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https://github.com/PaddlePaddle/FastDeploy.git
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453487d5b0
* delete dynamic control flow for decode * coda-style * fix scatter/gather typos and use input stream instead default stream * support 0-Size Tensor * update runner and model * using static mem address as input * fix mem leak * refine code * update mm_buffer * fix typo * fix buffersize * fix unk token * refine code * refine * support other arch * open cudagraph in vlci * fix * update * update * update * fix cmd * update --------- Co-authored-by: aquagull <hongyuh@qq.com> Co-authored-by: Yuanle Liu <yuanlehome@163.com>
69 lines
2.2 KiB
Plaintext
69 lines
2.2 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 "helper.h"
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template <int VecSize>
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__global__ void text_image_index_out_kernel(
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const int32_t* token_type_ids,
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int32_t* text_index,
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int32_t* image_index,
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const int64_t token_num
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) {
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int global_thread_idx = blockDim.x * blockIdx.x + threadIdx.x;
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if (global_thread_idx >= 1) return;
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int text_count = 0;
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int images_count = 0;
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for (int i = 0; i < token_num; ++i) {
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// printf(" %d %d %d %d \n", text_index[i], text_count, images_count, i);
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if (token_type_ids[i] == 0) {
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text_index[i] = text_count;
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text_count += 1;
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} else if (token_type_ids[i] == 1) {
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image_index[i] = images_count;
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images_count += 1;
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} else {
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// skip cuda graph padding value
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continue;
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}
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}
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}
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void TextImageIndexOut(
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const paddle::Tensor& token_type_ids,
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paddle::Tensor& text_index,
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paddle::Tensor& image_index) {
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const int64_t token_num = token_type_ids.shape()[0];
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auto stream = token_type_ids.stream();
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text_image_index_out_kernel<1><<<1, 1, 0, stream>>>(
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token_type_ids.data<int32_t>(),
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text_index.data<int32_t>(),
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image_index.data<int32_t>(),
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token_num
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);
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}
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PD_BUILD_STATIC_OP(text_image_index_out)
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.Inputs({"token_type_ids",
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"text_index",
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"image_index"})
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.Outputs({"text_index_out",
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"image_index_out"})
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.SetInplaceMap({{"text_index", "text_index_out"},
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{"image_index", "image_index_out"}})
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.SetKernelFn(PD_KERNEL(TextImageIndexOut));
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