wehub-resource-sync
52 lines
1.8 KiB
Plaintext
52 lines
1.8 KiB
Plaintext
// Copyright (c) 2023 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/common/enforce.h"
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#include "paddle/extension.h"
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#define CHECK_GPU_INPUT(x) \
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PADDLE_ENFORCE_EQ( \
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x.is_gpu(), true, common::errors::Fatal(#x " must be a GPU Tensor."))
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template <typename data_t>
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__global__ void relu_cuda_forward_kernel(const data_t* x,
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data_t* y,
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int64_t num) {
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int64_t gid = blockIdx.x * blockDim.x + threadIdx.x;
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for (int64_t i = gid; i < num; i += blockDim.x * gridDim.x) {
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y[i] = x[i] > static_cast<data_t>(0.) ? x[i] : static_cast<data_t>(0.);
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}
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}
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paddle::Tensor relu_cuda_forward(const paddle::Tensor& x) {
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CHECK_GPU_INPUT(x);
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auto out = paddle::empty_like(x);
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PADDLE_ENFORCE_EQ(
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x.place() == paddle::DefaultGPUPlace(),
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true,
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common::errors::InvalidArgument("Input tensor `x` should be on GPU"));
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int64_t numel = x.numel();
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int64_t block = 512;
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int64_t grid = (numel + block - 1) / block;
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PD_DISPATCH_FLOATING_AND_HALF_TYPES(
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x.type(), "relu_cuda_forward_kernel", ([&] {
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relu_cuda_forward_kernel<data_t><<<grid, block, 0, x.stream()>>>(
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x.data<data_t>(), out.data<data_t>(), numel);
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}));
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return out;
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}
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