src/transformers/models/wav2vec2/modeling_wav2vec2.py/Wav2Vec2PreTrainedModel/_init_weights
class Wav2Vec2PreTrainedModel:    def _init_weights(self, module):
        """Initialize the weights"""
        # gumbel softmax requires special init
        if isinstance(module, Wav2Vec2GumbelVectorQuantizer):
            module.weight_proj.weight.data.normal_(mean=0.0, std=1)
            module.weight_proj.bias.data.zero_()
            nn.init.uniform_(module.codevectors)
        elif isinstance(module, nn.Linear):
            # Slightly different from the TF version which uses truncated_normal for initialization
            # cf https://github.com/pytorch/pytorch/pull/5617
            module.weight.data.normal_(mean=0.0, std=self.config.initializer_range)
        elif isinstance(module, (nn.LayerNorm, nn.GroupNorm)):
            module.bias.data.zero_()
            module.weight.data.fill_(1.0)
        elif isinstance(module, nn.Conv1d):
            nn.init.kaiming_normal_(module.weight.data)

        if isinstance(module, (nn.Linear, nn.Conv1d)) and module.bias is not None:
            module.bias.data.zero_()