code: def forward(
      self,
      sample_shape=(),
      data_type=torch.float,
      device=torch.device("cpu"),
  ) -> Tensor:
      # sample values from uniform distribution
      return self.clip_fn(self._value)
  
imports: from typing import Any, Optional
  import torch
  from torch import Tensor, nn
label_desc: Use image node_id 2 for calling the FixedSampler obj's underlying member method code with example usage: obj.forward(sample_shape, data_type, device) and returns: self