src/transformers/models/wav2vec2/modeling_flax_wav2vec2.py/FlaxWav2Vec2ForPreTrainingModule/__call__
class FlaxWav2Vec2ForPreTrainingModule:    def __call__(
        self,
        input_values,
        attention_mask=None,
        mask_time_indices=None,
        gumbel_temperature: int = 1,
        deterministic: bool = True,
        output_attentions=None,
        output_hidden_states=None,
        freeze_feature_encoder=False,
        return_dict=None,
    ):
        r"""
        Returns:

        Example:

        ```python

        ```"""

        return_dict = return_dict if return_dict is not None else self.config.use_return_dict

        outputs = self.wav2vec2(
            input_values,
            attention_mask=attention_mask,
            output_attentions=output_attentions,
            output_hidden_states=output_hidden_states,
            mask_time_indices=mask_time_indices,
            deterministic=deterministic,
            freeze_feature_encoder=freeze_feature_encoder,
            return_dict=return_dict,
        )

        # project all transformed features (including masked) to final vq dim
        transformer_features = self.project_hid(outputs[0])

        # quantize all (unmasked) extracted features and project to final vq dim
        extract_features = self.dropout_features(outputs[1], deterministic=deterministic)
        quantized_features, codevector_perplexity = self.quantizer(
            extract_features, mask_time_indices, deterministic=deterministic, temperature=gumbel_temperature
        )
        quantized_features = self.project_q(quantized_features)

        if not return_dict:
            return (transformer_features, quantized_features, codevector_perplexity) + outputs[2:]

        return FlaxWav2Vec2ForPreTrainingOutput(
            projected_states=transformer_features,
            projected_quantized_states=quantized_features,
            codevector_perplexity=codevector_perplexity,
            hidden_states=outputs.hidden_states,
            attentions=outputs.attentions,
        )