class_docstr: Samples elements from a given list of indices.
  Args:
      indices (sequence): a sequence of indices
class_docstr_tok: ["Samples","elements","from","a","given","list","of","indices",".","Args",":","indices","(","sequence",")",":","a","sequence","of","indices"]
code: def __init__(self, indices: Sequence[int]) -> None:
      self.indices = indices
  
imports: from typing import Iterator, Sequence
  from torch.utils.data.sampler import Sampler
label_desc: Use image node_id 1 to create a new FixedSampler object from inherited base classes: Sampler with example: obj = FixedSampler(indices)