wehub-resource-sync
99 lines
3.2 KiB
Plaintext
99 lines
3.2 KiB
Plaintext
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/expand_as_kernel.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/common/scalar.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/expand_kernel.h"
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#include "paddle/phi/kernels/funcs/broadcast_function.h"
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namespace phi {
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template <typename T, typename Context>
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void ExpandAsKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const optional<DenseTensor>& y,
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const std::vector<int64_t>& target_shape_t,
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DenseTensor* out) {
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if (x.numel() == 0 || (y.get_ptr() && y.get_ptr()->numel() == 0)) {
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dev_ctx.template Alloc<T>(out);
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return;
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}
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std::vector<int64_t> target_shape = target_shape_t;
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if (y.get_ptr()) {
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target_shape = vectorize<int64_t>(y.get_ptr()->dims());
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}
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int rank = x.dims().size();
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int target_rank = static_cast<int>(target_shape.size());
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auto vec_in_dims = vectorize<int64_t>(x.dims());
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unsigned int diff = target_rank - rank;
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vec_in_dims.insert(vec_in_dims.begin(), diff, 1);
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for (unsigned int i = 0; i < vec_in_dims.size(); ++i) {
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if (target_shape[i] == 0) {
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dev_ctx.template Alloc<T>(out);
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return;
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}
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if (i < diff) {
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PADDLE_ENFORCE_GT(
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target_shape[i],
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0,
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errors::InvalidArgument(
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"The expanded size (%d) for non-existing dimensions must be "
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"positive for expand_as_v2 op.",
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target_shape[i]));
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} else if (target_shape[i] > 0) {
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if (vec_in_dims[i] != 1) {
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PADDLE_ENFORCE_EQ(
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vec_in_dims[i],
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target_shape[i],
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errors::InvalidArgument(
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"The value (%d) of the non-singleton dimension does not match"
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" the corresponding value (%d) in shape for expand_as_v2 op.",
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vec_in_dims[i],
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target_shape[i]));
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}
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} else {
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PADDLE_ENFORCE_EQ(
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target_shape[i],
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-1,
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errors::InvalidArgument(
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"When the value in shape is negative for expand_as_v2 op, "
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"only -1 is supported, but the value received is %d.",
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target_shape[i]));
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}
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}
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ExpandKernel<T, Context>(dev_ctx, x, target_shape, out);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(expand_as,
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GPU,
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ALL_LAYOUT,
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phi::ExpandAsKernel,
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float,
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double,
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int,
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int64_t,
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bool,
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phi::bfloat16) {}
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