wehub-resource-sync
103 lines
3.2 KiB
C++
103 lines
3.2 KiB
C++
/* Copyright (c) 2023 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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#pragma once
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#if defined(__NVCC__) || defined(__HIPCC__)
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#include <thrust/device_ptr.h>
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#include <thrust/functional.h>
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#include <thrust/reduce.h>
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#else
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#include <algorithm>
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#endif
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#include "paddle/phi/core/tensor_utils.h"
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#include "paddle/phi/kernels/funcs/sequence_mask.h"
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namespace phi {
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template <typename T, typename Context>
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void SequenceMaskScalarKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& max_len,
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DataType out_dtype,
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DenseTensor* y) {
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int maxlen = max_len.to<int>();
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auto* x_data = x.data<T>();
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int64_t x_numel = x.numel();
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if (maxlen < 0) {
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if (x_numel == 0) {
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maxlen = 0;
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} else {
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#if defined(__NVCC__) || defined(__HIPCC__)
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VLOG(10)
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<< "SequenceMaskOp on GPU may be slow when maxlen is not provided.";
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maxlen = static_cast<int>(
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thrust::reduce(thrust::device_pointer_cast(x_data),
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thrust::device_pointer_cast(x_data) + x_numel,
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static_cast<T>(0),
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thrust::maximum<T>()));
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#else
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maxlen = static_cast<int>(*std::max_element(x_data, x_data + x_numel));
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#endif
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}
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auto y_dim = vectorize<int64_t>(x.dims());
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y_dim.push_back(maxlen);
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y->Resize(y_dim);
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}
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if (x_numel == 0) {
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dev_ctx.Alloc(y, out_dtype);
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return;
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}
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VisitDataType(out_dtype,
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funcs::SequenceMaskFunctor<Context, T>(
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dev_ctx, x_data, y, x_numel * maxlen, maxlen));
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}
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template <typename T, typename Context>
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void SequenceMaskKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const optional<DenseTensor>& max_len_tensor,
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int maxlen,
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DataType out_dtype,
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DenseTensor* y) {
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if (max_len_tensor) {
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bool is_gpu_place = dev_ctx.GetPlace().GetType() == AllocationType::GPU;
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if (is_gpu_place) {
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DenseTensor temp;
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Copy(dev_ctx, *max_len_tensor.get_ptr(), CPUPlace(), false, &temp);
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maxlen = *temp.data<int32_t>();
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} else {
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maxlen = *max_len_tensor.get_ptr()->data<int32_t>();
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}
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auto y_dim = vectorize<int64_t>(x.dims());
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y_dim.push_back(maxlen);
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y->Resize(y_dim);
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PADDLE_ENFORCE_GT(
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maxlen,
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0,
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common::errors::InvalidArgument(
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"Input(MaxLenTensor) value should be greater than 0. But "
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"received Input(MaxLenTensor) value = %d.",
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maxlen));
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}
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SequenceMaskScalarKernel<T, Context>(
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dev_ctx, x, Scalar(maxlen), out_dtype, y);
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}
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} // namespace phi
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