FastDeploy/custom_ops/gpu_ops/get_padding_offset.cu

// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "paddle/extension.h"
#include "helper.h"

#ifndef PD_BUILD_STATIC_OP
#define PD_BUILD_STATIC_OP(name) PD_BUILD_OP(static_op_##name)
#endif

__global__ void RemovePadding(int64_t *output_data,
                              const int64_t *input_data,
                              const int *seq_lens,
                              const int *cum_offsets,
                              const int sequence_length) {
    const int bi = blockIdx.x;
    const int tid = threadIdx.x;

    for (int i = tid; i < seq_lens[bi]; i += blockDim.x) {
        const int tgt_seq_id = bi * sequence_length - cum_offsets[bi] + i;
        const int src_seq_id = bi * sequence_length + i;
        output_data[tgt_seq_id] = input_data[src_seq_id];
    }
}

__global__ void GetPaddingOffsetKernel(int *batch_id_per_token,
                                       int *cum_offsets_out,
                                       int *cu_seqlens_q,
                                       int *cu_seqlens_k,
                                       const int *cum_offsets,
                                       const int *seq_lens,
                                       const int max_seq_len) {
    // get padding offset of each batch
    const int bi = blockIdx.x;
    const int ti = threadIdx.x;
    int cum_offset = bi == 0 ? 0 : cum_offsets[bi - 1];
    for (int i = ti; i < seq_lens[bi]; i += blockDim.x) {
        batch_id_per_token[bi * max_seq_len - cum_offset + i] = bi;
    }
    if (ti == 0) {
        cum_offsets_out[bi] = cum_offset;
        int cum_seq_len = (bi + 1) * max_seq_len - cum_offsets[bi];
        cu_seqlens_q[bi + 1] = cum_seq_len;
        cu_seqlens_k[bi + 1] = cum_seq_len;
    }
}

std::vector<paddle::Tensor> GetPaddingOffset(const paddle::Tensor &input_ids,
                                             const paddle::Tensor &cum_offsets,
                                             const paddle::Tensor &token_num,
                                             const paddle::Tensor &seq_len) {
#ifdef PADDLE_WITH_CUSTOM_DEVICE
    auto dev_ctx = static_cast<const phi::CustomContext*>(paddle::experimental::DeviceContextPool::Instance().Get(input_ids.place()));
    auto cu_stream = dev_ctx->stream();
#else
    auto cu_stream = input_ids.stream();
#endif
    std::vector<int64_t> input_ids_shape = input_ids.shape();
    const int bsz = seq_len.shape()[0];
    const int seq_length = input_ids_shape[1];
    auto cum_offsets_out = cum_offsets.copy_to(cum_offsets.place(), false);
    auto cpu_token_num = token_num.copy_to(paddle::CPUPlace(), false);

    const int token_num_data = cpu_token_num.data<int64_t>()[0];
    auto x_remove_padding = paddle::empty(
        {token_num_data}, paddle::DataType::INT64, input_ids.place());
    auto batch_id_per_token = paddle::empty(
        {token_num_data}, paddle::DataType::INT32, input_ids.place());
    auto cu_seqlens_q =
        paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
    auto cu_seqlens_k =
        paddle::full({bsz + 1}, 0, paddle::DataType::INT32, input_ids.place());
#ifdef PADDLE_WITH_COREX
    int blockSize = std::min((token_num_data + WARP_SIZE - 1) / WARP_SIZE * WARP_SIZE, 128);
#else
    int blockSize = min((token_num_data + WARP_SIZE - 1) / WARP_SIZE * WARP_SIZE, 128);
#endif
    GetPaddingOffsetKernel<<<bsz, 128, 0, cu_stream>>>(
        batch_id_per_token.data<int>(),
        cum_offsets_out.data<int>(),
        cu_seqlens_q.data<int>(),
        cu_seqlens_k.data<int>(),
        cum_offsets.data<int>(),
        seq_len.data<int>(),
        seq_length);
    RemovePadding<<<bsz, blockSize, 0, cu_stream>>>(
        x_remove_padding.data<int64_t>(),
        input_ids.data<int64_t>(),
        seq_len.data<int>(),
        cum_offsets_out.data<int>(),
        seq_length);
    return {x_remove_padding,
            batch_id_per_token,
            cu_seqlens_q,
            cu_seqlens_k};  // , enc_token_num, dec_token_num};
}

std::vector<std::vector<int64_t>> GetPaddingOffsetInferShape(
    const std::vector<int64_t> &input_ids_shape,
    const std::vector<int64_t> &cum_offsets_shape,
    const std::vector<int64_t> &token_num_shape,
    const std::vector<int64_t> &seq_len_shape) {
    int64_t bsz = seq_len_shape[0];
    int64_t seq_len = input_ids_shape[1];
    return {{-1}, {-1}, {bsz + 1}, {bsz + 1}};
}

std::vector<paddle::DataType> GetPaddingOffsetInferDtype(
    const paddle::DataType &input_ids_dtype,
    const paddle::DataType &cum_offsets_dtype,
    const paddle::DataType &token_num_dtype,
    const paddle::DataType &seq_len_dtype) {
    return {input_ids_dtype,
            seq_len_dtype,
            seq_len_dtype,
            seq_len_dtype};
}

PD_BUILD_STATIC_OP(get_padding_offset)
    .Inputs({"input_ids", "token_num", "cum_offsets", "seq_len"})
    .Outputs({"x_remove_padding",
              "batch_id_per_token",
              "cu_seqlens_q",
              "cu_seqlens_k"})
    .SetKernelFn(PD_KERNEL(GetPaddingOffset))
    .SetInferShapeFn(PD_INFER_SHAPE(GetPaddingOffsetInferShape))
    .SetInferDtypeFn(PD_INFER_DTYPE(GetPaddingOffsetInferDtype));