code: def __init__(
      self,
      value: float,
      clip_fn: Optional[nn.Module] = Identity(),
      *args,
      **kwargs,
  ):
      super().__init__()
      self._value = nn.Parameter(
          torch.FloatTensor(1, 3, 1, 1).fill_(value)
      )
      self.clip_fn = clip_fn
  
imports: from typing import Any, Optional
  import torch
  from torch import Tensor, nn
label_desc: Use image node_id 1 to create a new FixedSampler object from inherited base classes: nn with example: obj = FixedSampler(value, clip_fn)