| /external/tensorflow/tensorflow/core/kernels/ |
| substr_op.cc | 109 auto input = input_tensor.shaped<string, 1>(bcast.x_reshape());
110 auto output = output_tensor->shaped<string, 1>(bcast.result_shape());
111 auto pos_shaped = pos_tensor.shaped<T, 1>(bcast.y_reshape());
112 auto len_shaped = len_tensor.shaped<T, 1>(bcast.y_reshape());
119 input_buffer.shaped<string, 1>(bcast.result_shape());
129 pos_buffer.shaped<T, 1>(bcast.result_shape()));
139 len_buffer.shaped<T, 1>(bcast.result_shape()));
158 auto input = input_tensor.shaped<string, 2>(bcast.x_reshape());
159 auto output = output_tensor->shaped<string, 2>(bcast.result_shape());
160 auto pos_shaped = pos_tensor.shaped<T, 2>(bcast.y_reshape())
[all...] |
| adjust_contrast_op.cc | 81 context->eigen_device<Device>(), input.shaped<T, 4>(shape),
83 max_value.scalar<float>(), mean_values.shaped<float, 4>(shape),
84 output->shaped<float, 4>(shape));
216 auto input_data = input->shaped<float, 3>({batch, image_size, channels});
218 auto output_data = output->shaped<float, 3>({batch, image_size, channels});
407 options.input->shaped<float, 4>(shape), options.factor->scalar<float>(),
408 options.output->shaped<float, 4>(shape));
429 options.input->shaped<float, 4>(shape), options.factor->scalar<float>(),
430 options.output->shaped<float, 4>(shape));
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| betainc_op.cc | 94 auto a_value = a.shaped<T, NDIM>(a_shaper.x_reshape()); \
95 auto b_value = b.shaped<T, NDIM>(b_shaper.x_reshape()); \
96 auto x_value = x.shaped<T, NDIM>(x_shaper.x_reshape()); \
101 output->shaped<T, NDIM>(a_shaper.y_reshape())); \
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| gather_op.cc | 106 params.shaped<T, 3>({outer_size, gather_dim_size, inner_size});
108 auto out_flat = out->shaped<T, 3>({outer_size, N, inner_size});
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| one_hot_op.cc | 110 indices.shaped<TI, 2>({prefix_dim_size, suffix_dim_size});
114 output->shaped<T, 3>({prefix_dim_size, depth_v, suffix_dim_size});
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| pack_op.cc | 105 output->shaped<T, 2>({before_dim, after_dim * axis_dim});
113 values[i].shaped<T, 2>({before_dim, after_dim})));
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| unpack_op.cc | 107 input.shaped<T, 3>({1, before_dim, axis_dim * after_dim});
115 auto output_shaped = output->shaped<T, 3>({1, before_dim, after_dim});
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| cwise_ops_common.h | 123 eigen_device, out->shaped<Tout, 2>(bcast->result_shape()),
124 in0.template shaped<Tin, 2>(bcast->x_reshape()),
126 in1.template shaped<Tin, 2>(bcast->y_reshape()),
130 eigen_device, out->shaped<Tout, 3>(bcast->result_shape()),
131 in0.template shaped<Tin, 3>(bcast->x_reshape()),
133 in1.template shaped<Tin, 3>(bcast->y_reshape()),
137 eigen_device, out->shaped<Tout, 4>(bcast->result_shape()),
138 in0.template shaped<Tin, 4>(bcast->x_reshape()),
140 in1.template shaped<Tin, 4>(bcast->y_reshape()),
144 eigen_device, out->shaped<Tout, 5>(bcast->result_shape())
[all...] |
| 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}),
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| lrn_op.cc | 93 auto in_shaped = in.shaped<T, 2>({nodes * batch, depth});
100 auto out_shaped = output->shaped<T, 2>({nodes * batch, depth});
321 auto grads_shaped = in_grads.shaped<T, 2>({nodes * batch, depth});
322 auto in_shaped = in_image.shaped<T, 2>({nodes * batch, depth});
323 auto activations = out_image.shaped<T, 2>({nodes * batch, depth});
325 auto out_shaped = output->shaped<T, 2>({nodes * batch, depth});
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| split_op.cc | 158 input.shaped<T, 3>({prefix_dim_size, split_dim_size, suffix_dim_size});
194 auto result_shaped = result->shaped<T, 3>(
322 input.shaped<T, 3>({prefix_dim_size, split_dim_size, suffix_dim_size});
344 auto result_shaped = result->shaped<T, 3>(
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| split_v_op.cc | 213 input.shaped<T, 3>({prefix_dim_size, split_dim_size, suffix_dim_size});
250 auto result_shaped = result->shaped<T, 3>(
367 auto input_reshaped = input.shaped<T, 2>(
383 auto result_shaped = result->shaped<T, 2>(
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| summary_audio_op.cc | 79 tensor.shaped<float, 3>({batch_size, length_frames, num_channels});
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| adjust_hue_op.cc | 211 auto input_data = input->shaped<float, 2>({channel_count, kChannelSize});
213 auto output_data = output->shaped<float, 2>({channel_count, kChannelSize});
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| adjust_saturation_op.cc | 188 auto input_data = input->shaped<float, 2>({channel_count, kChannelSize});
190 auto output_data = output->shaped<float, 2>({channel_count, kChannelSize});
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| batch_kernels.cc | 72 input.shaped<T, 2>({1, input.NumElements()})));
83 auto output_flat = output->shaped<T, 2>({1, output->NumElements()});
149 input.shaped<T, 3>({1, input.shape().dim_size(0), suffix_dim_size});
158 auto output_shaped = output.shaped<T, 3>({1, size, suffix_dim_size});
454 auto index_flat = index->shaped<int64, 2>({batch.num_tasks(), 3});
635 batch_index_t.shaped<int64, 2>({batch_index_t.dim_size(0), 3});
831 batch_index_t.shaped<int64, 2>({batch_index_t.dim_size(0), 3});
[all...] |
| batchtospace_op.cc | 191 output_tensor->shaped<T, NUM_BLOCK_DIMS + 2>( \
194 orig_input_tensor.shaped<T, NUM_BLOCK_DIMS + 2>( \
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| lookup_table_op.cc | 329 empty_key_input->template shaped<K, 2>({1, key_shape_.num_elements()}),
355 const auto key_matrix = key.shaped<K, 2>({num_elements, key_size});
356 auto value_matrix = value->shaped<V, 2>({num_elements, value_size});
365 empty_key_.AccessTensor(ctx)->template shaped<K, 2>({1, key_size});
442 empty_key_.AccessTensor(ctx)->template shaped<K, 2>(
508 const auto key_matrix = key.shaped<K, 2>({num_elements, key_size});
509 auto value_matrix = value.shaped<V, 2>({num_elements, value_size});
516 empty_key_.AccessTensor(ctx)->template shaped<K, 2>({1, key_size});
[all...] |
| scan_ops.cc | 82 functor::Scan<Device, Reducer, T>()(d, input.shaped<T, 3>(reduced_shape),
83 output->shaped<T, 3>(reduced_shape),
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| spacetobatch_op.cc | 190 orig_input_tensor.shaped<T, NUM_BLOCK_DIMS + 2>( \
193 output_tensor->shaped<T, NUM_BLOCK_DIMS + 2>( \
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| /prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.15-4.8/sysroot/usr/include/X11/extensions/ |
| shape.h | 46 Bool shaped; /* true if the region exists */ member in struct:__anon61952
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| /external/tensorflow/tensorflow/core/framework/ |
| tensor.h | 292 /// auto outer = my_ten.shaped<T, 2>({4, 15});
294 /// auto outer = my_ten.shaped<T, 2>({4, 8});
296 /// auto weird = my_ten.shaped<T, 3>({6, 5, 2});
303 return shaped<T, 1>({NumElements()});
335 typename TTypes<T, NDIMS>::Tensor shaped(gtl::ArraySlice<int64> new_sizes);
341 /// The allowed bitcast is the only difference from `shaped()`.
392 return shaped<T, 1>({NumElements()});
401 typename TTypes<T, NDIMS>::ConstTensor shaped(
408 /// The allowed bitcast is the only difference from `shaped()`.
661 typename TTypes<T, NDIMS>::Tensor Tensor::shaped( function in class:tensorflow::Tensor
688 typename TTypes<T, NDIMS>::ConstTensor Tensor::shaped( function in class:tensorflow::Tensor
[all...] |
| tensor_test.cc | 371 T shaped = (t.*Func)(sizes); local
372 TestReshapeImpl(shaped, sizes);
377 T shaped = (static_cast<const Tensor&>(t).*Func)(sizes); local
378 TestReshapeImpl(shaped, sizes);
382 void TestReshapeImpl(T shaped, std::initializer_list<int64> sizes) {
384 for (int i = 0; i < shaped.rank(); ++i, ++iter) {
385 EXPECT_EQ(*iter, shaped.dimension(i));
392 // To handle the cast when `shaped` is bit casted into a different type.
395 EXPECT_EQ(shaped(coord), *reinterpret_cast<const Scalar*>(&expected_first));
398 coord[i] = shaped.dimension(i) - 1
[all...] |
| /external/tensorflow/tensorflow/contrib/image/kernels/ |
| bipartite_match_op.cc | 89 input_distance_mat.shaped<float, 2>(
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| adjust_hsv_in_yiq_op.cc | 105 auto input_data = input->shaped<float, 2>({channel_count, kChannelSize});
109 auto output_data = output->shaped<float, 2>({channel_count, kChannelSize});
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