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/external/tensorflow/tensorflow/core/kernels/
Dsubstr_op.cc144 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()
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Dbroadcast_to_op.h57 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()
Dadjust_contrast_op.cc81 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()
Dlookup_table_op.cc346 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()
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Dbetainc_op.cc94 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()
Dcwise_ops_common.h125 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()
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Dsplit_op.cc239 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()
Dsplit_v_op.cc301 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()
Dlrn_op.cc97 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()
Dreduction_ops_common.h106 return out->shaped<T, N>(out_reshape_);
112 return data.shaped<T, N>(data_reshape_);
231 const_shuffled.shaped<T, 2>({unreduced, reduced}),
Dxent_op.cc92 logits_in.template shaped<T, 2>(bcast.x_reshape()), in Compute()
93 labels_in.template shaped<T, 2>(bcast.y_reshape()), in Compute()
Dgather_op.cc106 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()
Dunpack_op.cc107 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()
Dpack_op.cc105 output->shaped<T, 2>({before_dim, after_dim * axis_dim}); in Compute()
113 values[i].shaped<T, 2>({before_dim, after_dim}))); in Compute()
Dmkl_lrn_op.cc229 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()
Dlist_kernels.h149 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()
Done_hot_op.cc110 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/
Dapi_def_SparseFillEmptyRowsGrad.pbtxt29 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
Dapi_def_CompareAndBitpack.pbtxt50 Given an `input` shaped `[s0, s1, ..., s_n]`, the output is
51 a `uint8` tensor shaped `[s0, s1, ..., s_n / 8]`.
Dapi_def_SparseFillEmptyRows.pbtxt78 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/
Dtensor.h398 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()
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Dtensor_test.cc372 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()
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/external/iproute2/examples/
DREADME.cbq81 # 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/
DREADME.md67 … | :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/
DREADME.md67 … | :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

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