
import importlib
import inspect
from functools import wraps
from typing import TYPE_CHECKING, Optional, Union

from .download.streaming_download_manager import (
    xbasename,
    xdirname,
    xet_parse,
    xexists,
    xgetsize,
    xglob,
    xgzip_open,
    xisdir,
    xisfile,
    xjoin,
    xlistdir,
    xnumpy_load,
    xopen,
    xpandas_read_csv,
    xpandas_read_excel,
    xPath,
    xrelpath,
    xsio_loadmat,
    xsplit,
    xsplitext,
    xwalk,
    xxml_dom_minidom_parse,
)
from .utils.logging import get_logger
from .utils.patching import patch_submodule
from .utils.py_utils import get_imports


_A  					= get_logger(__name__)


if TYPE_CHECKING:
   from .builder import DatasetBuilder



def 						lowercase_			(   A__ ,		A__ = None		)							->							int:
    """simple docstring"""

    snake_case      =					importlib.import_module(A__		)

    # TODO(QL): always update the module to add subsequent new authentication
    if hasattr(A__ ,		"_patched_for_streaming"		) and module._patched_for_streaming:
        return

    def wrap_auth(A__		):
        @wraps(A__		)
        def wrapper(*A__ ,		**A__		):
            return function(*A__ ,		use_auth_token=A__ ,		**A__		)

        snake_case      =					"wrap_auth"
        return wrapper

    # open files in a streaming fashion
    patch_submodule(A__ ,		"open" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"os.listdir" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"os.walk" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"glob.glob" ,		wrap_auth(A__		)		).start()
    # allow to navigate in remote zip files
    patch_submodule(A__ ,		"os.path.join" ,		A__		).start()
    patch_submodule(A__ ,		"os.path.dirname" ,		A__		).start()
    patch_submodule(A__ ,		"os.path.basename" ,		A__		).start()
    patch_submodule(A__ ,		"os.path.relpath" ,		A__		).start()
    patch_submodule(A__ ,		"os.path.split" ,		A__		).start()
    patch_submodule(A__ ,		"os.path.splitext" ,		A__		).start()
    # allow checks on paths
    patch_submodule(A__ ,		"os.path.exists" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"os.path.isdir" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"os.path.isfile" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"os.path.getsize" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"pathlib.Path" ,		A__		).start()
    # file readers
    patch_submodule(A__ ,		"gzip.open" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"numpy.load" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"pandas.read_csv" ,		wrap_auth(A__		) ,		attrs=["__version__"]		).start()
    patch_submodule(A__ ,		"pandas.read_excel" ,		wrap_auth(A__		) ,		attrs=["__version__"]		).start()
    patch_submodule(A__ ,		"scipy.io.loadmat" ,		wrap_auth(A__		) ,		attrs=["__version__"]		).start()
    patch_submodule(A__ ,		"xml.etree.ElementTree.parse" ,		wrap_auth(A__		)		).start()
    patch_submodule(A__ ,		"xml.dom.minidom.parse" ,		wrap_auth(A__		)		).start()
    snake_case      =					True





def 						lowercase_			(   A__		)							->							Union[str, Any]:
    """simple docstring"""

    extend_module_for_streaming(builder.__module__ ,		use_auth_token=builder.use_auth_token		)
    # if needed, we also have to extend additional internal imports (like wmt14 -> wmt_utils)
    if not builder.__module__.startswith("datasets."		):  # check that it's not a packaged builder like csv
        for imports in get_imports(inspect.getfile(builder.__class__		)		):
            if imports[0] == "internal":
                snake_case      =					imports[1]
                snake_case      =					".".join(builder.__module__.split("."		)[:-1] + [internal_import_name]		)
                extend_module_for_streaming(A__ ,		use_auth_token=builder.use_auth_token		)

    # builders can inherit from other builders that might use streaming functionality
    # (for example, ImageFolder and AudioFolder inherit from FolderBuilder which implements examples generation)
    # but these parents builders are not patched automatically as they are not instantiated, so we patch them here
    from .builder import DatasetBuilder

    snake_case      =					[
        cls.__module__
        for cls in type(A__		).__mro__[1:]  # make sure it's not the same module we've already patched
        if issubclass(cls ,		A__		) and cls.__module__ != DatasetBuilder.__module__
    ]  # check it's not a standard builder from datasets.builder
    for module in parent_builder_modules:
        extend_module_for_streaming(A__ ,		use_auth_token=builder.use_auth_token		)



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

