/external/tensorflow/tensorflow/core/kernels/ |
D | substr_op.cc | 144 auto input = input_tensor.shaped<string, 1>(bcast.x_reshape()); in Compute() 145 auto output = output_tensor->shaped<string, 1>(bcast.result_shape()); in Compute() 146 auto pos_shaped = pos_tensor.shaped<T, 1>(bcast.y_reshape()); in Compute() 147 auto len_shaped = len_tensor.shaped<T, 1>(bcast.y_reshape()); in Compute() 154 input_buffer.shaped<string, 1>(bcast.result_shape()); in Compute() 164 pos_buffer.shaped<T, 1>(bcast.result_shape())); in Compute() 174 len_buffer.shaped<T, 1>(bcast.result_shape())); in Compute() 207 auto input = input_tensor.shaped<string, 2>(bcast.x_reshape()); in Compute() 208 auto output = output_tensor->shaped<string, 2>(bcast.result_shape()); in Compute() 209 auto pos_shaped = pos_tensor.shaped<T, 2>(bcast.y_reshape()); in Compute() [all …]
|
D | broadcast_to_op.h | 57 device, output_tensor.template shaped<T, NDIMS>(bcast.result_shape()), in ReshapeAndBCast() 58 input_tensor.template shaped<T, NDIMS>(bcast.x_reshape()), in ReshapeAndBCast() 62 device, output_tensor.template shaped<T, NDIMS>(bcast.result_shape()), in ReshapeAndBCast() 63 input_tensor.template shaped<T, NDIMS>(bcast.x_reshape()), in ReshapeAndBCast()
|
D | adjust_contrast_op.cc | 81 context->eigen_device<Device>(), input.shaped<T, 4>(shape), in Compute() 83 max_value.scalar<float>(), mean_values.shaped<float, 4>(shape), in Compute() 84 output->shaped<float, 4>(shape)); in Compute() 216 auto input_data = input->shaped<float, 3>({batch, image_size, channels}); in DoCompute() 218 auto output_data = output->shaped<float, 3>({batch, image_size, channels}); in DoCompute() 416 context->eigen_device<GPUDevice>(), options.input->shaped<T, 4>(shape), in DoCompute() 417 options.factor->scalar<float>(), options.output->shaped<T, 4>(shape)); in DoCompute() 446 options.input->shaped<float, 4>(shape), options.factor->scalar<float>(), in DoCompute() 447 options.output->shaped<float, 4>(shape)); in DoCompute()
|
D | lookup_table_op.cc | 346 empty_key_input->template shaped<K, 2>({1, key_shape_.num_elements()}), in MutableDenseHashTable() 357 deleted_key_hash_ = HashKey(deleted_key_input->template shaped<K, 2>( in MutableDenseHashTable() 364 empty_key_.AccessTensor(ctx)->template shaped<K, 2>({1, key_size}); in MutableDenseHashTable() 366 deleted_key_.AccessTensor(ctx)->template shaped<K, 2>({1, key_size}); in MutableDenseHashTable() 395 const auto key_matrix = key.shaped<K, 2>({num_elements, key_size}); in Find() 396 auto value_matrix = value->shaped<V, 2>({num_elements, value_size}); in Find() 405 empty_key_.AccessTensor(ctx)->template shaped<K, 2>({1, key_size}); in Find() 407 deleted_key_.AccessTensor(ctx)->template shaped<K, 2>({1, key_size}); in Find() 502 empty_key_.AccessTensor(ctx)->template shaped<K, 2>( in ImportValues() 505 deleted_key_.AccessTensor(ctx)->template shaped<K, 2>( in ImportValues() [all …]
|
D | betainc_op.cc | 94 auto a_value = a.shaped<T, NDIM>(a_shaper.x_reshape()); \ in Compute() 95 auto b_value = b.shaped<T, NDIM>(b_shaper.x_reshape()); \ in Compute() 96 auto x_value = x.shaped<T, NDIM>(x_shaper.x_reshape()); \ in Compute() 101 output->shaped<T, NDIM>(a_shaper.y_reshape())); \ in Compute()
|
D | cwise_ops_common.h | 125 eigen_device, out->shaped<Tout, 2>(bcast->result_shape()), in Compute() 126 in0.template shaped<Tin, 2>(bcast->x_reshape()), in Compute() 128 in1.template shaped<Tin, 2>(bcast->y_reshape()), in Compute() 132 eigen_device, out->shaped<Tout, 3>(bcast->result_shape()), in Compute() 133 in0.template shaped<Tin, 3>(bcast->x_reshape()), in Compute() 135 in1.template shaped<Tin, 3>(bcast->y_reshape()), in Compute() 139 eigen_device, out->shaped<Tout, 4>(bcast->result_shape()), in Compute() 140 in0.template shaped<Tin, 4>(bcast->x_reshape()), in Compute() 142 in1.template shaped<Tin, 4>(bcast->y_reshape()), in Compute() 146 eigen_device, out->shaped<Tout, 5>(bcast->result_shape()), in Compute() [all …]
|
D | split_op.cc | 239 input.shaped<T, 2>({split_dim_size, suffix_dim_size}); in Compute() 244 return result->shaped<T, 2>({split_size, suffix_dim_size}); in Compute() 251 auto input_reshaped = input.shaped<T, 3>( in Compute() 258 return result->shaped<T, 3>( in Compute() 363 input.shaped<T, 3>({prefix_dim_size, split_dim_size, suffix_dim_size}); in Compute() 385 auto result_shaped = result->shaped<T, 3>( in Compute()
|
D | split_v_op.cc | 301 input.shaped<T, 2>({split_dim_size, suffix_dim_size}); in Compute() 306 return result->shaped<T, 2>({split_size, suffix_dim_size}); in Compute() 313 auto input_reshaped = input.shaped<T, 3>( in Compute() 320 return result->shaped<T, 3>( in Compute() 411 auto input_reshaped = input.shaped<T, 2>( in Compute() 427 auto result_shaped = result->shaped<T, 2>( in Compute()
|
D | lrn_op.cc | 97 auto in_shaped = in.shaped<T, 2>({nodes * batch, depth}); in launch() 104 auto out_shaped = output->shaped<T, 2>({nodes * batch, depth}); in launch() 325 auto grads_shaped = in_grads.shaped<T, 2>({nodes * batch, depth}); in launch() 326 auto in_shaped = in_image.shaped<T, 2>({nodes * batch, depth}); in launch() 327 auto activations = out_image.shaped<T, 2>({nodes * batch, depth}); in launch() 329 auto out_shaped = output->shaped<T, 2>({nodes * batch, depth}); in launch()
|
D | reduction_ops_common.h | 106 return out->shaped<T, N>(out_reshape_); 112 return data.shaped<T, N>(data_reshape_); 231 const_shuffled.shaped<T, 2>({unreduced, reduced}),
|
D | xent_op.cc | 92 logits_in.template shaped<T, 2>(bcast.x_reshape()), in Compute() 93 labels_in.template shaped<T, 2>(bcast.y_reshape()), in Compute()
|
D | gather_op.cc | 106 params.shaped<T, 3>({outer_size, gather_dim_size, inner_size}); in Compute() 108 auto out_flat = out->shaped<T, 3>({outer_size, N, inner_size}); in Compute()
|
D | unpack_op.cc | 107 input.shaped<T, 2>({before_dim, axis_dim * after_dim}); in Compute() 115 auto output_shaped = output->shaped<T, 2>({before_dim, after_dim}); in Compute()
|
D | pack_op.cc | 105 output->shaped<T, 2>({before_dim, after_dim * axis_dim}); in Compute() 113 values[i].shaped<T, 2>({before_dim, after_dim}))); in Compute()
|
D | mkl_lrn_op.cc | 229 auto in_shaped = input.shaped<T, 2>({nodes * batch, depth}); in MklDefaultToEigen() 253 auto out_shaped = output_dnn_data->shaped<T, 2>({nodes * batch, depth}); in MklDefaultToEigen() 561 input_gradient_tensor.shaped<T, 2>({nodes * batch, depth}); in MklDefaultToEigen() 563 auto in_shaped = orig_input_tensor.shaped<T, 2>({nodes * batch, depth}); in MklDefaultToEigen() 564 auto activations = orig_output_tensor.shaped<T, 2>({nodes * batch, depth}); in MklDefaultToEigen() 574 auto out_shaped = output_dnn_data->shaped<T, 2>({nodes * batch, depth}); in MklDefaultToEigen()
|
D | list_kernels.h | 149 t.shaped<T, 2>({1, t.NumElements()}))); in Compute() 162 const_cast<const Tensor&>(zeros).shaped<T, 2>( in Compute() 166 auto output_flat = output->shaped<T, 2>({1, output->NumElements()}); in Compute() 460 element_tensor.shaped<T, 2>({1, element_tensor.NumElements()}))); in Compute() 475 const_cast<const Tensor&>(zeros).shaped<T, 2>( in Compute() 479 auto output_flat = output->shaped<T, 2>({1, output->NumElements()}); in Compute() 638 t.shaped<T, 2>({1, t.NumElements()}))); in Compute() 651 const_cast<const Tensor&>(zeros).shaped<T, 2>( in Compute() 655 auto output_flat = output->shaped<T, 2>({1, output->NumElements()}); in Compute()
|
D | one_hot_op.cc | 110 indices.shaped<TI, 2>({prefix_dim_size, suffix_dim_size}); in Compute() 114 output->shaped<T, 3>({prefix_dim_size, depth_v, suffix_dim_size}); in Compute()
|
/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_SparseFillEmptyRowsGrad.pbtxt | 29 Takes vectors reverse_index_map, shaped `[N]`, and grad_values, 30 shaped `[N_full]`, where `N_full >= N` and copies data into either 31 `d_values` or `d_default_value`. Here `d_values` is shaped `[N]` and
|
D | api_def_CompareAndBitpack.pbtxt | 50 Given an `input` shaped `[s0, s1, ..., s_n]`, the output is 51 a `uint8` tensor shaped `[s0, s1, ..., s_n / 8]`.
|
D | api_def_SparseFillEmptyRows.pbtxt | 78 This op also returns an indicator vector shaped `[dense_shape[0]]` such that 82 And a reverse index map vector shaped `[indices.shape[0]]` that is used during
|
/external/tensorflow/tensorflow/core/framework/ |
D | tensor.h | 398 return shaped<T, 1>({NumElements()}); in flat() 430 typename TTypes<T, NDIMS>::Tensor shaped(gtl::ArraySlice<int64> new_sizes); 487 return shaped<T, 1>({NumElements()}); in flat() 496 typename TTypes<T, NDIMS>::ConstTensor shaped( 812 typename TTypes<T, NDIMS>::Tensor Tensor::shaped( in shaped() function 839 typename TTypes<T, NDIMS>::ConstTensor Tensor::shaped( in shaped() function 880 return shaped<T, NDIMS>(ComputeFlatInnerDims(shape_.dim_sizes(), NDIMS)); in flat_inner_dims() 885 return shaped<T, NDIMS>(ComputeFlatOuterDims(shape_.dim_sizes(), NDIMS)); in flat_outer_dims() 892 return shaped<T, NDIMS>(ComputeFlatInnerDims(flat_outer, NDIMS)); in flat_inner_outer_dims() 897 return shaped<T, NDIMS>(ComputeFlatInnerDims(shape_.dim_sizes(), NDIMS)); in flat_inner_dims() [all …]
|
D | tensor_test.cc | 372 T shaped = (t.*Func)(sizes); in TestReshape() local 373 TestReshapeImpl(shaped, sizes); in TestReshape() 378 T shaped = (static_cast<const Tensor&>(t).*Func)(sizes); in TestReshape() local 379 TestReshapeImpl(shaped, sizes); in TestReshape() 383 void TestReshapeImpl(T shaped, std::initializer_list<int64> sizes) { in TestReshapeImpl() argument 385 for (int i = 0; i < shaped.rank(); ++i, ++iter) { in TestReshapeImpl() 386 EXPECT_EQ(*iter, shaped.dimension(i)); in TestReshapeImpl() 396 EXPECT_EQ(shaped(coord), *reinterpret_cast<const Scalar*>(&expected_first)); in TestReshapeImpl() 399 coord[i] = shaped.dimension(i) - 1; in TestReshapeImpl() 404 EXPECT_EQ(shaped(coord), reinterpret_cast<const Scalar*>( in TestReshapeImpl() [all …]
|
/external/iproute2/examples/ |
D | README.cbq | 81 # will be shaped. 85 # will be shaped. 102 # Let all traffic from backbone to client will be shaped at 28Kbit and
|
/external/skqp/src/compute/hs/ |
D | README.md | 67 … | :x: | :x: | :x: | Need to generate properly shaped kernels 69 …ck_mark: | :white_check_mark: | :x: | Good but the assumed *best-shaped* kernels aren't be… 70 … | :x: | :x: | :x: | Need to generate properly shaped kernels 129 … | :x: | :x: | :x: | Need to generate properly shaped kernels 172 …ol | :x: | :x: | :x: | Need to generate properly shaped kernels
|
/external/skia/src/compute/hs/ |
D | README.md | 67 … | :x: | :x: | :x: | Need to generate properly shaped kernels 69 …ck_mark: | :white_check_mark: | :x: | Good but the assumed *best-shaped* kernels aren't be… 70 … | :x: | :x: | :x: | Need to generate properly shaped kernels 129 … | :x: | :x: | :x: | Need to generate properly shaped kernels 172 …ol | :x: | :x: | :x: | Need to generate properly shaped kernels
|