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83 lines
3.1 KiB
83 lines
3.1 KiB
// Copyright (c) 2018 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 <cuda_runtime.h>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/operators/allclose_op.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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struct GetTensorValue<platform::CUDADeviceContext, T> {
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T operator()(const platform::CUDADeviceContext& dev_ctx,
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const framework::Tensor& tensor) const {
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const T* data = tensor.data<T>();
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T value;
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const auto gpu_place =
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BOOST_GET_CONST(platform::CUDAPlace, dev_ctx.GetPlace());
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memory::Copy(platform::CPUPlace(), &value, gpu_place, data, sizeof(T),
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dev_ctx.stream());
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return value;
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}
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};
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template <typename T>
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__global__ void AllcloseCUDAKernel(const T* in_data, const T* other_data,
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const double rtol, const double atol,
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bool equal_nan, int num, bool* out_data) {
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unsigned int idx = threadIdx.x + blockIdx.x * blockDim.x;
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bool val;
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for (int i = idx; i < num; i += blockDim.x * gridDim.x) {
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const T a = in_data[i], b = other_data[i];
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if (isnan(a) || isnan(b)) {
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val = equal_nan && isnan(a) == isnan(b);
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} else {
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T left = (a > b ? a - b : b - a);
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T right = atol + (b > 0 ? rtol * b : (-rtol) * b);
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T diff = (left > right ? left - right : right - left);
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val = a == b || left <= right || diff <= 1e-15;
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}
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if (!val) *out_data = false;
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}
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}
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template <typename T>
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struct AllcloseFunctor<platform::CUDADeviceContext, T> {
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void operator()(const platform::CUDADeviceContext& dev_ctx,
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const framework::Tensor& in, const framework::Tensor& other,
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const double rtol, const double atol, bool equal_nan,
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framework::Tensor* output) {
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int num = in.numel();
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const T* in_data = in.data<T>();
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const T* other_data = other.data<T>();
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bool* out_data = output->mutable_data<bool>(dev_ctx.GetPlace());
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int block = 1024;
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int grid = (block - 1 + num) / block;
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grid = (grid > block) ? block : grid;
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cudaMemset(out_data, true, sizeof(bool));
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AllcloseCUDAKernel<T><<<grid, block, 0, dev_ctx.stream()>>>(
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in_data, other_data, rtol, atol, equal_nan, num, out_data);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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using CUDA = paddle::platform::CUDADeviceContext;
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REGISTER_OP_CUDA_KERNEL(allclose, ops::AllcloseKernel<CUDA, float>,
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ops::AllcloseKernel<CUDA, double>);
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