






"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

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


_UpperCamelCase						:    Optional[int]		=						logging.get_logger(__name__)

_UpperCamelCase						:    Optional[Any]		=						{
    'squeezebert/squeezebert-uncased': (
        'https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json'
    ),
    'squeezebert/squeezebert-mnli': 'https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json',
    'squeezebert/squeezebert-mnli-headless': (
        'https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json'
    ),
}

class 			a	(  a_      ):
    UpperCAmelCase_					:	Optional[Any]      	=SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
    UpperCAmelCase_					:	List[Any]      	="squeezebert"







    def __init__(     self				,						_lowerCamelCase=3_0_5_2_2				,						_lowerCamelCase=7_6_8				,						_lowerCamelCase=1_2				,						_lowerCamelCase=1_2				,						_lowerCamelCase=3_0_7_2				,						_lowerCamelCase="gelu"				,						_lowerCamelCase=0.1				,						_lowerCamelCase=0.1				,						_lowerCamelCase=5_1_2				,						_lowerCamelCase=2				,						_lowerCamelCase=0.0_2				,						_lowerCamelCase=1e-12				,						_lowerCamelCase=0				,						_lowerCamelCase=7_6_8				,						_lowerCamelCase=4				,						_lowerCamelCase=4				,						_lowerCamelCase=4				,						_lowerCamelCase=1				,						_lowerCamelCase=4				,						_lowerCamelCase=4				,						**_lowerCamelCase				,						):
      super().__init__(pad_token_id=_lowerCamelCase				,						**_lowerCamelCase			)

      lowercase				       =			vocab_size
      lowercase				       =			hidden_size
      lowercase				       =			num_hidden_layers
      lowercase				       =			num_attention_heads
      lowercase				       =			hidden_act
      lowercase				       =			intermediate_size
      lowercase				       =			hidden_dropout_prob
      lowercase				       =			attention_probs_dropout_prob
      lowercase				       =			max_position_embeddings
      lowercase				       =			type_vocab_size
      lowercase				       =			initializer_range
      lowercase				       =			layer_norm_eps
      lowercase				       =			embedding_size
      lowercase				       =			q_groups
      lowercase				       =			k_groups
      lowercase				       =			v_groups
      lowercase				       =			post_attention_groups
      lowercase				       =			intermediate_groups
      lowercase				       =			output_groups


class 			a	(  a_      ):







    @property
    def      UpperCamelCase_ (     self			):
      if self.task == "multiple-choice":
        lowercase				       =			{0: 'batch', 1: 'choice', 2: 'sequence'}
      else:
        lowercase				       =			{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_tokenizers_available, is_torch_available


_UpperCamelCase:					Optional[Any]     				=	{
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase:					Union[str, Any]     				=	['CodeGenTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase:					str     				=	[
         'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
         'CodeGenForCausalLM',
         'CodeGenModel',
         'CodeGenPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
     from .tokenization_codegen import CodeGenTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_codegen_fast import CodeGenTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_codegen import (
              CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
              CodeGenForCausalLM,
              CodeGenModel,
              CodeGenPreTrainedModel,
          )

else:
     import sys

     _UpperCamelCase:					int     				=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
