def METHOD_NAME(self, pre_alloc_tensor: torch.Tensor = None):
    """
    Map the parameters in the region to a contiguous memory space.
    """
    self.fp16_data = torch.zeros(self.param_num, dtype=torch.half, device='cuda')
    offset = 0
    for param in self.fp16_params:
        param.data = param.data.cuda()
        p_num = param.data.numel()
        self.fp16_data[offset:offset + p_num].copy_(param.data.flatten())
        param.data = self.fp16_data[offset:offset + p_num].view(param.data.shape)
        self.param_to_range[param] = (offset, offset + p_num)
        offset += p_num
    self.fp32_data = self.fp16_data.float().cpu().pin_memory()
    free_storage(self.fp16_data)
    if self.in_mem_pool_flag and pre_alloc_tensor is not None:
        self.fp16_data = pre_alloc_tensor