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62 lines
2.1 KiB
62 lines
2.1 KiB
/* Copyright (c) 2020 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 "paddle/fluid/operators/dequantize_log_op.h"
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#include "paddle/fluid/operators/math.h"
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#include "paddle/fluid/platform/cuda_primitives.h"
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#include "paddle/fluid/platform/hostdevice.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 KeDequantize(const T* in, const float* dict, int num,
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float* out) {
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const int idx = threadIdx.x + blockIdx.x * blockDim.x;
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if (idx < num) {
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if (in[idx] < 0) {
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out[idx] = -dict[in[idx] + 128];
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} else {
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out[idx] = dict[in[idx]];
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}
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}
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}
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template <typename T>
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struct DequantizeFunctor<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* dict,
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framework::Tensor* out) {
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const T* in_data = in->data<T>();
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const float* dict_data = dict->data<float>();
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float* out_data = out->mutable_data<float>(dev_ctx.GetPlace());
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int num = in->numel();
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int block = 512;
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int grid = (num + block - 1) / block;
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KeDequantize<T><<<grid, block, 0, dev_ctx.stream()>>>(in_data, dict_data,
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num, out_data);
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}
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};
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template struct DequantizeFunctor<platform::CUDADeviceContext, int8_t>;
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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(dequantize_log, ops::DequantizeLogKernel<CUDA, int8_t>);
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