/external/tensorflow/tensorflow/core/kernels/ |
H A D | xent_op_test.cc | 24 static Graph* Xent(int batch_size, int num_classes) { argument 26 Tensor logits(DT_FLOAT, TensorShape({batch_size, num_classes})); 28 Tensor labels(DT_FLOAT, TensorShape({batch_size, num_classes}));
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H A D | multinomial_op_test.cc | 27 static Graph* Multinomial(int batch_size, int num_classes, int num_samples) { argument 29 Tensor logits_t(DT_FLOAT, TensorShape({batch_size, num_classes}));
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H A D | sparse_xent_op_test.cc | 26 static Graph* SparseXent(int batch_size, int num_classes) { argument 28 Tensor logits(DT_FLOAT, TensorShape({batch_size, num_classes})); 30 Tensor labels(DT_INT64, TensorShape({batch_size})); 35 for (int i = 0; i < batch_size; ++i) {
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H A D | attention_ops.cc | 40 // Expect input tensor of rank 4 with dimensions (batch_size, height, width, 49 "input must be 4-dimensional (batch_size, height, width, depth)", 52 const int64 batch_size = input_shape.dim_size(0); variable 72 OP_REQUIRES(context, offsets.shape().dim_size(0) == batch_size, 88 offset_vec.reserve(batch_size); 89 for (int i = 0; i < batch_size; ++i) {
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H A D | cholesky_op.cc | 144 const int64 batch_size = input_reshaped.dimension(0); variable 146 dev_info.push_back(solver->GetDeviceLapackInfo(batch_size, "potrf")); 149 for (int batch = 0; batch < batch_size; ++batch) {
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H A D | conv_grad_ops.h | 233 int64 batch_size; member in struct:tensorflow::ConvBackpropDimensions
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H A D | softmax_op_functor.h | 31 // logits: dim: batch_size, num_classes. 32 // softmax: dims: batch_size, num_classes. 49 const int batch_size = logits.dimension(kBatchDim); local 56 Eigen::DSizes<int, 2> batch_by_one(batch_size, 1); 62 batch_by_one.set(0, batch_size);
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H A D | xent_op.h | 31 // logits: batch_size, num_classes. 32 // labels: batch_size, num_classes. 33 // scratch: temporary tensor, dims: batch_size, 1 34 // loss: output tensor for the loss, dims: batch_size. 35 // backprop: output tensor for the backprop, dims: batch_size, num_classes. 60 const int batch_size = logits.dimension(kBatchDim); local 69 batch_only[0] = batch_size; 71 batch_by_one[0] = batch_size; 79 batch_by_one.set(0, batch_size); 81 batch_only.set(0, batch_size); [all...] |
/external/tensorflow/tensorflow/core/ops/ |
H A D | candidate_sampling_ops.cc | 35 DimensionHandle batch_size = c->Dim(true_classes_shape, 0); local 39 c->set_output(1, c->Matrix(batch_size, num_true));
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
H A D | categorical_op.cc | 56 const int64 batch_size = logits_shape.dim_size(0); variable 62 {batch_size, num_samples, num_classes}};
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H A D | batchtospace_op.cc | 50 const int64 batch_size = input_shape[0]; local 67 ctx, batch_size % block_num_elems == 0, 68 errors::InvalidArgument("Input batch dimension (", batch_size, 73 reshaped_shape[block_rank] = batch_size / block_num_elems; 107 reshaped_permuted_shape[0] = batch_size / block_num_elems;
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H A D | spacetobatch_op.cc | 88 const int64 batch_size = input_shape[0]; local 90 reshaped_padded_shape[0] = batch_size; 138 output_shape[0] = batch_size * block_num_elems;
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/common/partitioners/ |
H A D | example_partitioner.cc | 28 const int64 batch_size = features.batch_size(); local 29 if (batch_size <= 0) { 51 boosted_trees::utils::ParallelFor(batch_size, desired_parallelism, 61 const int64 batch_size = features.batch_size(); local 62 if (batch_size <= 0) { 84 boosted_trees::utils::ParallelFor(batch_size, desired_parallelism,
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/models/ |
H A D | multiple_additive_trees.cc | 34 const int64 batch_size = features.batch_size(); local 35 if (batch_size <= 0) { 76 boosted_trees::utils::ParallelFor(batch_size, worker_threads->NumThreads(),
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/utils/ |
H A D | batch_features.h | 33 explicit BatchFeatures(int64 batch_size) : batch_size_(batch_size) {} argument 75 int64 batch_size() const { return batch_size_; }
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H A D | parallel_for.cc | 22 void ParallelFor(int64 batch_size, int64 desired_parallelism, argument 27 do_work(0, batch_size); 31 1, std::min(static_cast<int64>(desired_parallelism), batch_size)); 32 const int64 block_size = (batch_size + num_shards - 1) / num_shards; 34 const int num_shards_used = (batch_size + block_size - 1) / block_size; 36 for (int64 start = block_size; start < batch_size; start += block_size) { 37 auto end = std::min(start + block_size, batch_size); 45 do_work(0, std::min(block_size, batch_size));
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/external/tensorflow/tensorflow/contrib/cudnn_rnn/ops/ |
H A D | cudnn_rnn_ops_test.cc | 44 int batch_size = 3; local 48 std::vector<int> input_shape = {seq_length, batch_size, num_units}; 49 std::vector<int> input_h_shape = {num_layers * dir_count, batch_size, 51 std::vector<int> output_shape = {seq_length, batch_size,
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/external/tensorflow/tensorflow/contrib/lite/kernels/internal/ |
H A D | kernel_utils.cc | 22 int input_size, int num_units, int batch_size, 26 tensor_utils::VectorBatchVectorAssign(bias_ptr, num_units, batch_size, 30 input_weights_ptr, num_units, input_size, input_ptr_batch, batch_size, 35 batch_size, output_ptr_batch, /*result_stride=*/1); 38 output_ptr_batch, num_units * batch_size, activation, output_ptr_batch); 39 tensor_utils::VectorBatchVectorAssign(output_ptr_batch, num_units, batch_size, 20 RnnBatchStep(const float* input_ptr_batch, const float* input_weights_ptr, const float* recurrent_weights_ptr, const float* bias_ptr, int input_size, int num_units, int batch_size, TfLiteFusedActivation activation, float* hidden_state_ptr_batch, float* output_ptr_batch) argument
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/external/tensorflow/tensorflow/contrib/tpu/ops/ |
H A D | tpu_embedding_ops.cc | 247 int64 batch_size = config.batch_size(); local 252 c->set_output(table_id, c->Matrix(batch_size * num_features, width));
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/external/tensorflow/tensorflow/contrib/nearest_neighbor/kernels/ |
H A D | hyperplane_lsh_probes.cc | 105 int batch_size = products_tensor.dim_size(0); variable 109 TensorShape output_shape({batch_size, num_probes}); 125 batch_size, cost_per_unit, [&](int64 start, int64 end) {
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/external/tensorflow/tensorflow/core/kernels/data/ |
H A D | batch_dataset_op.cc | 34 int64 batch_size = 0; variable 36 ParseScalarArgument<int64>(ctx, "batch_size", &batch_size)); 38 ctx, batch_size > 0, 41 *output = new Dataset(ctx, batch_size, input); 47 Dataset(OpKernelContext* ctx, int64 batch_size, const DatasetBase* input) argument 48 : GraphDatasetBase(ctx), batch_size_(batch_size), input_(input) { 53 // then we could always report `batch_size` as the 0th dimension. 87 Node* batch_size = nullptr; variable 88 TF_RETURN_IF_ERROR(b->AddScalar(batch_size_, &batch_size)); [all...] |
/external/libdrm/intel/ |
H A D | test_decode.c | 78 size_t batch_size; local 80 read_file(batch_filename, &batch_ptr, &batch_size); 83 batch_size / 4); 97 size_t ref_size, batch_size; local 105 read_file(batch_filename, &batch_ptr, &batch_size); 120 batch_size / 4);
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/external/tensorflow/tensorflow/contrib/boosted_trees/lib/testutil/ |
H A D | batch_features_testutil.cc | 30 const int64 batch_size = static_cast<int64>(batch_features->batch_size()); local 36 for (int64 j = 0; j < batch_size; ++j) { 39 auto dense_tensor = Tensor(tensorflow::DT_FLOAT, {batch_size, 1}); 53 for (int64 k = 0; k < static_cast<int64>(density * batch_size) + 1; ++k) { 54 indices.insert(rng->Uniform64(batch_size)); 75 tensorflow::test::FillValues<int64>(&shape_tensor, {batch_size, 1});
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/external/tensorflow/tensorflow/contrib/lite/kernels/ |
H A D | softmax_test.cc | 80 const int batch_size = 2; local 88 SoftmaxOpModel m(batch_size, input_size, beta); 90 m.SetInput(0, input_buffer, input_buffer + input_size * batch_size); 94 std::unique_ptr<float[]> output_buffer(new float[input_size * batch_size]); 95 static tflite::Dims<4> input_dims = {{input_size, 1, 1, batch_size}, 102 output_buffer.get() + input_size * batch_size); 108 const int batch_size = 2; local 116 SoftmaxOpModel m(batch_size, input_size, beta); 118 m.SetInput(0, input_buffer, input_buffer + input_size * batch_size); 122 std::unique_ptr<float[]> output_buffer(new float[input_size * batch_size]); [all...] |
/external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
H A D | basic_decoder.py | 76 def batch_size(self): member in class:BasicDecoder 77 return self._helper.batch_size
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