kvcache-ai--ktransformers/kt-kernel/operators/llamafile/linear.cpp

/**
 * @Description  :
 * @Author       : chenht2022
 * @Date         : 2024-07-12 10:07:58
 * @Version      : 1.0.0
 * @LastEditors  : kkk1nak0
 * @LastEditTime : 2024-08-15 07:45:18
 * @Copyright (c) 2024 by KVCache.AI, All Rights Reserved.
 **/
#include "linear.h"

Linear::Linear(LinearConfig config) {
  config_ = config;
  proj_ = config_.proj;

  MemoryRequest mem_requests;
  mem_requests.append_pointer(&input_fp32_, sizeof(float) * config_.group_max_len * config_.input_size);
  mem_requests.append_pointer(&proj_input_,
                              config_.group_max_len * config_.input_size *
                                  ggml_type_size(ggml_internal_get_type_traits(config_.proj_type).vec_dot_type) /
                                  ggml_blck_size(ggml_internal_get_type_traits(config_.proj_type).vec_dot_type));
  mem_requests.append_pointer(&proj_output_, sizeof(float) * config_.group_max_len * config_.output_size);
  shared_mem_buffer.alloc(this, mem_requests);
}

Linear::~Linear() {}

void Linear::warm_up(WorkerPool* backend) {
  std::vector<float> input_fp32(config_.input_size);
  std::vector<uint8_t> input(config_.input_size * ggml_type_size(config_.hidden_type) /
                             ggml_blck_size(config_.hidden_type));
  std::vector<uint8_t> output(config_.output_size * ggml_type_size(config_.hidden_type) /
                              ggml_blck_size(config_.hidden_type));
  for (int i = 0; i < config_.input_size; i++) {
    input_fp32[i] = 0;
  }
  from_float(input_fp32.data(), input.data(), config_.input_size, config_.hidden_type);
  forward_many(1, input.data(), output.data(), backend);
}

void Linear::forward_many(int qlen, const void* input, void* output, WorkerPool* backend) {
  const void* proj_input_ptr;
  if (config_.hidden_type == ggml_internal_get_type_traits(config_.proj_type).vec_dot_type) {
    proj_input_ptr = input;
  } else {
    to_float(input, input_fp32_, qlen * config_.input_size, config_.hidden_type);
    from_float(input_fp32_, proj_input_, qlen * config_.input_size,
               ggml_internal_get_type_traits(config_.proj_type).vec_dot_type);
    proj_input_ptr = proj_input_;
  }
  int nth = config_.output_size / config_.stride;
  backend->do_work_stealing_job(
      nth, nullptr,
      [&](int task_id) {
        int ith = task_id;
        void* proj_ptr = (uint8_t*)proj_ + ith * config_.stride * config_.input_size *
                                               ggml_type_size(config_.proj_type) / ggml_blck_size(config_.proj_type);
        float* proj_output_ptr = proj_output_ + ith * config_.stride;
        llamafile_sgemm(config_.stride, qlen, config_.input_size / ggml_blck_size(config_.proj_type), proj_ptr,
                        config_.input_size / ggml_blck_size(config_.proj_type), proj_input_ptr,
                        config_.input_size / ggml_blck_size(config_.proj_type), proj_output_ptr, config_.output_size, 0,
                        1, GGML_TASK_TYPE_COMPUTE, config_.proj_type,
                        ggml_internal_get_type_traits(config_.proj_type).vec_dot_type, GGML_TYPE_F32,
                        GGML_PREC_DEFAULT);
        if (config_.stride % ggml_blck_size(config_.hidden_type) == 0) {
          for (int i = 0; i < qlen; i++) {
            float* output_fp32_ptr = proj_output_ + i * config_.output_size + ith * config_.stride;
            void* output_ptr =
                (uint8_t*)output +
                i * config_.output_size * ggml_type_size(config_.hidden_type) / ggml_blck_size(config_.hidden_type) +
                ith * config_.stride * ggml_type_size(config_.hidden_type) / ggml_blck_size(config_.hidden_type);
            from_float(output_fp32_ptr, output_ptr, config_.stride, config_.hidden_type);
          }
        }
      },
      nullptr);
  if (config_.stride % ggml_blck_size(config_.hidden_type) != 0) {
    from_float(proj_output_, output, qlen * config_.output_size, config_.hidden_type);
  }
}

void Linear::forward(int qlen, const void* input, void* output, WorkerPool* backend) {
  if (qlen <= 0) {
    return;
  }
  int forward_len = std::min(qlen, config_.group_max_len);
  forward_many(forward_len, input, output, backend);
  forward(qlen - forward_len,
          (uint8_t*)input + forward_len * config_.input_size * ggml_type_size(config_.hidden_type) /
                                ggml_blck_size(config_.hidden_type),
          (uint8_t*)output + forward_len * config_.output_size * ggml_type_size(config_.hidden_type) /
                                 ggml_blck_size(config_.hidden_type),
          backend);
}