



import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import Mock, patch

import diffusers.utils.hub_utils



class        __snake_case		(  unittest.TestCase		):




							@patch('''diffusers.utils.hub_utils.get_full_repo_name''')
							def      UpperCAmelCase__    ( self  : str       ,       A_  : Mock):
									lowerCAmelCase_    :  Optional[Any]             =				'''full_repo_name'''
									with TemporaryDirectory() as tmpdir:
											# Dummy args values
											lowerCAmelCase_    :  List[Any]             =				Mock()
											lowerCAmelCase_    :  Optional[Any]             =				tmpdir
											lowerCAmelCase_    :  Any             =				0
											lowerCAmelCase_    :  Dict             =				'''hub_token'''
											lowerCAmelCase_    :  Optional[int]             =				'''dataset_name'''
											lowerCAmelCase_    :  Optional[Any]             =				0.01
											lowerCAmelCase_    :  str             =				1_0_0_0_0_0
											lowerCAmelCase_    :  Union[str, Any]             =				1_0_0_0_0
											lowerCAmelCase_    :  Any             =				0.01
											lowerCAmelCase_    :  Optional[Any]             =				0.02
											lowerCAmelCase_    :  Tuple             =				0.03
											lowerCAmelCase_    :  str             =				0.0005
											lowerCAmelCase_    :  Optional[int]             =				0.00_0001
											lowerCAmelCase_    :  Dict             =				1
											lowerCAmelCase_    :  Any             =				1_0
											lowerCAmelCase_    :  List[Any]             =				0.001
											lowerCAmelCase_    :  Optional[int]             =				0.1
											lowerCAmelCase_    :  Union[str, Any]             =				0.2
											lowerCAmelCase_    :  List[Any]             =				True

											# Model card mush be rendered and saved
											diffusers.utils.hub_utils.create_model_card(A_       ,       model_name='''model_name''')
											self.assertTrue((Path(A_) / '''README.md''').is_file())










from collections import OrderedDict
from typing import Mapping

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


A__						:						Dict          =      logging.get_logger(__name__)

A__						:						List[str]          =      {
    '''google/electra-small-generator''': '''https://huggingface.co/google/electra-small-generator/resolve/main/config.json''',
    '''google/electra-base-generator''': '''https://huggingface.co/google/electra-base-generator/resolve/main/config.json''',
    '''google/electra-large-generator''': '''https://huggingface.co/google/electra-large-generator/resolve/main/config.json''',
    '''google/electra-small-discriminator''': (
        '''https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-base-discriminator''': (
        '''https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-large-discriminator''': (
        '''https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'''
    ),
}



class        __snake_case		(  UpperCamelCase_		):
							_a       =				'''electra'''




							def __init__( self  : Dict       ,       A_  : Dict=3_0_5_2_2       ,       A_  : List[Any]=1_2_8       ,       A_  : Dict=2_5_6       ,       A_  : Any=1_2       ,       A_  : Optional[Any]=4       ,       A_  : Optional[int]=1_0_2_4       ,       A_  : Optional[int]="gelu"       ,       A_  : str=0.1       ,       A_  : Optional[int]=0.1       ,       A_  : str=5_1_2       ,       A_  : Optional[int]=2       ,       A_  : Dict=0.02       ,       A_  : Union[str, Any]=1e-12       ,       A_  : List[Any]="first"       ,       A_  : List[str]=True       ,       A_  : List[str]="gelu"       ,       A_  : Any=0.1       ,       A_  : int=0       ,       A_  : Optional[Any]="absolute"       ,       A_  : Optional[int]=True       ,       A_  : str=None       ,       **A_  : List[Any]       ,       ):
									super().__init__(pad_token_id=A_       ,       **A_)

									lowerCAmelCase_    :  str             =				vocab_size
									lowerCAmelCase_    :  Union[str, Any]             =				embedding_size
									lowerCAmelCase_    :  Optional[int]             =				hidden_size
									lowerCAmelCase_    :  List[Any]             =				num_hidden_layers
									lowerCAmelCase_    :  List[str]             =				num_attention_heads
									lowerCAmelCase_    :  str             =				intermediate_size
									lowerCAmelCase_    :  Union[str, Any]             =				hidden_act
									lowerCAmelCase_    :  Union[str, Any]             =				hidden_dropout_prob
									lowerCAmelCase_    :  Tuple             =				attention_probs_dropout_prob
									lowerCAmelCase_    :  Optional[Any]             =				max_position_embeddings
									lowerCAmelCase_    :  Dict             =				type_vocab_size
									lowerCAmelCase_    :  Any             =				initializer_range
									lowerCAmelCase_    :  int             =				layer_norm_eps

									lowerCAmelCase_    :  Union[str, Any]             =				summary_type
									lowerCAmelCase_    :  str             =				summary_use_proj
									lowerCAmelCase_    :  str             =				summary_activation
									lowerCAmelCase_    :  List[Any]             =				summary_last_dropout
									lowerCAmelCase_    :  Optional[Any]             =				position_embedding_type
									lowerCAmelCase_    :  List[Any]             =				use_cache
									lowerCAmelCase_    :  Any             =				classifier_dropout





class        __snake_case		(  UpperCamelCase_		):




							@property
							def      UpperCAmelCase__    ( self  : Union[str, Any]):
									if self.task == "multiple-choice":
											lowerCAmelCase_    :  Any             =				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
											lowerCAmelCase_    :  Union[str, Any]             =				{0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									        ('''token_type_ids''', dynamic_axis),
									    ])





