code: def backward(ctx, g_output, g_state=None):
      input_dtype = ctx.input_dtype
  
      time_decay, time_first, key, value, output = ctx.saved_tensors
      # The CUDA kernel will fill those tensors.
      g_time_decay = torch.empty_like(
          time_decay,
          memory_format=torch.contiguous_format,
          dtype=torch.bfloat16
          if input_dtype == torch.bfloat16
          else torch.float32,
      )
      g_time_first = torch.empty_like(
          time_first, memory_format=torch.contiguous_format
      )
      g_key = torch.empty_like(
          key, memory_format=torch.contiguous_format
      )
      g_value = torch.empty_like(
          value, memory_format=torch.contiguous_format
      )
  
      if input_dtype == torch.float16:
          g_output = g_output.float()
      backward_func = (
          rwkv_cuda_kernel.backward_bf16
          if input_dtype == torch.bfloat16
          else rwkv_cuda_kernel.backward
      )
      backward_func(
          time_decay,
          time_first,
          key,
          value,
          output,
          g_output.contiguous(),
          g_time_decay,
          g_time_first,
          g_key,
          g_value,
      )
  
      return (
          g_time_decay.to(input_dtype),
          g_time_first.to(input_dtype),
          g_key.to(input_dtype),
          g_value.to(input_dtype),
          None,
          None,
      )
  
imports: import math
  from dataclasses import dataclass
  from pathlib import Path
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from ...modeling_utils import PreTrainedModel
  from ...utils import ModelOutput, add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, is_bitsandbytes_available, is_ninja_available, is_torch_cuda_available, logging
  from .configuration_rwkv import RwkvConfig
label_desc: Use image node_id 2 for calling the RwkvLinearAttention obj's underlying member method code with example usage: obj.backward(ctx, g_output, g_state) and returns: g_time_decay,  g_time_first,  g_key,  g_value,  None,  None