

import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput







@dataclass
class 							a__							( lowercase__							):







  """simple docstring"""




  UpperCAmelCase__   :			float
  UpperCAmelCase__   :			Optional[float]      							=None
  UpperCAmelCase__   :			Optional[float]      							=None







class 							a__							( unittest.TestCase							):







  """simple docstring"""




  def 			_lowercase   (      self     :			Tuple		)       ->int:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   List[Any]	  = ModelOutputTest(a=3_0		)
        self.assertEqual(x.a					,					3_0		)
        self.assertIsNone(x.b		)
        self.assertIsNone(x.c		)
        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   Dict	  = x.d


  def 			_lowercase   (      self     :			int		)       ->Tuple:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   Optional[int]	  = ModelOutputTest(a=3_0					,					b=1_0		)
        self.assertEqual(x[0]					,					3_0		)
        self.assertEqual(x[1]					,					1_0		)
        self.assertEqual(x[:2]					,					(3_0, 1_0)		)
        self.assertEqual(x[:]					,					(3_0, 1_0)		)

        SCREAMING_SNAKE_CASE			:   Any	  = ModelOutputTest(a=3_0					,					c=1_0		)
        self.assertEqual(x[0]					,					3_0		)
        self.assertEqual(x[1]					,					1_0		)
        self.assertEqual(x[:2]					,					(3_0, 1_0)		)
        self.assertEqual(x[:]					,					(3_0, 1_0)		)


  def 			_lowercase   (      self     :			int		)       ->str:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   str	  = ModelOutputTest(a=3_0					,					b=1_0		)
        self.assertEqual(x["""a"""]					,					3_0		)
        self.assertEqual(x["""b"""]					,					1_0		)
        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   List[str]	  = x["c"]

        SCREAMING_SNAKE_CASE			:   Dict	  = ModelOutputTest(a=3_0					,					c=1_0		)
        self.assertEqual(x["""a"""]					,					3_0		)
        self.assertEqual(x["""c"""]					,					1_0		)
        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   int	  = x["b"]


  def 			_lowercase   (      self     :			Optional[int]		)       ->Dict:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   List[str]	  = ModelOutputTest(a=3_0		)
        self.assertEqual(list(x.keys()		)					,					["""a"""]		)
        self.assertEqual(list(x.values()		)					,					[3_0]		)
        self.assertEqual(list(x.items()		)					,					[("""a""", 3_0)]		)
        self.assertEqual(list(lowercase_		)					,					["""a"""]		)

        SCREAMING_SNAKE_CASE			:   List[Any]	  = ModelOutputTest(a=3_0					,					b=1_0		)
        self.assertEqual(list(x.keys()		)					,					["""a""", """b"""]		)
        self.assertEqual(list(x.values()		)					,					[3_0, 1_0]		)
        self.assertEqual(list(x.items()		)					,					[("""a""", 3_0), ("""b""", 1_0)]		)
        self.assertEqual(list(lowercase_		)					,					["""a""", """b"""]		)

        SCREAMING_SNAKE_CASE			:   Tuple	  = ModelOutputTest(a=3_0					,					c=1_0		)
        self.assertEqual(list(x.keys()		)					,					["""a""", """c"""]		)
        self.assertEqual(list(x.values()		)					,					[3_0, 1_0]		)
        self.assertEqual(list(x.items()		)					,					[("""a""", 3_0), ("""c""", 1_0)]		)
        self.assertEqual(list(lowercase_		)					,					["""a""", """c"""]		)

        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = x.update({"""d""": 2_0}		)
        with self.assertRaises(lowercase_		):
              del x["a"]
        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   List[Any]	  = x.pop("""a"""		)
        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = x.setdefault("""d"""					,					3_2		)


  def 			_lowercase   (      self     :			Union[str, Any]		)       ->Dict:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   Optional[int]	  = ModelOutputTest(a=3_0		)
        SCREAMING_SNAKE_CASE			:   List[str]	  = 1_0
        self.assertEqual(x.a					,					1_0		)
        self.assertEqual(x["""a"""]					,					1_0		)


  def 			_lowercase   (      self     :			Dict		)       ->Optional[Any]:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = ModelOutputTest(a=3_0		)
        SCREAMING_SNAKE_CASE			:   str	  = 1_0
        self.assertEqual(x.a					,					1_0		)
        self.assertEqual(x["""a"""]					,					1_0		)


  def 			_lowercase   (      self     :			Optional[Any]		)       ->Optional[int]:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   List[str]	  = ModelOutputTest({"""a""": 3_0, """b""": 1_0}		)
        self.assertEqual(list(x.keys()		)					,					["""a""", """b"""]		)
        self.assertEqual(x.a					,					3_0		)
        self.assertEqual(x.b					,					1_0		)




  def 			_lowercase   (      self     :			Any		)       ->Union[str, Any]:
        """simple docstring"""







        SCREAMING_SNAKE_CASE			:   Any	  = ModelOutputTest([("""a""", 3_0), ("""b""", 1_0)]		)
        self.assertEqual(list(x.keys()		)					,					["""a""", """b"""]		)
        self.assertEqual(x.a					,					3_0		)
        self.assertEqual(x.b					,					1_0		)

        with self.assertRaises(lowercase_		):
              SCREAMING_SNAKE_CASE			:   Union[str, Any]	  = ModelOutputTest([("""a""", 3_0), (1_0, 1_0)]		)

        SCREAMING_SNAKE_CASE			:   int	  = ModelOutputTest(a=(3_0, 3_0)		)
        self.assertEqual(list(x.keys()		)					,					["""a"""]		)
        self.assertEqual(x.a					,					(3_0, 3_0)		)






"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

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


_a									=				logging.get_logger(__name__)

_a									=				{
    '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_      (lowercase__ ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__     :		Any    	=						SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
  SCREAMING_SNAKE_CASE__     :		Optional[Any]    	=						"""squeezebert"""







  def __init__(						self							,  lowercase_=3_0522							,  lowercase_=768							,  lowercase_=12							,  lowercase_=12							,  lowercase_=3072							,  lowercase_="gelu"							,  lowercase_=0.1							,  lowercase_=0.1							,  lowercase_=512							,  lowercase_=2							,  lowercase_=0.02							,  lowercase_=1E-1_2							,  lowercase_=0							,  lowercase_=768							,  lowercase_=4							,  lowercase_=4							,  lowercase_=4							,  lowercase_=1							,  lowercase_=4							,  lowercase_=4							,  **lowercase_							,  ):

     """simple docstring"""
     super().__init__(pad_token_id=lowercase_							,  **lowercase_    )

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




class A_      (lowercase__ ):




  '''simple docstring'''







  @property
  def 			UpperCamelCase__   (						self    ):

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


