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90 lines
3.0 KiB
Plaintext
90 lines
3.0 KiB
Plaintext
// Copyright (c) 2024 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 "helper.h"
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template <int THREADBLOCK_SIZE>
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__global__ void update_inputs_beam_kernel(
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int *seq_lens_this_time,
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int *seq_lens_encoder,
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int64_t *input_ids,
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float *logits,
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const int bsz,
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const int seq_len,
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const int hidden_size,
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const int beam_width) {
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int thread_idx = threadIdx.x;
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int block_idx = blockIdx.x;
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if (thread_idx < bsz) {
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int bsz_index = thread_idx / beam_width * beam_width;
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if (seq_lens_encoder[bsz_index] > 0) {
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if (block_idx == 0) {
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seq_lens_this_time[thread_idx] = seq_lens_this_time[bsz_index];
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seq_lens_encoder[thread_idx] = seq_lens_encoder[bsz_index];
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}
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if (block_idx < seq_len) {
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input_ids[thread_idx * seq_len + block_idx] = input_ids[bsz_index * seq_len + block_idx];
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}
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logits[thread_idx * hidden_size + block_idx] = logits[bsz_index * hidden_size + block_idx];
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}
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}
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__syncthreads();
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}
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void UpdateInputesBeam(
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const paddle::Tensor& beam_width,
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const paddle::Tensor& seq_lens_this_time,
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const paddle::Tensor& seq_lens_encoder,
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const paddle::Tensor& input_ids,
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const paddle::Tensor& logits) {
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int beam_width_scalar = beam_width.data<int>()[0];
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if (beam_width_scalar > 1) {
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const int bsz = seq_lens_this_time.shape()[0];
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const int seq_len = input_ids.shape()[1];
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const int hidden_size = logits.shape()[1];
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update_inputs_beam_kernel<1024><<<hidden_size, 1024, 0, input_ids.stream()>>>(
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const_cast<int*>(seq_lens_this_time.data<int>()),
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const_cast<int*>(seq_lens_encoder.data<int>()),
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const_cast<int64_t*>(input_ids.data<int64_t>()),
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const_cast<float*>(logits.data<float>()),
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bsz,
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seq_len,
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hidden_size,
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beam_width_scalar
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);
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}
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}
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PD_BUILD_STATIC_OP(update_inputs_beam)
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.Inputs({"beam_width",
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"seq_lens_this_time",
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"seq_lens_encoder",
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"input_ids",
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"logits"})
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.Outputs({"seq_lens_this_time_out",
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"seq_lens_encoder_out",
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"input_ids_out",
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"logits_out"})
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.SetInplaceMap({{"seq_lens_this_time", "seq_lens_this_time_out"},
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{"seq_lens_encoder", "seq_lens_encoder_out"},
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{"input_ids", "input_ids_out"},
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{"logits", "logits_out"}})
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.SetKernelFn(PD_KERNEL(UpdateInputesBeam));
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