

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__	:       List[str]			      =      {
    """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__    (				UpperCAmelCase    ):







  """simple docstring"""




  UpperCAmelCase__ :	Any         =SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
  UpperCAmelCase__ :	Optional[Any]         ="""squeezebert"""


  def __init__(     self      :	Any			,			UpperCAmelCase__      :	Tuple=3_0_5_2_2			,			UpperCAmelCase__      :	List[str]=7_6_8			,			UpperCAmelCase__      :	Tuple=1_2			,			UpperCAmelCase__      :	Optional[Any]=1_2			,			UpperCAmelCase__      :	List[Any]=3_0_7_2			,			UpperCAmelCase__      :	List[str]="gelu"			,			UpperCAmelCase__      :	Union[str, Any]=0.1			,			UpperCAmelCase__      :	Optional[int]=0.1			,			UpperCAmelCase__      :	List[Any]=5_1_2			,			UpperCAmelCase__      :	str=2			,			UpperCAmelCase__      :	Any=0.02			,			UpperCAmelCase__      :	Any=1e-12			,			UpperCAmelCase__      :	List[str]=0			,			UpperCAmelCase__      :	Tuple=7_6_8			,			UpperCAmelCase__      :	Optional[Any]=4			,			UpperCAmelCase__      :	str=4			,			UpperCAmelCase__      :	Dict=4			,			UpperCAmelCase__      :	str=1			,			UpperCAmelCase__      :	Union[str, Any]=4			,			UpperCAmelCase__      :	int=4			,			**UpperCAmelCase__      :	Optional[int]			,			)   ->str:
        """simple docstring"""







        super().__init__(pad_token_id=UpperCAmelCase__			,			**UpperCAmelCase__						)

        SCREAMING_SNAKE_CASE	: List[Any]					       =				vocab_size
        SCREAMING_SNAKE_CASE	: str					       =				hidden_size
        SCREAMING_SNAKE_CASE	: Union[str, Any]					       =				num_hidden_layers
        SCREAMING_SNAKE_CASE	: str					       =				num_attention_heads
        SCREAMING_SNAKE_CASE	: Optional[int]					       =				hidden_act
        SCREAMING_SNAKE_CASE	: Dict					       =				intermediate_size
        SCREAMING_SNAKE_CASE	: Union[str, Any]					       =				hidden_dropout_prob
        SCREAMING_SNAKE_CASE	: List[Any]					       =				attention_probs_dropout_prob
        SCREAMING_SNAKE_CASE	: Optional[Any]					       =				max_position_embeddings
        SCREAMING_SNAKE_CASE	: Union[str, Any]					       =				type_vocab_size
        SCREAMING_SNAKE_CASE	: List[str]					       =				initializer_range
        SCREAMING_SNAKE_CASE	: List[Any]					       =				layer_norm_eps
        SCREAMING_SNAKE_CASE	: Optional[Any]					       =				embedding_size
        SCREAMING_SNAKE_CASE	: Any					       =				q_groups
        SCREAMING_SNAKE_CASE	: int					       =				k_groups
        SCREAMING_SNAKE_CASE	: List[Any]					       =				v_groups
        SCREAMING_SNAKE_CASE	: Dict					       =				post_attention_groups
        SCREAMING_SNAKE_CASE	: Optional[Any]					       =				intermediate_groups
        SCREAMING_SNAKE_CASE	: List[Any]					       =				output_groups







class     a__    (				UpperCAmelCase    ):







  """simple docstring"""




  @property
  def 	_lowercase (     self      :	Tuple						)   ->Mapping[str, Mapping[int, str]]:
        """simple docstring"""







        if self.task == "multiple-choice":
              SCREAMING_SNAKE_CASE	: Optional[Any]					       =				{0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
              SCREAMING_SNAKE_CASE	: Optional[int]					       =				{0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
                ("""token_type_ids""", dynamic_axis),
            ]						)







import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

UpperCAmelCase__	:       Dict			      =      [(1,)]






def    __lowercase (       )       ->  Tuple:
      SCREAMING_SNAKE_CASE	: Optional[Any]					       =				bool(os.getenv("""RUN_SLOW"""  ,      0     )     )
      if run_slow:
            assert True
      else:
            assert False, "should have been skipped"






def    __lowercase (       )       ->  Optional[Any]:
      SCREAMING_SNAKE_CASE	: Dict					       =				bool(os.getenv("""RUN_SLOW"""  ,      0     )     )
      if run_slow and torch_device == "cuda":
            assert True
      else:
            assert False, "should have been skipped"







@require_torch
class     a__    (				unittest.TestCase    ):







  """simple docstring"""




  @slow
  @require_torch_gpu
  def 	_lowercase (     self      :	Any						)   ->Optional[Any]:
        """simple docstring"""







        check_slow_torch_cuda()


  @require_torch_gpu
  @slow
  def 	_lowercase (     self      :	Optional[Any]						)   ->Any:
        """simple docstring"""







        check_slow_torch_cuda()




  @parameterized.expand(UpperCAmelCase__						)
  @slow
  def 	_lowercase (     self      :	Optional[int]			,			UpperCAmelCase__      :	Dict=None						)   ->Optional[Any]:
        """simple docstring"""







        check_slow()






@slow
@require_torch_gpu
def    __lowercase (       )       ->  Optional[int]:
      check_slow_torch_cuda()






@require_torch_gpu
@slow
def    __lowercase (       )       ->  int:
      check_slow_torch_cuda()






@slow
@pytest.mark.parametrize("""param"""  ,      [1]     )
def    __lowercase (       _A     )       ->  Optional[int]:
      check_slow()







@pytest.mark.parametrize("""param"""  ,      [1]     )
@slow
def    __lowercase (       _A     )       ->  str:
      check_slow()




