code: def __init__(self, config, layer_id=0):
      super().__init__()
      self.config = config
      kernel_loaded = (
          rwkv_cuda_kernel is not None
          and rwkv_cuda_kernel.max_seq_length == config.context_length
      )
      if (
          is_ninja_available()
          and is_torch_cuda_available()
          and not kernel_loaded
      ):
          try:
              load_wkv_cuda_kernel(config.context_length)
          except Exception:
              logger.info(
                  "Could not load the custom CUDA kernel for RWKV attention."
              )
      self.layer_id = layer_id
      hidden_size = config.hidden_size
      attention_hidden_size = (
          config.attention_hidden_size
          if config.attention_hidden_size is not None
          else hidden_size
      )
      self.attention_hidden_size = attention_hidden_size
  
      self.time_decay = nn.Parameter(torch.empty(attention_hidden_size))
      self.time_first = nn.Parameter(torch.empty(attention_hidden_size))
  
      self.time_mix_key = nn.Parameter(torch.empty(1, 1, hidden_size))
      self.time_mix_value = nn.Parameter(torch.empty(1, 1, hidden_size))
      self.time_mix_receptance = nn.Parameter(
          torch.empty(1, 1, hidden_size)
      )
  
      self.time_shift = nn.ZeroPad2d((0, 0, 1, -1))
      self.key = nn.Linear(
          hidden_size, attention_hidden_size, bias=False
      )
      self.value = nn.Linear(
          hidden_size, attention_hidden_size, bias=False
      )
      self.receptance = nn.Linear(
          hidden_size, attention_hidden_size, bias=False
      )
      self.output = nn.Linear(
          attention_hidden_size, hidden_size, bias=False
      )
  
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 1 to create a new RwkvSelfAttention object from inherited base classes: nn with example: obj = RwkvSelfAttention(config, layer_id)