| /external/libvpx/libvpx/vp9/common/ |
| D | vp9_scale.c | 82 sf->predict[0][0][0] = vpx_convolve_copy;
83 sf->predict[0][0][1] = vpx_convolve_avg;
84 sf->predict[0][1][0] = vpx_convolve8_vert;
85 sf->predict[0][1][1] = vpx_convolve8_avg_vert;
86 sf->predict[1][0][0] = vpx_convolve8_horiz;
87 sf->predict[1][0][1] = vpx_convolve8_avg_horiz;
90 sf->predict[0][0][0] = vpx_scaled_vert;
91 sf->predict[0][0][1] = vpx_scaled_avg_vert;
92 sf->predict[0][1][0] = vpx_scaled_vert;
93 sf->predict[0][1][1] = vpx_scaled_avg_vert;
[all …]
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| /external/libvpx/libvpx/test/ |
| D | idct_test.cc | 36 predict = new Buffer<uint8_t>(4, 4, 3); in SetUp()
37 ASSERT_TRUE(predict != NULL); in SetUp()
38 ASSERT_TRUE(predict->Init()); in SetUp()
46 delete predict; in TearDown()
53 Buffer<uint8_t> *predict; member in __anondd905de80111::IDCTTest
60 predict->Set(0); in TEST_P()
63 ASM_REGISTER_STATE_CHECK(UUT(input->TopLeftPixel(), predict->TopLeftPixel(), in TEST_P()
64 predict->stride(), output->TopLeftPixel(), in TEST_P()
78 predict->Set(0); in TEST_P()
81 ASM_REGISTER_STATE_CHECK(UUT(input->TopLeftPixel(), predict->TopLeftPixel(), in TEST_P()
[all …]
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | gru_v2_test.py | 106 model.predict(x_train)
163 y_1 = gru_model.predict(x_train)
166 y_2 = gru_model.predict(x_train)
174 y_3 = cudnn_model.predict(x_train)
177 y_4 = cudnn_model.predict(x_train)
211 y_ref = model.predict(x)
216 y = cloned_model.predict(x)
236 y_1 = cpu_model.predict(x_train)
243 y_2 = gpu_model.predict(x_train)
255 y_3 = canonical_model.predict(x_train)
[all …]
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| D | convolutional_recurrent_test.py | 71 state = model.predict(inputs)
113 out1 = model.predict(np.ones_like(inputs))
118 out2 = model.predict(np.ones_like(inputs))
126 out3 = model.predict(np.ones_like(inputs))
131 out4 = model.predict(np.ones_like(inputs))
135 out5 = model.predict(np.ones_like(inputs))
194 reference_outputs = model.predict(test_inputs)
202 outputs = clone.predict(test_inputs)
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| D | lstm_v2_test.py | 259 state = model.predict(inputs)
277 model.predict(inputs)
330 y_1 = lstm_model.predict(x_train)
333 y_2 = lstm_model.predict(x_train)
339 y_3 = cudnn_model.predict(x_train)
342 y_4 = cudnn_model.predict(x_train)
437 y_ref = lstm_model.predict(x_train)
442 y = unified_lstm_model.predict(x_train)
470 model.predict(x_train)
501 y_ref = model.predict(x)
[all …]
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| D | gru_test.py | 105 gru_model.predict(x_train)
141 out1 = model.predict(np.ones((num_samples, timesteps)))
147 out2 = model.predict(np.ones((num_samples, timesteps)))
155 out3 = model.predict(np.ones((num_samples, timesteps)))
160 out4 = model.predict(np.ones((num_samples, timesteps)))
164 out5 = model.predict(np.ones((num_samples, timesteps)))
173 out6 = model.predict(left_padded_input)
180 out7 = model.predict(right_padded_input)
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| D | simplernn_test.py | 160 out1 = model.predict(np.ones((num_samples, timesteps)))
166 out2 = model.predict(np.ones((num_samples, timesteps)))
174 out3 = model.predict(np.ones((num_samples, timesteps)))
179 out4 = model.predict(np.ones((num_samples, timesteps)))
183 out5 = model.predict(np.ones((num_samples, timesteps)))
192 out6 = model.predict(left_padded_input)
199 out7 = model.predict(right_padded_input)
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| D | cudnn_recurrent_test.py | 92 state = model.predict(inputs)
119 out = model.predict(np.ones((num_samples, timesteps, input_size)))
215 out1 = model.predict(np.ones((num_samples, timesteps)))
221 out2 = model.predict(np.ones((num_samples, timesteps)))
229 out3 = model.predict(np.ones((num_samples, timesteps)))
234 out4 = model.predict(np.ones((num_samples, timesteps)))
238 out5 = model.predict(np.ones((num_samples, timesteps)))
313 self.assertAllClose(model.predict(inputs), cudnn_model.predict(inputs),
389 self.assertAllClose(model.predict(inputs), cudnn_model.predict(inputs),
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| D | merge_test.py | 48 out = model.predict([x1, x2, x3])
80 out = model.predict([x1, x2])
114 out = model.predict([x1, x2, x3])
128 out = model.predict([x1, x2])
142 out = model.predict([x1, x2])
156 out = model.predict([x1, x2])
171 out = model.predict([x1, x2])
203 out = model.predict([x1, x2])
215 out = model.predict([x1, x2])
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| D | lstm_test.py | 276 state = model.predict(inputs)
293 outputs = model.predict(inputs)
363 out1 = model.predict(np.ones((num_samples, timesteps)))
369 out2 = model.predict(np.ones((num_samples, timesteps)))
377 out3 = model.predict(np.ones((num_samples, timesteps)))
382 out4 = model.predict(np.ones((num_samples, timesteps)))
386 out5 = model.predict(np.ones((num_samples, timesteps)))
395 out6 = model.predict(left_padded_input)
402 out7 = model.predict(right_padded_input)
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| D | normalization_test.py | 104 out = model.predict(x)
124 out = model.predict(x)
265 out = model.predict(x)
326 x1 = model.predict(val_a)
328 x2 = model.predict(val_a)
336 x2 = model.predict(val_a)
343 x1 = model.predict(val_a)
345 x2 = model.predict(val_a)
382 out = model.predict(val_a)
399 out = model.predict(x)
[all …]
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| /external/webp/src/enc/ |
| D | predictor_enc.c | 150 static uint8_t NearLosslessComponent(uint8_t value, uint8_t predict, in NearLosslessComponent() argument
152 const int residual = (value - predict) & 0xff; in NearLosslessComponent()
153 const int boundary_residual = (boundary - predict) & 0xff; in NearLosslessComponent()
189 static uint32_t NearLossless(uint32_t value, uint32_t predict, in NearLossless() argument
197 return VP8LSubPixels(value, predict); in NearLossless()
205 a = NearLosslessDiff(value >> 24, predict >> 24); in NearLossless()
207 a = NearLosslessComponent(value >> 24, predict >> 24, 0xff, quantization); in NearLossless()
209 g = NearLosslessComponent((value >> 8) & 0xff, (predict >> 8) & 0xff, 0xff, in NearLossless()
214 new_green = ((predict >> 8) + g) & 0xff; in NearLossless()
221 (predict >> 16) & 0xff, 0xff - new_green, in NearLossless()
[all …]
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | estimator_input_test.py | 199 predictions = np.array(list(est2.predict(x=boston_input)))
215 predictions = np.array(list(est.predict(x=boston.data)))
233 predictions = np.array(list(est.predict(x=boston_input)))
250 predictions = est.predict(x=iris.data)
251 predictions_class = est.predict(x=iris.data, outputs=['class'])['class']
273 predictions = list(est.predict(x=iris_data))
274 predictions_class = list(est.predict(x=iris_data, outputs=['class']))
292 predictions = list(est.predict(x=iris.data))
309 predictions = list(est.predict(x=iris.data))
322 output = list(est.predict(input_fn=input_fn))
[all …]
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| D | dnn.py | 398 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None, member in DNNClassifier
428 return super(DNNClassifier, self).predict(
458 preds = super(DNNClassifier, self).predict(
493 preds = super(DNNClassifier, self).predict(
714 def predict(self, x=None, input_fn=None, batch_size=None, outputs=None, member in DNNRegressor
744 return super(DNNRegressor, self).predict(
774 preds = super(DNNRegressor, self).predict(
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| D | estimators_test.py | 71 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
111 prediction = next(estimator.predict(input_fn=input_fn, as_iterable=True))
157 estimator_with_fe_fn.predict(input_fn=input_fn, as_iterable=True))
160 estimator_without_fe_fn.predict(input_fn=input_fn, as_iterable=True))
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| /external/tensorflow/tensorflow/python/keras/saving/ |
| D | hdf5_format_test.py | 62 ref_y = model.predict(x)
65 y = model.predict(x)
79 y = model.predict(x)
88 y = model.predict(x)
92 y = model.predict(x)
97 y = model.predict(x)
247 ref_y = model.predict(x)
255 y = model.predict(x)
369 out = model.predict(x)
377 out2 = new_model.predict(x)
[all …]
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| D | saved_model_test.py | 69 ref_y = model.predict(x)
75 y = loaded_model.predict(x)
87 ref_y = model.predict(x)
93 y = loaded_model.predict(x)
111 ref_y = model.predict(x)
117 y = loaded_model.predict(x)
132 ref_y = model.predict(x)
138 y = loaded_model.predict(x)
154 ref_y = model.predict(x)
163 y = loaded_model.predict(x)
[all …]
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| /external/tensorflow/tensorflow/contrib/distribute/python/ |
| D | keras_test.py | 633 model.predict(inputs)
635 model.predict(inputs, steps=2)
637 model.predict(inputs, batch_size=8)
668 model.predict(inputs)
670 model.predict(inputs, steps=2)
672 model.predict(inputs, batch_size=8)
706 outs = model.predict(inputs, steps=1)
735 predict_ground_truth = cpu_model.predict(inputs)
738 model_with_ds_strategy.predict(inputs, batch_size=4, steps=3),
744 model_with_ds_strategy.predict(inputs, batch_size=4),
[all …]
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| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| D | estimator_test.py | 180 result_iter = classifier.predict(input_fn=_eval_input_fn)
276 model.predict(input_fn=_infer_ranking_train_input_fn)
340 result_iter = classifier.predict(input_fn=_eval_input_fn)
367 result_iter = classifier.predict(input_fn=_eval_input_fn)
394 result_iter = classifier.predict(input_fn=_eval_input_fn)
421 result_iter = model_upper.predict(input_fn=test_input_fn)
456 result_iter = model_upper.predict(input_fn=test_input_fn)
499 est.predict(input_fn=_eval_input_fn)
527 est.predict(input_fn=_infer_ranking_train_input_fn)
554 classifier.predict(input_fn=_eval_input_fn)
[all …]
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| /external/tensorflow/tensorflow/contrib/timeseries/examples/ |
| D | predict_test.py | 23 from tensorflow.contrib.timeseries.examples import predict
36 ) = predict.structural_ensemble_train_and_predict(_DATA_FILE)
49 upper_limit, lower_limit) = predict.ar_train_and_predict(_DATA_FILE)
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| /external/tensorflow/tensorflow/python/keras/wrappers/ |
| D | scikit_learn.py | 89 Sequential.fit, Sequential.predict, Sequential.predict_classes,
225 def predict(self, x, **kwargs): member in KerasClassifier
318 def predict(self, x, **kwargs): member in KerasRegressor
332 kwargs = self.filter_sk_params(Sequential.predict, kwargs)
333 return np.squeeze(self.model.predict(x, **kwargs))
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| /external/tensorflow/tensorflow/lite/models/smartreply/ops/ |
| D | predict.cc | 41 namespace predict { namespace
168 static TfLiteRegistration r = {predict::Init, predict::Free, predict::Prepare, in Register_PREDICT()
169 predict::Eval}; in Register_PREDICT()
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_dataset_test.py | 70 model.predict(iterator, steps=2)
110 model.predict(iterator, verbose=0)
183 model.predict(dataset, steps=2)
218 model.predict(dataset, batch_size=10, steps=2, verbose=0)
238 model.predict(dataset, verbose=0)
277 model.predict(predict_dataset_tuple, steps=1)
298 model.predict(predict_dataset_dict, steps=1)
320 model.predict(dataset, steps=2)
434 out = model.predict(dataset)
457 out = model.predict(dataset)
[all …]
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| /external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
| D | random_forest_test.py | 81 predictions = list(classifier.predict(input_fn=predict_input_fn))
104 predictions = list(regressor.predict(input_fn=predict_input_fn))
134 predictions = list(classifier.predict(input_fn=input_fn))
192 predictions = list(est.predict(input_fn=predict_input_fn))
219 predictions = list(regressor.predict(input_fn=predict_input_fn))
289 predictions = list(regressor.predict(input_fn=predict_input_fn))
320 predictions = list(classifier.predict(input_fn=input_fn))
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| /external/libaom/libaom/test/ |
| D | cfl_test.cc | 355 predict = ::testing::get<1>(this->GetParam())(tx_size); in SetUp()
361 cfl_predict_lbd_fn predict; member in __anon41cf28f70111::CFLPredictTest
368 predict(sub_luma_pels, chroma_pels, CFL_BUF_LINE, alpha_q3); in TEST_P()
386 predict(sub_luma_pels, chroma_pels, CFL_BUF_LINE, alpha_q3); in TEST_P()
401 predict = ::testing::get<1>(this->GetParam())(tx_size); in SetUp()
407 cfl_predict_hbd_fn predict; member in __anon41cf28f70111::CFLPredictHBDTest
415 predict(sub_luma_pels, chroma_pels, CFL_BUF_LINE, alpha_q3, bd); in TEST_P()
434 predict(sub_luma_pels, chroma_pels, CFL_BUF_LINE, alpha_q3, bd); in TEST_P()
|