wehub-resource-sync
102 lines
4.3 KiB
C++
102 lines
4.3 KiB
C++
/* Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#pragma once
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#include <algorithm>
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#include <vector>
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#include "paddle/common/enforce.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/common/memory_utils.h"
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#include "paddle/phi/kernels/funcs/blas/blas.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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namespace phi {
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namespace funcs {
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// template struct ColwiseSum<GPUContext, double>;
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// The ColwiseSum<GPUContext, double> failed in debug
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// mode,
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// and only failed for this case. So reimplemented it.
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template <>
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void ColwiseSum<GPUContext, double>::operator()(const GPUContext& dev_ctx,
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const DenseTensor& input,
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DenseTensor* vector) {
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auto in_dims = input.dims();
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auto size = input.numel() / in_dims[0];
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PADDLE_ENFORCE_EQ(vector->numel(),
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size,
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common::errors::InvalidArgument(
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"The size of input vector"
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" should be equal to the size of input tensor column"
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" dimension. Expected vector size=%d, but received %d",
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size,
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vector->numel()));
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DenseTensor one;
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one.Resize({in_dims[0]});
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dev_ctx.template Alloc<double>(&one);
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SetConstant<GPUContext, double> set;
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set(dev_ctx, &one, static_cast<double>(1.0));
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PADDLE_ENFORCE_LE_INT_MAX(in_dims[0], "ColwiseSum GEMV m");
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PADDLE_ENFORCE_LE_INT_MAX(in_dims[1], "ColwiseSum GEMV n");
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funcs::GetBlas<GPUContext, double>(dev_ctx).GEMV(true,
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static_cast<int>(in_dims[0]),
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static_cast<int>(in_dims[1]),
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1.0,
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input.data<double>(),
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one.data<double>(),
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0.0,
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vector->data<double>());
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}
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// template struct RowwiseSum<GPUContext, double>;
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// TODO(zcd): Following ColwiseSum format, need to confirm.
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// The RowwiseSum<GPUContext, double> failed in debug
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// mode,
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template <>
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void RowwiseSum<GPUContext, double>::operator()(const GPUContext& dev_ctx,
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const DenseTensor& input,
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DenseTensor* vector) {
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auto in_dims = input.dims();
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auto size = input.numel() / in_dims[0];
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PADDLE_ENFORCE_EQ(vector->numel(),
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in_dims[0],
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common::errors::InvalidArgument(
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"The size of input vector"
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" should be equal to the size of input tensor row"
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" dimension. Expected vector size=%d, but received %d",
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in_dims[0],
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vector->numel()));
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DenseTensor one;
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one.Resize({size});
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dev_ctx.template Alloc<double>(&one);
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SetConstant<GPUContext, double> set;
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set(dev_ctx, &one, static_cast<double>(1.0));
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PADDLE_ENFORCE_LE_INT_MAX(in_dims[1], "RowwiseSum GEMV m");
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PADDLE_ENFORCE_LE_INT_MAX(in_dims[0], "RowwiseSum GEMV n");
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funcs::GetBlas<GPUContext, double>(dev_ctx).GEMV(true,
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static_cast<int>(in_dims[1]),
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static_cast<int>(in_dims[0]),
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1.0,
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one.data<double>(),
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input.data<double>(),
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0.0,
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vector->data<double>());
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}
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} // namespace funcs
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} // namespace phi
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