unpack Class — pytorch Architecture

Source Code

aten/src/ATen/native/quantized/cpu/qnnpack/include/pack_block_sparse.h lines 292–330

template <typename INDICES_DTYPE>
void TypedBCSRMatrix<INDICES_DTYPE>::unpack(
    int8_t* dst,
    const int64_t num_rows,
    const int64_t num_cols,
    const uint8_t* zero_points) const {
  for (int64_t i = 0; i < num_rows; i++) {
    memset(
        dst + i * num_cols,
        static_cast<int8_t>(static_cast<int16_t>(zero_points[i]) - 128),
        num_cols * sizeof(int8_t));
  }

  const int64_t num_block_rows = static_cast<int64_t>(row_values.size()) - 1;
  const int64_t block_size = (int64_t)row_block_size * col_block_size;
  int64_t weight_values_num = 0;
  for (int64_t block_row_num = 0; block_row_num < num_block_rows;
       block_row_num++) {
    const int64_t num_blocks_in_current_block_row =
        row_values[block_row_num + 1] - row_values[block_row_num];
    for (int64_t k = 0; k < num_blocks_in_current_block_row;
         k++) { // iterate over each block in the row
      const int64_t block_start_row_num = block_row_num * row_block_size;
      const int64_t block_start_col_num =
          (int64_t)(col_indices[weight_values_num / block_size]) *
          col_block_size;
      for (int64_t l = 0; l < block_size;
           l++) { // iterate over each value in the block
        const int64_t row_num = block_start_row_num + l / col_block_size;
        const int64_t col_num = block_start_col_num + l % col_block_size;
        if (row_num < num_rows && col_num < num_cols) {
          dst[row_num * num_cols + col_num] = static_cast<int8_t>(
              static_cast<int16_t>(values[weight_values_num]) - 128);
        }
        weight_values_num++;
      }
    }
  }
}