src/transformers/models/unispeech/modeling_unispeech.py/UniSpeechModel/__init__
class UniSpeechModel:    def __init__(self, config: UniSpeechConfig):
        super().__init__(config)
        self.config = config
        self.feature_extractor = UniSpeechFeatureEncoder(config)
        self.feature_projection = UniSpeechFeatureProjection(config)

        if config.mask_time_prob > 0.0 or config.mask_feature_prob > 0.0:
            self.masked_spec_embed = nn.Parameter(torch.FloatTensor(config.hidden_size).uniform_())

        if config.do_stable_layer_norm:
            self.encoder = UniSpeechEncoderStableLayerNorm(config)
        else:
            self.encoder = UniSpeechEncoder(config)

        # Initialize weights and apply final processing
        self.post_init()