code: def __init__(self, c, c_timestep):
      super().__init__()
      linear_cls = (
          nn.Linear if USE_PEFT_BACKEND else LoRACompatibleLinear
      )
      self.mapper = linear_cls(c_timestep, c * 2)
  
imports: import torch
  import torch.nn
  from ...models.attention_processor import Attention
  from ...models.lora import LoRACompatibleConv, LoRACompatibleLinear
  from ...utils import USE_PEFT_BACKEND
label_desc: Use image node_id 1 to create a new TimestepBlock object from inherited base classes: nn with example: obj = TimestepBlock(c, c_timestep)