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    Zhz$                     @   sr   d dl mZmZ ddlmZ ddlmZ ddlmZ e r-d dl	Z	ddl
mZ dd	lmZ d
ZG dd deZdS )    )ListUnion   )GenerationConfig)is_torch_available   )PipelineN)%MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING)SpeechT5HifiGanzmicrosoft/speecht5_hifiganc                       s|   e Zd ZdZdZeddZddd fdd
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eee f f fddZ			dddZdd Z  ZS )TextToAudioPipelinea  
    Text-to-audio generation pipeline using any `AutoModelForTextToWaveform` or `AutoModelForTextToSpectrogram`. This
    pipeline generates an audio file from an input text and optional other conditional inputs.

    Unless the model you're using explicitly sets these generation parameters in its configuration files
    (`generation_config.json`), the following default values will be used:
    - max_new_tokens: 256

    Example:

    ```python
    >>> from transformers import pipeline

    >>> pipe = pipeline(model="suno/bark-small")
    >>> output = pipe("Hey it's HuggingFace on the phone!")

    >>> audio = output["audio"]
    >>> sampling_rate = output["sampling_rate"]
    ```

    Learn more about the basics of using a pipeline in the [pipeline tutorial](../pipeline_tutorial)

    <Tip>

    You can specify parameters passed to the model by using [`TextToAudioPipeline.__call__.forward_params`] or
    [`TextToAudioPipeline.__call__.generate_kwargs`].

    Example:

    ```python
    >>> from transformers import pipeline

    >>> music_generator = pipeline(task="text-to-audio", model="facebook/musicgen-small", framework="pt")

    >>> # diversify the music generation by adding randomness with a high temperature and set a maximum music length
    >>> generate_kwargs = {
    ...     "do_sample": True,
    ...     "temperature": 0.7,
    ...     "max_new_tokens": 35,
    ... }

    >>> outputs = music_generator("Techno music with high melodic riffs", generate_kwargs=generate_kwargs)
    ```

    </Tip>

    This pipeline can currently be loaded from [`pipeline`] using the following task identifiers: `"text-to-speech"` or
    `"text-to-audio"`.

    See the list of available models on [huggingface.co/models](https://huggingface.co/models?filter=text-to-speech).
    T   )Zmax_new_tokensN)vocodersampling_ratec                   s   t  j|i | | jdkrtdd | _| jjt v r.|d u r+t	
t| jjn|| _|| _| jd ur<| jjj| _| jd u rj| jj}| jjdd }|d urX||  dD ]}t||d }|d uri|| _qZd S d S )Ntfz5The TextToAudioPipeline is only available in PyTorch.generation_config)Zsample_rater   )super__init__Z	framework
ValueErrorr   model	__class__r	   valuesr
   Zfrom_pretrainedDEFAULT_VOCODER_IDtodevicer   config__dict__getupdateto_dictgetattr)selfr   r   argskwargsr   Z
gen_configZsampling_rate_namer    S/var/www/auris/lib/python3.10/site-packages/transformers/pipelines/text_to_audio.pyr   Y   s0   


zTextToAudioPipeline.__init__c                 K   sf   t |tr|g}| jjjdkr$| jjddddddd}|| |}| j	|fi |dd	i}|S )
NZbarkZmax_input_semantic_lengthr   FT
max_length)r&   Zadd_special_tokensZreturn_attention_maskZreturn_token_type_idspaddingZreturn_tensorspt)

isinstancestrr   r   Z
model_typer   Zsemantic_configr   r   	tokenizer)r    textr"   Z
new_kwargsoutputr$   r$   r%   
preprocessx   s   

	zTextToAudioPipeline.preprocessc                 K   s   | j || jd}|d }|d }| j r7| j || jd}d|vr&| j|d< || | jjdi ||}nt|rDtd|	  | jdi ||d }| j
d urZ| 
|}|S )N)r   forward_paramsgenerate_kwargsr   zYou're using the `TextToAudioPipeline` with a forward-only model, but `generate_kwargs` is non empty. For forward-only TTA models, please use `forward_params` instead of `generate_kwargs`. For reference, the `generate_kwargs` used here are: r   r$   )Z_ensure_tensor_on_devicer   r   Zcan_generater   r   generatelenr   keysr   )r    Zmodel_inputsr"   r/   r0   r-   r$   r$   r%   _forward   s&   




zTextToAudioPipeline._forwardtext_inputsc                    s   t  j|fi |S )a  
        Generates speech/audio from the inputs. See the [`TextToAudioPipeline`] documentation for more information.

        Args:
            text_inputs (`str` or `List[str]`):
                The text(s) to generate.
            forward_params (`dict`, *optional*):
                Parameters passed to the model generation/forward method. `forward_params` are always passed to the
                underlying model.
            generate_kwargs (`dict`, *optional*):
                The dictionary of ad-hoc parametrization of `generate_config` to be used for the generation call. For a
                complete overview of generate, check the [following
                guide](https://huggingface.co/docs/transformers/en/main_classes/text_generation). `generate_kwargs` are
                only passed to the underlying model if the latter is a generative model.

        Return:
            A `dict` or a list of `dict`: The dictionaries have two keys:

            - **audio** (`np.ndarray` of shape `(nb_channels, audio_length)`) -- The generated audio waveform.
            - **sampling_rate** (`int`) -- The sampling rate of the generated audio waveform.
        )r   __call__)r    r5   r/   r#   r$   r%   r6      s   zTextToAudioPipeline.__call__c                 C   sr   t | dd d ur| j|d< t | dd d ur| j|d< | j|d< |r#|ni |r(|ni d}|d u r2i }i }|||fS )Nassistant_modelassistant_tokenizerr+   )r/   r0   )r   r7   r+   r8   )r    Zpreprocess_paramsr/   r0   paramsZpostprocess_paramsr$   r$   r%   _sanitize_parameters   s   





z(TextToAudioPipeline._sanitize_parametersc                 C   sP   i }t |tr|d }n	t |tr|d }|jdtjd |d< | j|d< |S )Nwaveformr   cpu)r   ZdtypeZaudior   )r)   dicttupler   torchfloatnumpyr   )r    r;   Zoutput_dictr$   r$   r%   postprocess   s   



zTextToAudioPipeline.postprocess)NNN)__name__
__module____qualname____doc__Z_pipeline_calls_generater   Z_default_generation_configr   r.   r4   r   r*   r   r6   r:   rB   __classcell__r$   r$   r#   r%   r      s    4!
r   )typingr   r   Z
generationr   utilsr   baser   r?   Zmodels.auto.modeling_autor	   Z!models.speecht5.modeling_speecht5r
   r   r   r$   r$   r$   r%   <module>   s   