class_docstr: Dynamic Chunk Training configuration object for use with transformers,
  often in ASR for streaming.
  
  This object may be used both to configure masking at training time and for
  run-time configuration of DynChunkTrain-ready models.
docstr: Returns true if the left context is infinite (i.e. any chunk can
  attend to any past frame).
docstr_tok: ["Returns","true","if","the","left","context","is","infinite","(","i.e",".","any","chunk","can","attend","to","any","past","frame",")","."]
code: def is_infinite_left_context(self) -> bool:
      """Returns true if the left context is infinite (i.e. any chunk can
      attend to any past frame)."""
      return self.left_context_size is None
  
file_path: speechbrain/speechbrain/utils/dynamic_chunk_training.py
imports: import speechbrain
  from dataclasses import dataclass
  from typing import Optional
  import torch
label_desc: Use image node_id 1 for calling the DynChunkTrainConfig obj's underlying member method code with example usage: obj.is_infinite_left_context() and returns: unknown