| /external/tensorflow/tensorflow/lite/delegates/nnapi/ |
| D | quant_lstm_sup.cc | 130 void DecomposeBiasTensor(const int32_t* biases, int bias_size, in DecomposeBiasTensor() argument
136 std::copy(biases, biases + bias_size, input_bias->begin()); in DecomposeBiasTensor()
139 std::copy(biases + bias_size, biases + 2 * bias_size, cell_bias->begin()); in DecomposeBiasTensor()
142 std::copy(biases + 2 * bias_size, biases + 3 * bias_size, in DecomposeBiasTensor()
146 std::copy(biases + 3 * bias_size, biases + 4 * bias_size, in DecomposeBiasTensor()
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| D | quant_lstm_sup_test.cc | 248 std::vector<int32_t> biases in TEST() local
263 DecomposeBiasTensor(biases.data(), 4, &input_bias, &cell_bias, &forget_bias, in TEST()
271 std::vector<int32_t> biases in TEST() local
286 DecomposeBiasTensor(biases.data(), 4, &input_bias, &cell_bias, &forget_bias, in TEST()
294 std::vector<int32_t> biases in TEST() local
309 DecomposeBiasTensor(biases.data(), 4, &input_bias, &cell_bias, &forget_bias, in TEST()
317 std::vector<int32_t> biases in TEST() local
332 DecomposeBiasTensor(biases.data(), 4, &input_bias, &cell_bias, &forget_bias, in TEST()
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| /external/tensorflow/tensorflow/lite/delegates/gpu/common/transformations/ |
| D | add_bias.cc | 37 tflite::gpu::Tensor<Linear, DataType::FLOAT32>* biases) { in FillBias() argument
38 if (biases->data.empty()) { in FillBias()
39 *biases = in FillBias()
43 if (biases->shape.v != output_channels) { in FillBias()
44 float last_value = biases->data.back(); in FillBias()
45 biases->shape.v = output_channels; in FillBias()
46 biases->data.resize(output_channels, last_value); in FillBias()
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| /external/tensorflow/tensorflow/lite/delegates/gpu/common/tasks/ |
| D | winograd_test_util.cc | 103 ::tflite::gpu::Tensor<Linear, DataType::FLOAT32> biases; in Winograd36To4x4Tile4x1Test()
104 biases.shape = Linear(1); in Winograd36To4x4Tile4x1Test()
105 biases.data.resize(biases.shape.DimensionsProduct()); in Winograd36To4x4Tile4x1Test()
106 for (int i = 0; i < biases.data.size(); ++i) { in Winograd36To4x4Tile4x1Test()
107 biases.data[i] = 0.0f; in Winograd36To4x4Tile4x1Test()
153 CreateWinograd36To4x4Tile4x1(env->GetGpuInfo(), op_def, biases); in Winograd36To4x4Tile4x1Test()
237 ::tflite::gpu::Tensor<Linear, DataType::FLOAT32> biases; in Winograd36To4x4Test()
238 biases.shape = Linear(1); in Winograd36To4x4Test()
239 biases.data.resize(biases.shape.DimensionsProduct()); in Winograd36To4x4Test()
240 for (int i = 0; i < biases.data.size(); ++i) { in Winograd36To4x4Test()
[all …]
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| D | depthwise_conv_3x3_stride_h2.h | 60 const tflite::gpu::Tensor<Linear, T>& biases,
65 const tflite::gpu::Tensor<Linear, S>& biases, absl::Span<T> dst);
73 const tflite::gpu::Tensor<Linear, T>& biases, bool weights_are_buffer) { in UploadWeightsAndBiases() argument
84 RearrangeWeightsAndBiasesData(weights, biases, in UploadWeightsAndBiases()
88 RearrangeWeightsAndBiasesData(weights, biases, in UploadWeightsAndBiases()
113 const tflite::gpu::Tensor<Linear, S>& biases, absl::Span<T> dst) { in RearrangeWeightsAndBiasesData() argument
137 bias_val[i] = dst_ch >= biases.shape.v ? 0.0f : biases.data[dst_ch]; in RearrangeWeightsAndBiasesData()
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| D | depthwise_conv_3x3.h | 57 const tflite::gpu::Tensor<Linear, T>& biases,
67 const tflite::gpu::Tensor<Linear, S>& biases, absl::Span<T> dst);
79 const tflite::gpu::Tensor<Linear, T>& biases, bool weights_are_buffer) { in UploadWeightsAndBiases() argument
90 RearrangeWeightsAndBiasesData(weights, biases, in UploadWeightsAndBiases()
94 RearrangeWeightsAndBiasesData(weights, biases, in UploadWeightsAndBiases()
119 const tflite::gpu::Tensor<Linear, S>& biases, absl::Span<T> dst) { in RearrangeWeightsAndBiasesData() argument
143 bias_val[i] = dst_ch >= biases.shape.v ? 0.0f : biases.data[dst_ch]; in RearrangeWeightsAndBiasesData()
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| D | conv_buffer_1x1.h | 88 const tflite::gpu::Tensor<Linear, T>& biases);
97 void UploadBiases(const tflite::gpu::Tensor<Linear, T>& biases);
108 const tflite::gpu::Tensor<Linear, T>& biases) { in UploadData() argument
110 UploadBiases(biases); in UploadData()
159 void ConvBuffer1x1::UploadBiases(const tflite::gpu::Tensor<Linear, T>& biases) { in UploadBiases() argument
163 int depth = AlignByN(biases.shape.v, 4 * conv_params_.block_size.z) / 4; in UploadBiases()
164 desc.UploadLinearData(biases, depth); in UploadBiases()
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| D | winograd.h | 120 const tflite::gpu::Tensor<Linear, DataType::FLOAT32>& biases);
125 const tflite::gpu::Tensor<Linear, DataType::FLOAT32>& biases);
149 const tflite::gpu::Tensor<Linear, DataType::FLOAT32>& biases);
161 const tflite::gpu::Tensor<Linear, DataType::FLOAT32>& biases);
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| D | convolution_transposed_thin.h | 56 const tflite::gpu::Tensor<Linear, T>& biases);
69 const tflite::gpu::Tensor<Linear, T>& biases) { in UploadData() argument
89 bias_value[i] = biases.data[i]; in UploadData()
97 bias_value[i] = biases.data[i]; in UploadData()
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| D | conv_powervr.h | 128 const tflite::gpu::Tensor<Linear, T>& biases);
207 const tflite::gpu::Tensor<Linear, T>& biases) { in UploadData() argument
209 UploadBias(biases); in UploadData()
218 tflite::gpu::Tensor<Linear, DataType::FLOAT32> biases; in UploadDataForWinograd4x4To6x6() local
219 biases.shape = Linear(weights.shape.o); in UploadDataForWinograd4x4To6x6()
220 biases.data.resize(weights.shape.o, 0.0f); in UploadDataForWinograd4x4To6x6()
221 UploadBias(biases); in UploadDataForWinograd4x4To6x6()
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | bidirectional_sequence_rnn_test.cc | 640 const std::initializer_list<float> biases = { variable
872 rnn.SetFwBias(biases); in TEST_P()
873 rnn.SetBwBias(biases); in TEST_P()
920 rnn.SetFwBias(biases); in TEST_P()
921 rnn.SetBwBias(biases); in TEST_P()
967 rnn.SetFwBias(biases); in TEST_P()
968 rnn.SetBwBias(biases); in TEST_P()
1008 rnn.SetFwBias(biases); in TEST()
1009 rnn.SetBwBias(biases); in TEST()
1054 rnn.SetFwBias(biases); in TEST()
[all …]
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| /external/skqp/src/gpu/gradients/ |
| D | GrUnrolledBinaryGradientColorizer.fp | 137 // The raster implementation also uses scales and biases, but since they must be calculated
140 SkPMColor4f biases[kMaxIntervals];
169 bias.store(biases + intervalCount);
177 biases[i] = SK_PMColor4fTRANSPARENT;
183 scales[6], scales[7], biases[0], biases[1], biases[2], biases[3], biases[4],
184 biases[5], biases[6], biases[7],
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| D | GrUnrolledBinaryGradientColorizer.cpp | 333 SkPMColor4f biases[kMaxIntervals]; in Make() local
362 bias.store(biases + intervalCount); in Make()
370 biases[i] = SK_PMColor4fTRANSPARENT; in Make()
376 scales[6], scales[7], biases[0], biases[1], biases[2], biases[3], biases[4], biases[5], in Make()
377 biases[6], biases[7], in Make()
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| /external/skia/src/gpu/gradients/ |
| D | GrUnrolledBinaryGradientColorizer.fp | 137 // The raster implementation also uses scales and biases, but since they must be calculated
140 SkPMColor4f biases[kMaxIntervals];
169 bias.store(biases + intervalCount);
177 biases[i] = SK_PMColor4fTRANSPARENT;
183 scales[6], scales[7], biases[0], biases[1], biases[2], biases[3], biases[4],
184 biases[5], biases[6], biases[7],
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| /external/tensorflow/tensorflow/compiler/mlir/tfr/examples/mnist/ |
| D | mnist_train.py | 81 self.biases = {
98 conv1 = gen_mnist_ops.new_conv2d(x, self.weights['f1'], self.biases['b1'],
108 self.biases['b2'], 1, 1, 1, 1, 'SAME',
121 self.biases['b3'], 'RELU')
124 self.biases['b4'])
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| /external/skia/src/gpu/gradients/generated/ |
| D | GrUnrolledBinaryGradientColorizer.cpp | 460 SkPMColor4f biases[kMaxIntervals]; in Make() local
489 bias.store(biases + intervalCount); in Make()
497 biases[i] = SK_PMColor4fTRANSPARENT; in Make()
511 biases[0], in Make()
512 biases[1], in Make()
513 biases[2], in Make()
514 biases[3], in Make()
515 biases[4], in Make()
516 biases[5], in Make()
517 biases[6], in Make()
[all …]
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_impl.py | 490 def relu_layer(x, weights, biases, name=None): argument
504 with ops.name_scope(name, "relu_layer", [x, weights, biases]) as name:
507 biases = ops.convert_to_tensor(biases, name="biases")
508 xw_plus_b = nn_ops.bias_add(math_ops.matmul(x, weights), biases)
1810 biases, argument
1875 weights + [biases, inputs, labels]):
1926 biases, all_ids, partition_strategy=partition_strategy)
1997 biases, argument
2087 biases,
2102 biases, argument
[all …]
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| D | nn_test.py | 583 biases = np.random.randn(num_classes).astype(np.float32)
590 sampled_w, sampled_b = weights[sampled], biases[sampled]
591 true_w, true_b = weights[labels], biases[labels]
609 return weights, biases, hidden_acts, sampled_vals, exp_logits, exp_labels
611 def _ShardTestEmbeddings(self, weights, biases, num_shards): argument
631 initializer=constant_op.constant(biases))
644 (weights, biases, hidden_acts, sampled_vals, exp_logits,
655 biases=constant_op.constant(biases),
680 (weights, biases, hidden_acts, sampled_vals, exp_logits,
691 biases=constant_op.constant(biases),
[all …]
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| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | minimize_loss_test.py | 115 weights, biases = [], []
119 biases.append(self.evaluate(layer.bias))
121 error = abs(numpy.add(numpy.squeeze(weights), numpy.squeeze(biases)) - 1)
153 weights, biases = [], []
158 biases.append(self.evaluate(layer.bias))
160 error = abs(numpy.add(numpy.squeeze(weights), numpy.squeeze(biases)) - 1)
510 weights, biases, losses = [], [], []
515 biases.append(self.evaluate(layer.bias))
521 numpy.add(numpy.squeeze(weights), numpy.squeeze(biases)) - 1)
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_CudnnRNNCanonicalToParamsV2.pbtxt | 10 biases.
18 biases: the canonical form of biases that can be used for saving
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| D | api_def_CudnnRNNParamsToCanonicalV2.pbtxt | 10 biases.
20 biases: the canonical form of biases that can be used for saving
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| D | api_def_CudnnRNNCanonicalToParams.pbtxt | 10 biases.
18 biases: the canonical form of biases that can be used for saving
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| D | api_def_CudnnRNNParamsToCanonical.pbtxt | 10 biases.
21 biases: the canonical form of biases that can be used for saving
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| /external/tensorflow/tensorflow/compiler/mlir/lite/transforms/ |
| D | default_quant_params.cc | 64 auto biases = TFL::GetOpQuantSpec(use.getOwner())->biases_params; in UsedAsBias() local
65 if (biases.find(use.getOperandNumber()) != biases.end()) return true; in UsedAsBias()
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| /external/tensorflow/tensorflow/core/profiler/g3doc/ |
| D | command_line.md | 229 pool_logit/biases (10, 10/10 params)
250 pool_logit/biases (10, 10/20 params)
251 pool_logit/biases/Momentum (10, 10/10 params)
289 entry.name = 'pool_logit/biases'
311 pool_logit/biases (10, 10/10 params)
335 pool_logit/biases (10, 10/20 params)
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