wehub-resource-sync
151 lines
6.0 KiB
C++
151 lines
6.0 KiB
C++
// Copyright (c) 2024 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/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/cpu/elementwise.h"
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#include "paddle/phi/kernels/impl/elementwise_kernel_impl.h"
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#include "paddle/phi/kernels/legacy/elementwise_add_kernel.h"
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#include "paddle/phi/kernels/legacy/elementwise_divide_kernel.h"
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#include "paddle/phi/kernels/legacy/elementwise_multiply_kernel.h"
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#include "paddle/phi/kernels/legacy/elementwise_subtract_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void FusedElementwiseAddKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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int axis,
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const std::string& fuse_activation UNUSED,
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float fuse_alpha UNUSED,
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float fuse_beta UNUSED,
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float fused_output_scale UNUSED,
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const std::vector<int>& fused_unsqueeze2_axes
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UNUSED,
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float scale_x UNUSED,
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float scale_y UNUSED,
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float scale_out UNUSED,
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DenseTensor* out) {
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AddRawKernel<T, Context>(dev_ctx, x, y, axis, out);
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}
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template <typename T, typename Context>
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void FusedElementwiseDivKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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int axis,
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const std::string& fuse_activation UNUSED,
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float fuse_alpha UNUSED,
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float fuse_beta UNUSED,
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float fused_output_scale UNUSED,
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const std::vector<int>& fused_unsqueeze2_axes
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UNUSED,
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float scale_x UNUSED,
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float scale_y UNUSED,
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float scale_out UNUSED,
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DenseTensor* out) {
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DivideRawKernel<T, Context>(dev_ctx, x, y, axis, out);
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}
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template <typename T, typename Context>
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void FusedElementwiseMulKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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int axis,
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const std::string& fuse_activation UNUSED,
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float fuse_alpha UNUSED,
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float fuse_beta UNUSED,
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float fused_output_scale UNUSED,
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const std::vector<int>& fused_unsqueeze2_axes
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UNUSED,
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float scale_x UNUSED,
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float scale_y UNUSED,
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float scale_out UNUSED,
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DenseTensor* out) {
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MultiplyRawKernel<T, Context>(dev_ctx, x, y, axis, out);
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}
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template <typename T, typename Context>
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void FusedElementwiseSubKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& y,
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int axis,
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const std::string& fuse_activation UNUSED,
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float fuse_alpha UNUSED,
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float fuse_beta UNUSED,
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float fused_output_scale UNUSED,
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const std::vector<int>& fused_unsqueeze2_axes
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UNUSED,
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float scale_x UNUSED,
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float scale_y UNUSED,
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float scale_out UNUSED,
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DenseTensor* out) {
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SubtractRawKernel<T, Context>(dev_ctx, x, y, axis, out);
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}
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} // namespace phi
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using complex64 = phi::complex64;
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using complex128 = phi::complex128;
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PD_REGISTER_KERNEL(fused_elementwise_add,
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CPU,
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ALL_LAYOUT,
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phi::FusedElementwiseAddKernel,
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float,
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double,
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int,
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bool,
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int64_t,
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complex64,
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complex128) {}
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PD_REGISTER_KERNEL(fused_elementwise_div,
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CPU,
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ALL_LAYOUT,
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phi::FusedElementwiseDivKernel,
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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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complex64,
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complex128) {}
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PD_REGISTER_KERNEL(fused_elementwise_mul,
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CPU,
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ALL_LAYOUT,
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phi::FusedElementwiseMulKernel,
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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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complex64,
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complex128,
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phi::bfloat16) {}
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PD_REGISTER_KERNEL(fused_elementwise_sub,
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CPU,
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ALL_LAYOUT,
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phi::FusedElementwiseSubKernel,
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float,
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double,
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int16_t,
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int,
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int64_t,
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complex64,
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complex128,
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phi::bfloat16) {}
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