wehub-resource-sync
124 lines
3.7 KiB
Plaintext
124 lines
3.7 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/flip_kernel.h"
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#include "paddle/common/array.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/backends/gpu/gpu_launch_config.h"
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#include "paddle/phi/common/place.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T>
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__global__ void FlipCudaKernel(const T* in_data,
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T* out_data,
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Array<int64_t, DDim::kMaxRank> shape,
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Array<int64_t, DDim::kMaxRank> stride,
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Array<int, DDim::kMaxRank> flip_dims,
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const int rank,
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const int64_t numel,
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const int flip_dims_size) {
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int64_t idx =
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static_cast<int64_t>(blockIdx.x) * static_cast<int64_t>(blockDim.x) +
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static_cast<int64_t>(threadIdx.x);
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if (idx >= numel) {
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return;
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}
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int64_t cur_indices = idx;
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int64_t rem = 0;
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int64_t dst_offset = 0;
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#pragma unroll
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for (int i = 0; i < DDim::kMaxRank; ++i) {
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if (i >= rank) {
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break;
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}
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int64_t temp = cur_indices;
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cur_indices = cur_indices / stride[i];
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rem = temp - cur_indices * stride[i];
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// flip the indices if it is in flip_dims
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for (int j = 0; j < flip_dims_size; ++j) {
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if (i == flip_dims[j]) {
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cur_indices = shape[i] - 1 - cur_indices;
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}
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}
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dst_offset += cur_indices * stride[i];
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cur_indices = rem;
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}
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out_data[idx] = in_data[dst_offset];
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}
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template <typename T, typename Context>
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void FlipKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const std::vector<int>& axis,
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DenseTensor* out) {
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auto* in_data = x.data<T>();
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auto* out_data = dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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auto x_dims = x.dims();
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const int rank = x_dims.size();
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const int64_t numel = x.numel();
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size_t flip_dims_size = axis.size();
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auto x_stride = common::stride(x_dims);
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Array<int64_t, DDim::kMaxRank> stride_array;
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Array<int64_t, DDim::kMaxRank> shape_array;
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Array<int, DDim::kMaxRank> flip_dims_array;
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for (int i = 0; i < rank; ++i) {
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stride_array[i] = x_stride[i];
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shape_array[i] = x_dims[i];
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if (i < flip_dims_size) {
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flip_dims_array[i] = axis[i] < 0 ? axis[i] + rank : axis[i];
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} else {
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flip_dims_array[i] = 0;
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}
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}
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auto config = backends::gpu::GetGpuLaunchConfig1D(dev_ctx, numel);
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FlipCudaKernel<T>
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<<<config.block_per_grid, config.thread_per_block, 0, dev_ctx.stream()>>>(
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in_data,
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out_data,
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shape_array,
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stride_array,
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flip_dims_array,
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rank,
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numel,
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flip_dims_size);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(flip,
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GPU,
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ALL_LAYOUT,
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phi::FlipKernel,
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float,
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double,
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phi::float16,
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phi::bfloat16,
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int,
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int64_t,
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bool,
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phi::complex64,
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phi::complex128) {}
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