




from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
    from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
class       __a					( __lowerCamelCase     ):


     """simple docstring"""


     _A				:    Dict									=  c_float




     @property
     def   __A				(	self			: Dict						)		->   int:


         '''simple docstring'''





         return sizeof(self.value						)






def 	UpperCAmelCase_    (	__UpperCamelCase,				__UpperCamelCase,				__UpperCamelCase = 0	):
    # < 0 is possible if using a dynamic axis
    if dimension <= 0:
        SCREAMING_SNAKE_CASE__								=fixed_dimension

    dimension -= num_token_to_add
    return dimension



def 	UpperCAmelCase_    (	__UpperCamelCase,				__UpperCamelCase	):
    return num_parameters * dtype.size




def 	UpperCAmelCase_    (	__UpperCamelCase	):
    from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

    try:
        return AutoProcessor.from_pretrained(__UpperCamelCase	)
    except (ValueError, OSError, KeyError):
        SCREAMING_SNAKE_CASE__			,		SCREAMING_SNAKE_CASE__								=None, None
        try:
            SCREAMING_SNAKE_CASE__								=AutoTokenizer.from_pretrained(__UpperCamelCase	)
        except (OSError, KeyError):
            pass
        try:
            SCREAMING_SNAKE_CASE__								=AutoFeatureExtractor.from_pretrained(__UpperCamelCase	)
        except (OSError, KeyError):
            pass

        if tokenizer is not None and feature_extractor is not None:
            raise ValueError(
                f"""Couldn't auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor."""	)
        elif tokenizer is None and feature_extractor is None:
            return None
        elif tokenizer is not None:
            return tokenizer
        else:
            return feature_extractor












import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput
@dataclass
class       __a					( __lowerCamelCase     ):


     """simple docstring"""


     _A				:    float
     _A				:    Optional[float]									=  None
     _A				:    Optional[float]									=  None






class       __a					( unittest.TestCase     ):


     """simple docstring"""


     def   __A				(	self			: Dict						)		->   Optional[int]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         self.assertEqual(x.a				,3_0						)
         self.assertIsNone(x.b						)
         self.assertIsNone(x.c						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.d




     def   __A				(	self			: Tuple						)		->   Dict:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=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__								=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   __A				(	self			: List[str]						)		->   Dict:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,b=1_0						)
         self.assertEqual(x["""a"""]				,3_0						)
         self.assertEqual(x["""b"""]				,1_0						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x["""c"""]

         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0				,c=1_0						)
         self.assertEqual(x["""a"""]				,3_0						)
         self.assertEqual(x["""c"""]				,1_0						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x["""b"""]




     def   __A				(	self			: Optional[int]						)		->   List[str]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=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(_UpperCamelCase						)				,["""a"""]						)

         SCREAMING_SNAKE_CASE__								=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(_UpperCamelCase						)				,["""a""", """b"""]						)

         SCREAMING_SNAKE_CASE__								=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(_UpperCamelCase						)				,["""a""", """c"""]						)

         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.update({"""d""": 2_0}						)
         with self.assertRaises(_UpperCamelCase						):
             del x["a"]
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.pop("""a"""						)
         with self.assertRaises(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=x.setdefault("""d"""				,3_2						)




     def   __A				(	self			: int						)		->   List[Any]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         SCREAMING_SNAKE_CASE__								=1_0
         self.assertEqual(x.a				,1_0						)
         self.assertEqual(x["""a"""]				,1_0						)




     def   __A				(	self			: Union[str, Any]						)		->   Optional[Any]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=ModelOutputTest(a=3_0						)
         SCREAMING_SNAKE_CASE__								=1_0
         self.assertEqual(x.a				,1_0						)
         self.assertEqual(x["""a"""]				,1_0						)




     def   __A				(	self			: Dict						)		->   List[str]:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=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   __A				(	self			: Optional[int]						)		->   int:


         '''simple docstring'''





         SCREAMING_SNAKE_CASE__								=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(_UpperCamelCase						):
             SCREAMING_SNAKE_CASE__								=ModelOutputTest([("""a""", 3_0), (1_0, 1_0)]						)

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






