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Paddle/paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu

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3.2 KiB

// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include "paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
namespace paddle {
namespace operators {
using platform::PADDLE_CUDA_NUM_THREADS;
using LoDTensor = framework::LoDTensor;
template <typename T>
__global__ void CalcOutPut(const T* in_data, const size_t* in_lod,
const size_t lod_len, const int64_t win_size,
const int64_t pad_value, T* out_data) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
if (index < in_lod[lod_len - 1]) {
int end_idx = 0;
// Get LoD interval of index
for (int i = 1; i < lod_len; ++i) {
if (index < in_lod[i]) {
end_idx = in_lod[i];
break;
}
}
for (size_t i = 0; i < win_size; ++i) {
int word_pos = index + i;
out_data[index * win_size + i] =
word_pos < end_idx ? in_data[word_pos] : pad_value;
}
}
}
template <typename T>
class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto* in = context.Input<LoDTensor>("X");
auto* out = context.Output<LoDTensor>("Out");
int win_size = context.Attr<int>("win_size");
int pad_value = context.Attr<int>("pad_value");
auto in_dims = in->dims();
auto in_lod = in->lod();
PADDLE_ENFORCE_EQ(
static_cast<uint64_t>(in_dims[0]), in_lod[0].back(),
platform::errors::InvalidArgument(
"The actual input data's size mismatched with LoD information."
"Received input data size is %d (actual) vs %d (loD information).",
static_cast<uint64_t>(in_dims[0]), in_lod[0].back()));
/* Generate enumerate sequence set */
auto stream = context.cuda_device_context().stream();
auto lod0 = in_lod[0];
auto in_len = in->numel();
auto in_data = in->data<T>();
out->Resize({in_dims[0], win_size});
auto out_data = out->mutable_data<T>(context.GetPlace());
// Copy LoD to GPU
const size_t* dev_in_lod_ptr = lod0.CUDAData(context.GetPlace());
// Calc output tensor
CalcOutPut<<<(in_len - 1) / PADDLE_CUDA_NUM_THREADS + 1,
PADDLE_CUDA_NUM_THREADS, 0, stream>>>(
in_data, dev_in_lod_ptr, lod0.size(), win_size, pad_value, out_data);
out->set_lod(in->lod());
}
};
} // namespace operators
} // namespace paddle
REGISTER_OP_CUDA_KERNEL(
sequence_enumerate,
paddle::operators::SequenceEnumerateOpCUDAKernel<int32_t>,
paddle::operators::SequenceEnumerateOpCUDAKernel<int64_t>);