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128 lines
4.5 KiB
Plaintext
128 lines
4.5 KiB
Plaintext
// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/extension.h"
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#ifndef PD_BUILD_STATIC_OP
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#define PD_BUILD_STATIC_OP(name) PD_BUILD_OP(static_op_##name)
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#endif
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template <paddle::DataType D>
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class PDTraits;
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template <>
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class PDTraits<paddle::DataType::FLOAT32> {
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public:
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typedef float DataType;
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typedef float data_t;
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};
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template <>
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class PDTraits<paddle::DataType::FLOAT16> {
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public:
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typedef half DataType;
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typedef paddle::float16 data_t;
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};
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template <>
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class PDTraits<paddle::DataType::BFLOAT16> {
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public:
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typedef __nv_bfloat16 DataType;
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typedef paddle::bfloat16 data_t;
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};
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template <typename T>
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__global__ void set_value_by_id(const int *seq_lens, const bool *stop_flags, T *output_data, int *sequence_lengths, int bs, int length) {
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int tid = threadIdx.x;
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if (tid < bs) {
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T *output_data_now = output_data + tid * length;
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output_data_now[seq_lens[tid]] = 1.0;
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if (stop_flags[tid]) {
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sequence_lengths[tid] = 0;
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}
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}
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}
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template <paddle::DataType D>
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std::vector<paddle::Tensor> set_mask_value(const paddle::Tensor& input_data, const paddle::Tensor& stop_flags, const paddle::Tensor& seq_lens) {
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typedef PDTraits<D> traits_;
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typedef typename traits_::DataType DataType_;
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typedef typename traits_::data_t data_t;
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PD_CHECK(seq_lens.dtype() == paddle::DataType::INT32);
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PD_CHECK(stop_flags.dtype() == paddle::DataType::BOOL);
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auto cu_stream = input_data.stream();
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std::vector<int64_t> input_data_shape = input_data.shape();
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std::vector<int64_t> seq_lens_shape = seq_lens.shape();
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auto sequence_lengths = seq_lens.copy_to(seq_lens.place(), false);
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int input_bs = input_data_shape[0];
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int length = input_data_shape[3];
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int seq_bs = seq_lens_shape[0];
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int block_size = (input_bs + 32 - 1) / 32 * 32;
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set_value_by_id<<<1, block_size, 0, cu_stream>>>(seq_lens.data<int>(),
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stop_flags.data<bool>(),
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reinterpret_cast<DataType_*>(const_cast<data_t*>(input_data.data<data_t>())),
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sequence_lengths.data<int>(), seq_bs, length);
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return {sequence_lengths};
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}
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std::vector<paddle::Tensor> SetMaskValue(const paddle::Tensor& input_data, const paddle::Tensor& stop_flags, const paddle::Tensor& seq_lens) {
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switch (input_data.type()) {
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case paddle::DataType::BFLOAT16: {
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return set_mask_value<paddle::DataType::BFLOAT16>(
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input_data,
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stop_flags,
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seq_lens
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);
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}
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case paddle::DataType::FLOAT16: {
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return set_mask_value<paddle::DataType::FLOAT16>(
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input_data,
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stop_flags,
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seq_lens
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);
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}
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case paddle::DataType::FLOAT32: {
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return set_mask_value<paddle::DataType::FLOAT32>(
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input_data,
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stop_flags,
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seq_lens
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);
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}
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default: {
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PD_THROW(
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"NOT supported data type. "
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"Only float16, bfloat16 and float32 are supported. ");
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break;
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}
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}
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}
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std::vector<std::vector<int64_t>> SetMaskValueInferShape(const std::vector<int64_t>& input_data_shape, const std::vector<int64_t>& stop_flags_shape, const std::vector<int64_t>& seq_lens_shape) {
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return {seq_lens_shape};
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}
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std::vector<paddle::DataType> SetMaskValueInferDtype(const paddle::DataType& input_data_dtype, const paddle::DataType& stop_flags_dtype, const paddle::DataType& seq_lens_dtype) {
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return {seq_lens_dtype};
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}
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PD_BUILD_STATIC_OP(set_mask_value)
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.Inputs({"input_data", "stop_flags", "seq_lens"})
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.Outputs({"sequence_lengths"})
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.SetKernelFn(PD_KERNEL(SetMaskValue))
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.SetInferShapeFn(PD_INFER_SHAPE(SetMaskValueInferShape))
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.SetInferDtypeFn(PD_INFER_DTYPE(SetMaskValueInferDtype));
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