


'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

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


lowercase							=logging.get_logger(__name__)

lowercase							={
    '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  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="xlm"
       UpperCAmelCase										={
           "hidden_size": "emb_dim",
           "num_attention_heads": "n_heads",
           "num_hidden_layers": "n_layers",
           "n_words": "vocab_size",  # For backward compatibility
       }






       def __init__(      self  ,							snake_case=3_0_1_4_5  ,							snake_case=2_0_4_8  ,							snake_case=1_2  ,							snake_case=1_6  ,							snake_case=0.1  ,							snake_case=0.1  ,							snake_case=True  ,							snake_case=False  ,							snake_case=False  ,							snake_case=False  ,							snake_case=1  ,							snake_case=True  ,							snake_case=5_1_2  ,							snake_case=2_0_4_8**-0.5  ,							snake_case=1E-1_2  ,							snake_case=0.02  ,							snake_case=0  ,							snake_case=1  ,							snake_case=2  ,							snake_case=3  ,							snake_case=5  ,							snake_case=True  ,							snake_case="first"  ,							snake_case=True  ,							snake_case=None  ,							snake_case=True  ,							snake_case=0.1  ,							snake_case=5  ,							snake_case=5  ,							snake_case=0  ,							snake_case=0  ,							snake_case=2  ,							snake_case=0  ,							**snake_case  ,							)						->  int:




          '''simple docstring'''
          _UpperCAmelCase       :       int							   =vocab_size
          _UpperCAmelCase       :       Optional[Any]							   =emb_dim
          _UpperCAmelCase       :       Union[str, Any]							   =n_layers
          _UpperCAmelCase       :       str							   =n_heads
          _UpperCAmelCase       :       List[str]							   =dropout
          _UpperCAmelCase       :       Optional[Any]							   =attention_dropout
          _UpperCAmelCase       :       Tuple							   =gelu_activation
          _UpperCAmelCase       :       Dict							   =sinusoidal_embeddings
          _UpperCAmelCase       :       Optional[int]							   =causal
          _UpperCAmelCase       :       Optional[Any]							   =asm
          _UpperCAmelCase       :       Any							   =n_langs
          _UpperCAmelCase       :       Dict							   =use_lang_emb
          _UpperCAmelCase       :       Union[str, Any]							   =layer_norm_eps
          _UpperCAmelCase       :       List[str]							   =bos_index
          _UpperCAmelCase       :       int							   =eos_index
          _UpperCAmelCase       :       Optional[int]							   =pad_index
          _UpperCAmelCase       :       List[Any]							   =unk_index
          _UpperCAmelCase       :       Optional[int]							   =mask_index
          _UpperCAmelCase       :       str							   =is_encoder
          _UpperCAmelCase       :       Dict							   =max_position_embeddings
          _UpperCAmelCase       :       Optional[Any]							   =embed_init_std
          _UpperCAmelCase       :       List[str]							   =init_std
          _UpperCAmelCase       :       Tuple							   =summary_type
          _UpperCAmelCase       :       Dict							   =summary_use_proj
          _UpperCAmelCase       :       Dict							   =summary_activation
          _UpperCAmelCase       :       Optional[Any]							   =summary_proj_to_labels
          _UpperCAmelCase       :       Dict							   =summary_first_dropout
          _UpperCAmelCase       :       Optional[int]							   =start_n_top
          _UpperCAmelCase       :       Dict							   =end_n_top
          _UpperCAmelCase       :       Tuple							   =mask_token_id
          _UpperCAmelCase       :       Optional[int]							   =lang_id

          if "n_words" in kwargs:
             _UpperCAmelCase       :       Tuple							   =kwargs['n_words']

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






class  __magic_name__							(		lowerCAmelCase    ):






       @property
       def       lowerCAmelCase		(      self)						->  Mapping[str, Mapping[int, str]]:




          '''simple docstring'''
          if self.task == "multiple-choice":
             _UpperCAmelCase       :       str							   ={0: 'batch', 1: 'choice', 2: 'sequence'}
          else:
             _UpperCAmelCase       :       List[str]							   ={0: 'batch', 1: 'sequence'}
          return OrderedDict(
              [
                  ('input_ids', dynamic_axis),
                  ('attention_mask', dynamic_axis),
                  ('token_type_ids', dynamic_axis),
              ])





'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowercase							={
    'configuration_groupvit': [
        'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'GroupViTConfig',
        'GroupViTOnnxConfig',
        'GroupViTTextConfig',
        'GroupViTVisionConfig',
    ],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowercase							=[
     'GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'GroupViTModel',
     'GroupViTPreTrainedModel',
     'GroupViTTextModel',
     'GroupViTVisionModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowercase							=[
     'TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFGroupViTModel',
     'TFGroupViTPreTrainedModel',
     'TFGroupViTTextModel',
     'TFGroupViTVisionModel',
 ]

if TYPE_CHECKING:
 from .configuration_groupvit import (
     GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     GroupViTConfig,
     GroupViTOnnxConfig,
     GroupViTTextConfig,
     GroupViTVisionConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_groupvit import (
      GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      GroupViTModel,
      GroupViTPreTrainedModel,
      GroupViTTextModel,
      GroupViTVisionModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_groupvit import (
      TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFGroupViTModel,
      TFGroupViTPreTrainedModel,
      TFGroupViTTextModel,
      TFGroupViTVisionModel,
  )

else:
 import sys

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

