src/transformers/models/hubert/modeling_tf_hubert.py/TFHubertFeatureEncoder/__init__
class TFHubertFeatureEncoder:    def __init__(self, config: HubertConfig, **kwargs: Any) -> None:
        super().__init__(**kwargs)

        if config.feat_extract_norm == "group":
            conv_layers = [TFHubertGroupNormConvLayer(config, layer_id=0, name=f"conv_layers.{0}")] + [
                TFHubertNoLayerNormConvLayer(config, layer_id=i + 1, name=f"conv_layers.{i+1}")
                for i in range(config.num_feat_extract_layers - 1)
            ]
        elif config.feat_extract_norm == "layer":
            conv_layers = [
                TFHubertLayerNormConvLayer(config, layer_id=i, name=f"conv_layers.{i}")
                for i in range(config.num_feat_extract_layers)
            ]
        else:
            raise ValueError(
                f"`config.feat_extract_norm` is {config.feat_extract_norm}, but has to be one of ['group', 'layer']"
            )
        self.conv_layers = conv_layers