


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase__      		= logging.get_logger(__name__)

lowerCAmelCase__      		= {
    'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json',
    'xlm-mlm-ende-1024': 'https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json',
    'xlm-mlm-enfr-1024': 'https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json',
    'xlm-mlm-enro-1024': 'https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json',
    'xlm-mlm-tlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json',
    'xlm-mlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json',
    'xlm-clm-enfr-1024': 'https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json',
    'xlm-clm-ende-1024': 'https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json',
    'xlm-mlm-17-1280': 'https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json',
    'xlm-mlm-100-1280': 'https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json',
}







class      lowerCAmelCase__       (				a):




     '''simple docstring'''
     __SCREAMING_SNAKE_CASE  			= "xlm"
     __SCREAMING_SNAKE_CASE  			= {
         "hidden_size": "emb_dim",
         "num_attention_heads": "n_heads",
         "num_hidden_layers": "n_layers",
         "n_words": "vocab_size",  # For backward compatibility
     }


     def __init__(						self ,						__lowerCamelCase=3_0_1_4_5 ,						__lowerCamelCase=2_0_4_8 ,						__lowerCamelCase=1_2 ,						__lowerCamelCase=1_6 ,						__lowerCamelCase=0.1 ,						__lowerCamelCase=0.1 ,						__lowerCamelCase=True ,						__lowerCamelCase=False ,						__lowerCamelCase=False ,						__lowerCamelCase=False ,						__lowerCamelCase=1 ,						__lowerCamelCase=True ,						__lowerCamelCase=5_1_2 ,						__lowerCamelCase=2_0_4_8**-0.5 ,						__lowerCamelCase=1e-12 ,						__lowerCamelCase=0.0_2 ,						__lowerCamelCase=0 ,						__lowerCamelCase=1 ,						__lowerCamelCase=2 ,						__lowerCamelCase=3 ,						__lowerCamelCase=5 ,						__lowerCamelCase=True ,						__lowerCamelCase="first" ,						__lowerCamelCase=True ,						__lowerCamelCase=None ,						__lowerCamelCase=True ,						__lowerCamelCase=0.1 ,						__lowerCamelCase=5 ,						__lowerCamelCase=5 ,						__lowerCamelCase=0 ,						__lowerCamelCase=0 ,						__lowerCamelCase=2 ,						__lowerCamelCase=0 ,						**__lowerCamelCase ,						)			->				Optional[int]:
            _A      :       Optional[Any]				    = vocab_size
            _A      :       Optional[Any]				    = emb_dim
            _A      :       Union[str, Any]				    = n_layers
            _A      :       int				    = n_heads
            _A      :       Union[str, Any]				    = dropout
            _A      :       List[str]				    = attention_dropout
            _A      :       Tuple				    = gelu_activation
            _A      :       Dict				    = sinusoidal_embeddings
            _A      :       int				    = causal
            _A      :       int				    = asm
            _A      :       int				    = n_langs
            _A      :       int				    = use_lang_emb
            _A      :       Union[str, Any]				    = layer_norm_eps
            _A      :       Union[str, Any]				    = bos_index
            _A      :       Union[str, Any]				    = eos_index
            _A      :       Tuple				    = pad_index
            _A      :       Any				    = unk_index
            _A      :       Dict				    = mask_index
            _A      :       str				    = is_encoder
            _A      :       Union[str, Any]				    = max_position_embeddings
            _A      :       Optional[int]				    = embed_init_std
            _A      :       List[str]				    = init_std
            _A      :       Optional[int]				    = summary_type
            _A      :       Optional[Any]				    = summary_use_proj
            _A      :       Dict				    = summary_activation
            _A      :       Optional[Any]				    = summary_proj_to_labels
            _A      :       Any				    = summary_first_dropout
            _A      :       str				    = start_n_top
            _A      :       Any				    = end_n_top
            _A      :       int				    = mask_token_id
            _A      :       List[Any]				    = lang_id

            if "n_words" in kwargs:
                   _A      :       Any				    = kwargs["n_words"]

            super().__init__(pad_token_id=__lowerCamelCase ,						bos_token_id=__lowerCamelCase ,						**__lowerCamelCase)







class      lowerCAmelCase__       (				a):




     '''simple docstring'''


     @property
     def  _lowerCamelCase (						self)			->				Mapping[str, Mapping[int, str]]:
            if self.task == "multiple-choice":
                   _A      :       List[str]				    = {0: "batch", 1: "choice", 2: "sequence"}
            else:
                   _A      :       List[Any]				    = {0: "batch", 1: "sequence"}
            return OrderedDict(
                [
                    ("input_ids", dynamic_axis),
                    ("attention_mask", dynamic_axis),
                    ("token_type_ids", dynamic_axis),
                ])




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


lowerCAmelCase__      		= {
    'configuration_speecht5': [
        'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP',
        'SpeechT5Config',
        'SpeechT5HifiGanConfig',
    ],
    'feature_extraction_speecht5': ['SpeechT5FeatureExtractor'],
    'processing_speecht5': ['SpeechT5Processor'],
}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__      		= ['SpeechT5Tokenizer']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__      		= [
        'SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST',
        'SpeechT5ForSpeechToText',
        'SpeechT5ForSpeechToSpeech',
        'SpeechT5ForTextToSpeech',
        'SpeechT5Model',
        'SpeechT5PreTrainedModel',
        'SpeechT5HifiGan',
    ]

if TYPE_CHECKING:
    from .configuration_speechta import (
        SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
        SpeechTaConfig,
        SpeechTaHifiGanConfig,
    )
    from .feature_extraction_speechta import SpeechTaFeatureExtractor
    from .processing_speechta import SpeechTaProcessor

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_speechta import SpeechTaTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_speechta import (
            SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
            SpeechTaForSpeechToSpeech,
            SpeechTaForSpeechToText,
            SpeechTaForTextToSpeech,
            SpeechTaHifiGan,
            SpeechTaModel,
            SpeechTaPreTrainedModel,
        )

else:
    import sys

    lowerCAmelCase__      		= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
