wehub-resource-sync
104 lines
3.8 KiB
C++
104 lines
3.8 KiB
C++
// 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/reduce_sum_kernel.h"
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#include <set>
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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/reduce.h"
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#include "paddle/phi/kernels/full_kernel.h"
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#include "paddle/phi/kernels/funcs/reduce_functor.h"
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namespace phi {
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template <typename T, typename Context>
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void SumRawKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const IntArray& dims,
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bool keep_dim,
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bool reduce_all,
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DataType out_dtype,
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DenseTensor* out) {
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if (out_dtype == DataType::UNDEFINED && out->dtype() != x.dtype()) {
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out_dtype = out->dtype();
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}
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if (x.numel() == 0) {
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dev_ctx.template Alloc<T>(out);
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// When out_dtype is DataType::UNDEFINED and input is int32 or bool,
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// result is int64, but FullKernel out_dtype parameter is not used, we need
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// to set int64 explicitly.
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if (out_dtype == DataType::INT64) {
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Full<int64_t, Context>(dev_ctx, out->dims(), 0, out);
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} else {
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Full<T, Context>(dev_ctx, out->dims(), 0, out);
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}
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return;
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}
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if constexpr (std::is_same_v<T, float16> || std::is_same_v<T, bfloat16>) {
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DenseTensor x_fp32 = Cast<T, Context>(dev_ctx, x, DataType::FLOAT32);
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DataType final_out_dtype = out_dtype;
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if (final_out_dtype == DataType::UNDEFINED) {
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final_out_dtype = x.dtype();
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}
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if (final_out_dtype == DataType::FLOAT32) {
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Reduce<CPUContext, float, funcs::SumFunctor>(dev_ctx,
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x_fp32,
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reduce_all,
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dims.GetData(),
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keep_dim,
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DataType::UNDEFINED,
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out);
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} else {
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DenseTensor intermediate_result;
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intermediate_result.set_meta(out->meta());
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Reduce<CPUContext, float, funcs::SumFunctor>(dev_ctx,
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x_fp32,
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reduce_all,
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dims.GetData(),
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keep_dim,
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DataType::UNDEFINED,
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&intermediate_result);
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CastKernel<float, Context>(
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dev_ctx, intermediate_result, final_out_dtype, out);
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}
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} else {
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Reduce<CPUContext, T, funcs::SumFunctor>(
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dev_ctx, x, reduce_all, dims.GetData(), keep_dim, out_dtype, out);
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(sum_raw,
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CPU,
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ALL_LAYOUT,
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phi::SumRawKernel,
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bool,
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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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int16_t,
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int8_t,
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uint8_t,
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int,
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int64_t,
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phi::complex64,
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phi::complex128) {
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kernel->OutputAt(0).SetDataType(phi::DataType::UNDEFINED);
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}
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