
import multiprocessing
import os
from typing import BinaryIO, Optional, Union

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader







class      lowerCamelCase		(  A_  ):





     def __init__(self      :    str				,    _A      :    NestedDataStructureLike[PathLike]				,    _A      :    Optional[NamedSplit] = None				,    _A      :    Optional[Features] = None				,    _A      :    str = None				,    _A      :    bool = False				,    _A      :    bool = False				,    _A      :    Optional[int] = None				,    **_A      :    Optional[Any]				,    )						->						Optional[int]:
         super().__init__(
             _A				,    split=_A				,    features=_A				,    cache_dir=_A				,    keep_in_memory=_A				,    streaming=_A				,    num_proc=_A				,    **_A				,    )
         snake_case      =					path_or_paths if isinstance(_A				,    _A   ) else {self.split: path_or_paths}
         snake_case      =					Csv(
             cache_dir=_A				,    data_files=_A				,    features=_A				,    **_A				,    )





     def 		UpperCAmelCase(self      :    List[str]   )						->						Tuple:
         # Build iterable dataset
         if self.streaming:
             snake_case      =					self.builder.as_streaming_dataset(split=self.split   )
         # Build regular (map-style) dataset
         else:
             snake_case      =					None
             snake_case      =					None
             snake_case      =					None
             snake_case      =					None

             self.builder.download_and_prepare(
                 download_config=_A				,    download_mode=_A				,    verification_mode=_A				,    base_path=_A				,    num_proc=self.num_proc				,    )
             snake_case      =					self.builder.as_dataset(
                 split=self.split				,    verification_mode=_A				,    in_memory=self.keep_in_memory   )
         return dataset







class      lowerCamelCase		:





     def __init__(self      :    List[str]				,    _A      :    Dataset				,    _A      :    Union[PathLike, BinaryIO]				,    _A      :    Optional[int] = None				,    _A      :    Optional[int] = None				,    **_A      :    Any				,    )						->						Dict:
         if num_proc is not None and num_proc <= 0:
             raise ValueError(f'num_proc {num_proc} must be an integer > 0.'   )

         snake_case      =					dataset
         snake_case      =					path_or_buf
         snake_case      =					batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
         snake_case      =					num_proc
         snake_case      =					"utf-8"
         snake_case      =					to_csv_kwargs





     def 		UpperCAmelCase(self      :    Optional[int]   )						->						int:
         snake_case      =					self.to_csv_kwargs.pop("path_or_buf"				,    _A   )
         snake_case      =					self.to_csv_kwargs.pop("header"				,    _A   )
         snake_case      =					self.to_csv_kwargs.pop("index"				,    _A   )

         if isinstance(self.path_or_buf				,    (str, bytes, os.PathLike)   ):
             with open(self.path_or_buf				,    "wb+"   ) as buffer:
                 snake_case      =					self._write(file_obj=_A				,    header=_A				,    index=_A				,    **self.to_csv_kwargs   )
         else:
             snake_case      =					self._write(file_obj=self.path_or_buf				,    header=_A				,    index=_A				,    **self.to_csv_kwargs   )
         return written





     def 		UpperCAmelCase(self      :    str				,    _A      :    Union[str, Any]   )						->						List[str]:
         snake_case     ,							snake_case     ,							snake_case     ,							snake_case      =					args

         snake_case      =					query_table(
             table=self.dataset.data				,    key=slice(_A				,    offset + self.batch_size   )				,    indices=self.dataset._indices				,    )
         snake_case      =					batch.to_pandas().to_csv(
             path_or_buf=_A				,    header=header if (offset == 0) else False				,    index=_A				,    **_A   )
         return csv_str.encode(self.encoding   )





     def 		UpperCAmelCase(self      :    List[Any]				,    _A      :    BinaryIO				,    _A      :    List[str]				,    _A      :    int				,    **_A      :    Optional[int]   )						->						int:
         snake_case      =					0

         if self.num_proc is None or self.num_proc == 1:
             for offset in logging.tqdm(
                 range(0				,    len(self.dataset   )				,    self.batch_size   )				,    unit="ba"				,    disable=not logging.is_progress_bar_enabled()				,    desc="Creating CSV from Arrow format"				,    ):
                 snake_case      =					self._batch_csv((offset, header, index, to_csv_kwargs)   )
                 written += file_obj.write(_A   )

         else:
             snake_case     ,							snake_case      =					len(self.dataset   ), self.batch_size
             with multiprocessing.Pool(self.num_proc   ) as pool:
                 for csv_str in logging.tqdm(
                     pool.imap(
                         self._batch_csv				,    [(offset, header, index, to_csv_kwargs) for offset in range(0				,    _A				,    _A   )]				,    )				,    total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size				,    unit="ba"				,    disable=not logging.is_progress_bar_enabled()				,    desc="Creating CSV from Arrow format"				,    ):
                     written += file_obj.write(_A   )

         return written



import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


_A  					= logging.get_logger(__name__)







class      lowerCamelCase		(  A_  ):
     UpperCAmelCase__				:							Tuple           =		"semantic"





     def __init__(self      :    Dict				,    _A      :    Optional[Any]=1_0_0_0_0				,    _A      :    List[Any]=True				,    _A      :    Any=7_6_8				,    _A      :    Union[str, Any]=False				,    _A      :    List[Any]=False				,    _A      :    Union[str, Any]=False				,    _A      :    Union[str, Any]=False				,    _A      :    str=0.7				,    _A      :    Optional[int]=True				,    _A      :    Any=1_0_0_4_8				,    _A      :    Optional[int]=1_2_9_5_9_5				,    _A      :    Union[str, Any]=1_2_9_5_9_9				,    _A      :    Any=1_0_0_0_0				,    _A      :    str=2_5_6				,    _A      :    int=49.9				,    **_A      :    Union[str, Any]				,    )						->						Any:
         super().__init__(
             temperature=_A				,    do_sample=_A				,    eos_token_id=_A				,    renormalize_logits=_A				,    max_new_tokens=_A				,    output_scores=_A				,    return_dict_in_generate=_A				,    output_hidden_states=_A				,    output_attentions=_A				,    **_A				,    )

         snake_case      =					text_encoding_offset
         snake_case      =					text_pad_token
         snake_case      =					eos_token_id
         snake_case      =					semantic_infer_token
         snake_case      =					semantic_vocab_size
         snake_case      =					max_input_semantic_length
         snake_case      =					semantic_rate_hz







class      lowerCamelCase		(  A_  ):
     UpperCAmelCase__				:							List[Any]           =		"coarse_acoustics"





     def __init__(self      :    Any				,    _A      :    Union[str, Any]=True				,    _A      :    List[Any]=False				,    _A      :    Any=False				,    _A      :    Union[str, Any]=False				,    _A      :    Optional[Any]=False				,    _A      :    str=0.7				,    _A      :    int=True				,    _A      :    List[str]=1_2_0_4_8				,    _A      :    Optional[int]=7_5				,    _A      :    Any=2				,    _A      :    Optional[Any]=1_2_0_5_0				,    _A      :    Tuple=2_5_6				,    _A      :    int = 6_3_0				,    _A      :    int = 6_0				,    **_A      :    int				,    )						->						Union[str, Any]:
         super().__init__(
             temperature=_A				,    do_sample=_A				,    renormalize_logits=_A				,    output_scores=_A				,    return_dict_in_generate=_A				,    output_hidden_states=_A				,    output_attentions=_A				,    **_A				,    )

         snake_case      =					coarse_semantic_pad_token
         snake_case      =					coarse_rate_hz
         snake_case      =					n_coarse_codebooks
         snake_case      =					coarse_infer_token
         snake_case      =					max_coarse_input_length
         snake_case      =					max_coarse_history
         snake_case      =					sliding_window_len







class      lowerCamelCase		(  A_  ):
     UpperCAmelCase__				:							int           =		"fine_acoustics"





     def __init__(self      :    Tuple				,    _A      :    Optional[int]=0.5				,    _A      :    List[str]=5_1_2				,    _A      :    Union[str, Any]=1_0_2_4				,    _A      :    Tuple=8				,    **_A      :    Tuple				,    )						->						Tuple:
         super().__init__(temperature=_A   )

         snake_case      =					max_fine_history_length
         snake_case      =					max_fine_input_length
         snake_case      =					n_fine_codebooks







class      lowerCamelCase		(  A_  ):
     UpperCAmelCase__				:							Optional[Any]           =		"bark"
     UpperCAmelCase__				:							Union[str, Any]           =		True





     def __init__(self      :    Union[str, Any]				,    _A      :    Dict = None				,    _A      :    Dict = None				,    _A      :    Dict = None				,    _A      :    Optional[int]=2_4_0_0_0				,    _A      :    Any=1_0_2_4				,    **_A      :    List[str]				,    )						->						Optional[Any]:
         if semantic_config is None:
             snake_case      =					{}
             logger.info("semantic_config is None. initializing the semantic model with default values."   )

         if coarse_acoustics_config is None:
             snake_case      =					{}
             logger.info("coarse_acoustics_config is None. initializing the coarse model with default values."   )

         if fine_acoustics_config is None:
             snake_case      =					{}
             logger.info("fine_acoustics_config is None. initializing the fine model with default values."   )

         snake_case      =					BarkSemanticGenerationConfig(**_A   )
         snake_case      =					BarkCoarseGenerationConfig(**_A   )
         snake_case      =					BarkFineGenerationConfig(**_A   )

         snake_case      =					sample_rate
         snake_case      =					codebook_size





     @classmethod
     def 		UpperCAmelCase(cls      :    List[Any]				,    _A      :    BarkSemanticGenerationConfig				,    _A      :    BarkCoarseGenerationConfig				,    _A      :    BarkFineGenerationConfig				,    **_A      :    Optional[int]				,    )						->						Union[str, Any]:
         return cls(
             semantic_config=semantic_config.to_dict()				,    coarse_acoustics_config=coarse_acoustics_config.to_dict()				,    fine_acoustics_config=fine_acoustics_config.to_dict()				,    **_A				,    )





     def 		UpperCAmelCase(self      :    List[str]   )						->						int:
         snake_case      =					copy.deepcopy(self.__dict__   )

         snake_case      =					self.semantic_config.to_dict()
         snake_case      =					self.coarse_acoustics_config.to_dict()
         snake_case      =					self.fine_acoustics_config.to_dict()

         snake_case      =					self.__class__.model_type
         return output

