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100 lines
3.5 KiB
100 lines
3.5 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 <stdio.h>
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#include <thrust/device_vector.h>
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#include <thrust/host_vector.h>
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#include "paddle/fluid/operators/ctc_align_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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__global__ void MergeAndDelCudaKernel(const int64_t num_token, const T* tokens,
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const size_t num_seq, size_t* lod0,
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const int blank, const int merge_repeated,
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size_t* out_lod0, T* output) {
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int ouput_idx = 0;
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out_lod0[0] = 0;
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for (int i = 0; i < num_seq; ++i) {
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T pre_token = -1;
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for (int j = lod0[i]; j < lod0[i + 1]; ++j) {
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if (tokens[j] != blank && !(merge_repeated && tokens[j] == pre_token)) {
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output[ouput_idx] = tokens[j];
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++ouput_idx;
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}
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pre_token = tokens[j];
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}
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out_lod0[i + 1] = ouput_idx;
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}
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}
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template <typename T>
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class CTCAlignOpCUDAKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
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"It must use CUDAPlace.");
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const size_t level = 0;
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auto* input = ctx.Input<LoDTensor>("Input");
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auto* output = ctx.Output<LoDTensor>("Output");
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auto input_lod = framework::ToAbsOffset(input->lod());
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const T* tokens = input->data<T>();
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const int64_t num_tokens = input->dims()[0];
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const size_t num_seq = input_lod[level].size() - 1;
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const int blank = ctx.Attr<int>("blank");
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const int merge_repeated =
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static_cast<int>(ctx.Attr<bool>("merge_repeated"));
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// prepare a lod to record lod information while merging elements
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thrust::device_vector<size_t> dev_out_lod0(input_lod[level].size());
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size_t* dev_out_lod0_ptr = thrust::raw_pointer_cast(dev_out_lod0.data());
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// merge elements and delete blank
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T* output_data = output->mutable_data<T>({num_tokens, 1}, ctx.GetPlace());
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auto stream = ctx.cuda_device_context().stream();
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MergeAndDelCudaKernel<T><<<1, 1, 0, stream>>>(
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num_tokens, tokens, num_seq,
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input_lod[level].CUDAMutableData(ctx.GetPlace()), blank, merge_repeated,
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dev_out_lod0_ptr, output_data);
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// set output lod
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std::vector<size_t> host_out_lod0(dev_out_lod0.begin(), dev_out_lod0.end());
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framework::LoD out_lod;
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out_lod.push_back(host_out_lod0);
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output->set_lod(out_lod);
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// resize output dims
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output->Resize({static_cast<int64_t>(host_out_lod0.back()), 1});
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if (host_out_lod0.back() == 0) {
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output->Resize({1, 1});
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output->mutable_data<T>(ctx.GetPlace());
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math::SetConstant<platform::CUDADeviceContext, T> set_constant;
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set_constant(ctx.template device_context<platform::CUDADeviceContext>(),
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output, -1);
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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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REGISTER_OP_CUDA_KERNEL(ctc_align, paddle::operators::CTCAlignOpCUDAKernel<int>,
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paddle::operators::CTCAlignOpCUDAKernel<int64_t>);
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