
    Uhz$                         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e      Zy)    )ListUnion   )GenerationConfig)is_torch_available   )PipelineN)%MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING)SpeechT5HifiGanzmicrosoft/speecht5_hifiganc                        e Zd ZdZdZ ed      Zddd fd
Zd Zd	 Z	d
e
eee   f   f fdZ	 	 	 ddZd Z x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   )max_new_tokensN)vocodersampling_ratec                   t        |   |i | | j                  dk(  rt        d      d | _        | j
                  j                  t        j                         v rE|<t        j                  t              j                  | j
                  j                        n|| _        || _        | j                  %| j                  j                  j                  | _        | j                  || j
                  j                  }| j
                  j                   j#                  dd       }||j%                  |j'                                dD ]  }t)        ||d       }||| _         y y )Ntfz5The TextToAudioPipeline is only available in PyTorch.generation_config)sample_rater   )super__init__	framework
ValueErrorr   model	__class__r
   valuesr   from_pretrainedDEFAULT_VOCODER_IDtodevicer   config__dict__getupdateto_dictgetattr)	selfr   r   argskwargsr!   
gen_configsampling_rate_namer   s	           v/var/www/catia.catastroantioquia-mas.com/valormas/lib/python3.12/site-packages/transformers/pipelines/text_to_audio.pyr   zTextToAudioPipeline.__init__Y   s:   $)&)>>T!TUU::#H#O#O#QQ ?  //0BCFFtzzGXGXY L +<<#!%!4!4!B!BD% ZZ&&F,,001DdKJ%j0023&F 7" '0BD I ,)6D&7 &    c                    t        |t              r|g}| j                  j                  j                  dk(  r?| j
                  j                  j                  dd      ddddd}|j                  |       |} | j                  |fi |dd	i}|S )
Nbarkmax_input_semantic_lengthr   FT
max_length)r1   add_special_tokensreturn_attention_maskreturn_token_type_idspaddingreturn_tensorspt)

isinstancestrr   r!   
model_typer   semantic_configr#   r$   	tokenizer)r'   textr)   
new_kwargsoutputs        r,   
preprocesszTextToAudioPipeline.preprocessx   s    dC 6D::''61 #44DDHHIdfij&+)-).'J f%FDDtDr-   c                    | j                  || j                        }|d   }|d   }| j                  j                         r`| j                  || j                        }d|vr| j                  |d<   |j                  |        | j                  j                  di ||}n>t        |      rt        d|j                                 | j                  di ||d   }| j                  | j                  |      }|S )N)r    forward_paramsgenerate_kwargsr   zYou're using the `TextToAudioPipeline` with a forward-only model, but `generate_kwargs` is non empty. For forward-only TTA models, please use `forward_params` instead of `generate_kwargs`. For reference, the `generate_kwargs` used here are: r    )_ensure_tensor_on_devicer    r   can_generater   r$   generatelenr   keysr   )r'   model_inputsr)   rB   rC   r?   s         r,   _forwardzTextToAudioPipeline._forward   s   ..vdkk.J 01 !23::""$";;OTXT_T_;`O #/97;7M7M 34 !!/2(TZZ((J<J>JF?# KKZK_K_KaJbd 
  TZZA,A.A!DF<<#\\&)Fr-   text_inputsc                 $    t        |   |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'   rL   rB   r   s      r,   rN   zTextToAudioPipeline.__call__   s    , w>~>>r-   c                     t        | dd       | j                  |d<   t        | dd       | j                  |d<   | j                  |d<   |r|ni |r|ni d}|i }i }|||fS )Nassistant_modelassistant_tokenizerr<   )rB   rC   )r&   rP   r<   rQ   )r'   preprocess_paramsrB   rC   paramspostprocess_paramss         r,   _sanitize_parametersz(TextToAudioPipeline._sanitize_parameters   s     4*D1=151E1EO-.4.5A+/>>OK(595M5MO12 1?nB2Ar

 $ " &*<<<r-   c                     i }t        |t              r|d   }nt        |t              r|d   }|j                  dt        j
                        j                         |d<   | j                  |d<   |S )Nwaveformr   cpu)r    dtypeaudior   )r8   dicttupler   torchfloatnumpyr   )r'   rW   output_dicts      r,   postprocesszTextToAudioPipeline.postprocess   sh    h%
+H%({H'{{%u{{{KQQSG'+'9'9O$r-   )NNN)__name__
__module____qualname____doc___pipeline_calls_generater   _default_generation_configr   r@   rK   r   r9   r   rN   rU   ra   __classcell__)r   s   @r,   r   r      sd    2h  $!1" '+$ 7>.B?E#tCy.$9 ?4 	=.	r-   r   )typingr   r   
generationr   utilsr   baser	   r]   models.auto.modeling_autor
   !models.speecht5.modeling_speecht5r   r   r   rD   r-   r,   <module>ro      s8     ) &  QC1 J( Jr-   