class_docstr: Encoder module definition.
  
  Args:
      input_size: Input size.
      body_conf: Encoder body configuration.
      input_conf: Encoder input configuration.
      main_conf: Encoder main configuration.
docstr: Initialize/Reset encoder cache for streaming.
  
  Args:
      left_context: Number of previous frames (AFTER subsampling) the attention
                    module can see in current chunk.
      device: Device ID.
code: def reset_cache(
      self, left_context: int, device: torch.device
  ) -> None:
      """Initialize/Reset encoder cache for streaming.
  
      Args:
          left_context: Number of previous frames (AFTER subsampling) the attention
                        module can see in current chunk.
          device: Device ID.
  
      """
      return self.encoders.reset_streaming_cache(left_context, device)
  
file_path: espnet/espnet2/asr_transducer/encoder/encoder.py
imports: from typing import Any, Dict, List, Tuple
  import torch
  from typeguard import check_argument_types
  from espnet2.asr_transducer.encoder.building import build_body_blocks, build_input_block, build_main_parameters, build_positional_encoding
  from espnet2.asr_transducer.encoder.validation import validate_architecture
  from espnet2.asr_transducer.utils import TooShortUttError, check_short_utt, make_chunk_mask, make_source_mask
label_desc: Use image node_id 2 for calling the Encoder obj's underlying member method code with example usage: obj.reset_cache(left_context, device) and returns: self