class_docstr: Masks extracted features as described in Section 3.1 of
  :cite:t:`https://doi.org/10.48550/arxiv.2006.11477`.
class_docstr_tok: ["Masks","extracted","features","as","described","in","Section","3.1","of",":","cite",":","t",":","`","https",":","\/\/doi.org\/10.48550\/arxiv.2006.11477","`","."]
docstr: Reset the parameters and buffers of the module.
docstr_tok: ["Reset","the","parameters","and","buffers","of","the","module","."]
code: def reset_parameters(self) -> None:
      """Reset the parameters and buffers of the module."""
      nn.init.uniform_(self.temporal_mask_embed)
  
file_path: fairseq2/src/fairseq2/models/wav2vec2/masker.py
imports: from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import Module, Parameter
  from fairseq2.nn.padding import PaddingMask
  from fairseq2.nn.utils.mask import compute_row_mask
  from fairseq2.typing import DataType, Device
label_desc: Use image node_id 2 for calling the Wav2Vec2Masker obj's underlying member method code with example usage: obj.reset_parameters() without return types