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https://github.com/PaddlePaddle/FastDeploy.git
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94 lines
4.1 KiB
C++
94 lines
4.1 KiB
C++
// 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 "paddle/extension.h"
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void update_inputs_kernel(bool *not_need_stop,
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int *seq_lens_this_time,
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int *seq_lens_encoder,
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int *seq_lens_decoder,
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int64_t *input_ids,
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const int64_t *stop_nums,
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const bool *stop_flags,
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const bool *is_block_step,
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const int64_t *next_tokens,
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const int bsz,
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const int input_ids_stride) {
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int64_t stop_sum = 0;
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for (int bi = 0; bi < bsz; ++bi) {
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bool stop_flag_now = false;
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int64_t stop_flag_now_int = 0;
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stop_flag_now = stop_flags[bi];
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stop_flag_now_int = static_cast<int64_t>(stop_flag_now);
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auto seq_len_this_time = seq_lens_this_time[bi];
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auto seq_len_encoder = seq_lens_encoder[bi];
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auto seq_len_decoder = seq_lens_decoder[bi];
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seq_lens_decoder[bi] =
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stop_flag_now ? 0
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: (seq_len_decoder == 0 ? seq_len_encoder
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: seq_len_decoder + 1);
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seq_lens_this_time[bi] = stop_flag_now ? 0 : 1;
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seq_lens_encoder[bi] = 0;
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int64_t *input_ids_now = input_ids + bi * input_ids_stride;
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input_ids_now[0] = next_tokens[bi];
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stop_sum += stop_flag_now_int;
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}
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not_need_stop[0] = stop_sum < stop_nums[0];
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}
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void UpdateInputes(const paddle::Tensor &stop_flags,
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const paddle::Tensor ¬_need_stop,
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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 &seq_lens_decoder,
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const paddle::Tensor &input_ids,
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const paddle::Tensor &stop_nums,
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const paddle::Tensor &next_tokens,
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const paddle::Tensor &is_block_step) {
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const int bsz = input_ids.shape()[0];
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const int input_ids_stride = input_ids.shape()[1];
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update_inputs_kernel(const_cast<bool *>(not_need_stop.data<bool>()),
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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<int *>(seq_lens_decoder.data<int>()),
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const_cast<int64_t *>(input_ids.data<int64_t>()),
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stop_nums.data<int64_t>(),
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stop_flags.data<bool>(),
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is_block_step.data<bool>(),
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next_tokens.data<int64_t>(),
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bsz,
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input_ids_stride);
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}
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PD_BUILD_STATIC_OP(update_inputs_cpu)
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.Inputs({"stop_flags",
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"not_need_stop",
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"seq_lens_this_time",
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"seq_lens_encoder",
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"seq_lens_decoder",
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"input_ids",
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"stop_nums",
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"next_tokens",
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"is_block_step"})
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.Outputs({"not_need_stop_out",
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"seq_lens_this_time_out",
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"seq_lens_encoder_out",
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"seq_lens_decoder_out",
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"input_ids_out"})
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.SetInplaceMap({{"not_need_stop", "not_need_stop_out"},
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{"seq_lens_this_time", "seq_lens_this_time_out"},
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{"seq_lens_encoder", "seq_lens_encoder_out"},
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{"seq_lens_decoder", "seq_lens_decoder_out"},
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{"input_ids", "input_ids_out"}})
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.SetKernelFn(PD_KERNEL(UpdateInputes));
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