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100 lines
3.7 KiB
100 lines
3.7 KiB
/* Copyright (c) 2016 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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#include <thrust/fill.h>
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#include "paddle/fluid/operators/controlflow/compare_all_op.h"
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#include "paddle/fluid/operators/reduce_ops/cub_reduce.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 IdentityFunctor {
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HOSTDEVICE explicit inline IdentityFunctor() {}
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HOSTDEVICE inline T operator()(const T& x) const { return x; }
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};
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struct BitwiseAdd {
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// Bitwise add operator, returns <tt>a + b</tt>
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template <typename T>
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__host__ __device__ __forceinline__ T operator()(const T& a,
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const T& b) const {
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return a & b;
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}
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};
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template <typename DeviceContext, typename Functor>
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class CompareReduceOpKernel
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: public framework::OpKernel<typename Functor::ELEM_TYPE> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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using T = typename Functor::ELEM_TYPE;
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using Tensor = framework::Tensor;
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auto* x = context.Input<Tensor>("X");
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auto* y = context.Input<Tensor>("Y");
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auto* z = context.Output<Tensor>("Out");
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bool shape_same = true;
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Tensor tmp;
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framework::DDim x_dims = x->dims();
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framework::DDim y_dims = y->dims();
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if (x_dims.size() != y_dims.size()) {
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shape_same = false;
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} else {
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for (auto i = 0; i < x_dims.size(); i++) {
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if (x_dims[i] != y_dims[i]) {
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shape_same = false;
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break;
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}
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}
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}
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bool* z_data = z->mutable_data<bool>(context.GetPlace());
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if (!shape_same) {
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thrust::device_ptr<bool> z_dev_ptr(z_data);
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thrust::fill(z_dev_ptr, z_dev_ptr + 1, false);
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return;
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} else {
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tmp.mutable_data<bool>(x_dims, context.GetPlace());
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ElementwiseComputeEx<Functor, DeviceContext, T, bool>(context, x, y, 0,
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Functor(), &tmp);
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// Reduce by 'bitwise and' operator
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std::vector<int> reduce_dims;
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reduce_dims.resize(tmp.dims().size());
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for (int i = 0; i < reduce_dims.size(); ++i) reduce_dims[i] = i;
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auto stream = context.cuda_device_context().stream();
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TensorReduce<bool, bool, BitwiseAdd, IdentityFunctor<bool>>(
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tmp, z, reduce_dims, true, BitwiseAdd(), IdentityFunctor<bool>(),
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stream);
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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#define REGISTER_COMPARE_REDUCE_CUDA_KERNEL(op_type, functor) \
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REGISTER_OP_CUDA_KERNEL( \
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op_type, paddle::operators::CompareReduceOpKernel< \
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paddle::platform::CUDADeviceContext, functor<int>>, \
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paddle::operators::CompareReduceOpKernel< \
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paddle::platform::CUDADeviceContext, functor<int64_t>>, \
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paddle::operators::CompareReduceOpKernel< \
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paddle::platform::CUDADeviceContext, functor<float>>, \
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paddle::operators::CompareReduceOpKernel< \
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paddle::platform::CUDADeviceContext, functor<double>>);
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REGISTER_COMPARE_REDUCE_CUDA_KERNEL(equal_all,
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paddle::operators::EqualReduceFunctor);
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