze(prediction, axis=0)
101 return prediction
106 prediction = prediction_result[i]
107 prediction = np.take(prediction, np.nonzero(
108 padding_mask[:len(prediction)]), axis=0)
109 predictions.append(np.squeeze(prediction))
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| /external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
| D | bidirectional_sequence_rnn_test.py | 123 prediction = tf.matmul(output, out_weights) + out_bias
124 output_class = tf.nn.softmax(prediction, name="OUTPUT_CLASS")
126 return x, prediction, output_class
128 def trainModel(self, x, prediction, output_class, sess): argument
133 tf.nn.softmax_cross_entropy_with_logits(logits=prediction, labels=y))
161 x, prediction, output_class = self.buildModel(
167 return x, prediction, output_class, new_sess
214 x, prediction, output_class = self.buildModel(
216 self.trainModel(x, prediction, output_class, sess)
219 x, prediction, output_class, new_sess = self.saveAndRestoreModel(
[all …]
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| D | unidirectional_sequence_rnn_test.py | 91 prediction = tf.matmul(outputs[-1], out_weights) + out_bias
92 output_class = tf.nn.softmax(prediction, name="OUTPUT_CLASS")
94 return x, prediction, output_class
96 def trainModel(self, x, prediction, output_class, sess): argument
101 tf.nn.softmax_cross_entropy_with_logits(logits=prediction, labels=y))
139 x, prediction, output_class = self.buildModel(rnn_layer, is_dynamic_rnn)
144 return x, prediction, output_class, new_sess
186 x, prediction, output_class = self.buildModel(
188 self.trainModel(x, prediction, output_class, sess)
191 x, prediction, output_class, new_sess = self.saveAndRestoreModel(
[all …]
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| D | unidirectional_sequence_lstm_test.py | 95 prediction = tf.matmul(outputs[-1], out_weights) + out_bias
96 output_class = tf.nn.softmax(prediction, name="OUTPUT_CLASS")
98 return x, prediction, output_class
100 def trainModel(self, x, prediction, output_class, sess): argument
105 tf.nn.softmax_cross_entropy_with_logits(logits=prediction, labels=y))
127 x, prediction, output_class = self.buildModel(lstm_layer, is_dynamic_rnn)
132 return x, prediction, output_class, new_sess
178 x, prediction, output_class = self.buildModel(
180 self.trainModel(x, prediction, output_class, sess)
183 x, prediction, output_class, new_sess = self.saveAndRestoreModel(
[all …]
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| D | bidirectional_sequence_lstm_test.py | 104 prediction = tf.matmul(output, out_weights) + out_bias
105 output_class = tf.nn.softmax(prediction, name="OUTPUT_CLASS")
107 return x, prediction, output_class
109 def trainModel(self, x, prediction, output_class, sess): argument
114 tf.nn.softmax_cross_entropy_with_logits(logits=prediction, labels=y))
137 x, prediction, output_class = self.buildModel(fw_lstm_layer, bw_lstm_layer,
143 return x, prediction, output_class, new_sess
193 x, prediction, output_class = self.buildModel(self.buildLstmLayer(),
195 self.trainModel(x, prediction, output_class, sess)
198 x, prediction, output_class, new_sess = self.saveAndRestoreModel(
[all …]
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| D | metric_spec_test.py | 47 def _fn2(prediction, label, weight=None): argument
48 self.assertEqual("p1_value", prediction)
53 def _fn3(prediction, target, weight=None): argument
54 self.assertEqual("p1_value", prediction)
201 def _fn2(prediction, label): argument
202 self.assertEqual("p1_value", prediction)
206 def _fn3(prediction, target): argument
207 self.assertEqual("p1_value", prediction)
374 def _fn1(prediction, weight=None): argument
375 del prediction, weight
[all …]
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| /external/libavc/common/arm/ |
| D | ih264_intra_pred_luma_4x4_a9q.s | 26 @* Contains function definitions for intra 4x4 Luma prediction .
62 @* Perform Intra prediction for luma_4x4 mode:vertical
65 @* Perform Intra prediction for luma_4x4 mode:vertical ,described in sec 8.3.1.2.1
135 @* Perform Intra prediction for luma_4x4 mode:horizontal
138 @* Perform Intra prediction for luma_4x4 mode:horizontal ,described in sec 8.3.1.2.2
217 @* Perform Intra prediction for luma_4x4 mode:DC
220 @* Perform Intra prediction for luma_4x4 mode:DC ,described in sec 8.3.1.2.3
356 @* Perform Intra prediction for luma_4x4 mode:Diagonal_Down_Left
359 @* Perform Intra prediction for luma_4x4 mode:Diagonal_Down_Left ,described in sec 8.3.1.2.4
438 @* Perform Intra prediction for luma_4x4 mode:Diagonal_Down_Right
[all …]
|
| D | ih264_intra_pred_luma_8x8_a9q.s | 26 @* Contains function definitions for intra 8x8 Luma prediction .
67 @* Reference sample filtering process for Intra_8x8 sample prediction
70 @* Perform Reference sample filtering process for Intra_8x8 sample prediction ,described in sec 8.…
152 @* Perform Intra prediction for luma_8x8 mode:vertical
155 @* Perform Intra prediction for luma_8x8 mode:vertical ,described in sec 8.3.2.2.2
225 @* Perform Intra prediction for luma_8x8 mode:horizontal
228 @* Perform Intra prediction for luma_8x8 mode:horizontal ,described in sec 8.3.2.2.2
305 @* Perform Intra prediction for luma_8x8 mode:DC
308 @* Perform Intra prediction for luma_8x8 mode:DC ,described in sec 8.3.2.2.3
416 @* Perform Intra prediction for luma_8x8 mode:Diagonal_Down_Left
[all …]
|
| D | ih264_intra_pred_luma_16x16_a9q.s | 26 @* Contains function definitions for intra 16x16 Luma prediction .
66 @* Perform Intra prediction for luma_16x16 mode:vertical
69 @* Perform Intra prediction for luma_16x16 mode:Vertical ,described in sec 8.3.3.1
147 @* Perform Intra prediction for luma_16x16 mode:horizontal
150 @* Perform Intra prediction for luma_16x16 mode:horizontal ,described in sec 8.3.3.2
225 @* Perform Intra prediction for luma_16x16 mode:DC
228 @* Perform Intra prediction for luma_16x16 mode:DC ,described in sec 8.3.3.3
349 @* Perform Intra prediction for luma_16x16 mode:PLANE
352 @* Perform Intra prediction for luma_16x16 mode:PLANE ,described in sec 8.3.3.4
|
| D | ih264_intra_pred_chroma_a9q.s | 26 @* Contains function definitions for intra chroma prediction .
65 @* Perform Intra prediction for chroma_8x8 mode:DC
68 @* Perform Intra prediction for chroma_8x8 mode:DC ,described in sec 8.3.4.1
197 @* Perform Intra prediction for chroma_8x8 mode:Horizontal
200 @* Perform Intra prediction for chroma_8x8 mode:Horizontal ,described in sec 8.3.4.2
273 @* Perform Intra prediction for chroma_8x8 mode:vertical
276 @*Perform Intra prediction for chroma_8x8 mode:vertical ,described in sec 8.3.4.3
345 @* Perform Intra prediction for chroma_8x8 mode:PLANE
348 @* Perform Intra prediction for chroma_8x8 mode:PLANE ,described in sec 8.3.4.4
|
| /external/python/google-api-python-client/samples/prediction/ |
| D | README | 1 Before you can run the prediction sample prediction.py, you must load some csv
7 api: prediction
|
| /external/tensorflow/tensorflow/lite/examples/label_image/ |
| D | get_top_n_impl.h | 30 void get_top_n(T* prediction, int prediction_size, size_t num_results, in get_top_n() argument
42 value = prediction[i]; in get_top_n()
44 value = prediction[i] / 255.0; in get_top_n()
|
| /external/v8/src/ |
| D | handler-table.cc | 109 CatchPrediction prediction) { in SetRangeHandler() argument
111 HandlerPredictionField::encode(prediction); in SetRangeHandler()
165 CatchPrediction prediction = GetRangePrediction(i); in LookupRange() local
175 if (prediction_out) *prediction_out = prediction; in LookupRange()
201 CatchPrediction prediction = GetRangePrediction(i); in HandlerTableRangePrint() local
204 << " (prediction=" << prediction << ", data=" << handler_data << ")\n"; in HandlerTableRangePrint()
|
| /external/arm-neon-tests/ |
| D | InitCache.s | 5 ; and program flow prediction
39 ; Cortex-A8 program flow prediction
43 ORR r0, r0, #(0x1 <<11) ; Enable all forms of branch prediction
44 ;BIC r0, r0, #(0x1 << 11) ; Disable all forms of branch prediction
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | target_column_test.py | 35 prediction = constant_op.constant([[1.], [1.], [3.]])
38 5. / 3, sess.run(target_column.loss(prediction, labels, {})))
45 prediction = constant_op.constant([[1.], [1.], [3.]])
49 sess.run(target_column.loss(prediction, labels, features)),
53 sess.run(target_column.training_loss(prediction, labels, features)),
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | estimator_input_test.py | 113 prediction, loss = (models.linear_regression_zero_init(features, labels))
119 return prediction, loss, train_op
129 prediction, loss = (models.linear_regression_zero_init(features, labels))
135 return prediction, loss, train_op
142 prediction, loss = (models.linear_regression_zero_init(features, labels))
149 mode=mode, predictions=prediction, loss=loss, train_op=train_op)
156 prediction, loss = (models.logistic_regression_zero_init(features, labels))
163 'class': math_ops.argmax(prediction, 1),
164 'prob': prediction
|
| D | estimators_test.py | 71 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
73 self.assertEqual(9., prediction)
111 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
113 self.assertEqual(9., prediction)
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| D | ar_model.py | 460 prediction = prediction_ops["mean"]
465 math_utils.normal_log_prob(targets, sigma, prediction))
469 math_ops.squared_difference(prediction, targets))
697 prediction = prediction_ops["mean"]
701 targets.get_shape().assert_is_compatible_with(prediction.get_shape())
714 prediction = self._scale_back_data(prediction)
722 predictions={"mean": prediction, "covariance": covariance,
963 prediction = prediction_ops["mean"]
968 log_prob = math_utils.normal_log_prob(targets, anomaly_sigma, prediction)
972 log_prob = math_utils.cauchy_log_prob(targets, anomaly_scale, prediction)
[all …]
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| /external/tensorflow/tensorflow/core/kernels/boosted_trees/ |
| D | boosted_trees.proto | 159 // prediction path 3) Leaf node IDs.
161 // Return the logits and associated feature splits across prediction paths for
163 // compute DFCs in Python, by subtracting each child prediction from its
164 // parent prediction and associating this change with its respective feature
169 // TODO(crawles): return 2) Node IDs for ensemble prediction path 3) Leaf node
|
| /external/tensorflow/tensorflow/contrib/timeseries/examples/ |
| D | lstm.py | 142 state_from_time, prediction, exogenous, lstm_state = state
151 (prediction - transformed_values) ** 2, axis=-1)
182 state_from_time, prediction, _, lstm_state = state
183 return (state_from_time, prediction,
|
| /external/v8/src/interpreter/ |
| D | handler-table-builder.cc | 61 int handler_id, HandlerTable::CatchPrediction prediction) { in SetPrediction() argument
62 entries_[handler_id].catch_prediction_ = prediction; in SetPrediction()
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
| D | ops_test.py | 42 prediction, loss = ops.softmax_classifier(features, labels, weights,
44 self.assertEqual(prediction.get_shape()[1], 2)
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_InTopK.pbtxt | 30 prediction for the target class is among the top `k` predictions among
33 same prediction value and straddle the top-`k` boundary, all of those
|
| D | api_def_InTopKV2.pbtxt | 30 prediction for the target class is among the top `k` predictions among
33 same prediction value and straddle the top-`k` boundary, all of those
|
| D | api_def_BoostedTreesTrainingPredict.pbtxt | 8 tree of prediction.
15 node of prediction.
|