




'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


_snake_case : Any  				=						{
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}

class      A       (						_a       ):
							lowercase_							     =							'albert'







							def __init__(    self			:    List[str]				,     lowerCAmelCase_			:    Tuple=3_00_00				,     lowerCAmelCase_			:    Dict=1_28				,     lowerCAmelCase_			:    str=40_96				,     lowerCAmelCase_			:    int=12				,     lowerCAmelCase_			:    Dict=1				,     lowerCAmelCase_			:    Tuple=64				,     lowerCAmelCase_			:    Union[str, Any]=1_63_84				,     lowerCAmelCase_			:    Dict=1				,     lowerCAmelCase_			:    Union[str, Any]="gelu_new"				,     lowerCAmelCase_			:    List[str]=0				,     lowerCAmelCase_			:    int=0				,     lowerCAmelCase_			:    Dict=5_12				,     lowerCAmelCase_			:    Any=2				,     lowerCAmelCase_			:    Any=0.0_2				,     lowerCAmelCase_			:    Tuple=1e-12				,     lowerCAmelCase_			:    Union[str, Any]=0.1				,     lowerCAmelCase_			:    Union[str, Any]="absolute"				,     lowerCAmelCase_			:    Any=0				,     lowerCAmelCase_			:    List[str]=2				,     lowerCAmelCase_			:    Dict=3				,     **lowerCAmelCase_			:    Any				,     )     ->				Optional[Any]:


														"""simple docstring"""


														super().__init__(pad_token_id=lowerCAmelCase_				,     bos_token_id=lowerCAmelCase_				,     eos_token_id=lowerCAmelCase_				,     **lowerCAmelCase_   )

														_a      	=							vocab_size
														_a      	=							embedding_size
														_a      	=							hidden_size
														_a      	=							num_hidden_layers
														_a      	=							num_hidden_groups
														_a      	=							num_attention_heads
														_a      	=							inner_group_num
														_a      	=							hidden_act
														_a      	=							intermediate_size
														_a      	=							hidden_dropout_prob
														_a      	=							attention_probs_dropout_prob
														_a      	=							max_position_embeddings
														_a      	=							type_vocab_size
														_a      	=							initializer_range
														_a      	=							layer_norm_eps
														_a      	=							classifier_dropout_prob
														_a      	=							position_embedding_type



class      A       (						_a       ):







							@property
							def   __lowerCAmelCase     (    self			:    Tuple   )     ->				Mapping[str, Mapping[int, str]]:


														"""simple docstring"""


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




'''simple docstring'''







import os
import sys
import unittest


__lowerCamelCase									=     os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
__lowerCamelCase									=     os.path.join(git_repo_path, '''src''', '''transformers''')

__lowerCamelCase									=     '''
{0} = None
'''

__lowerCamelCase									=     '''
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
'''


__lowerCamelCase									=     '''
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
'''


class        A__   (   unittest.TestCase      ):



    def        snake_case_      (       self							)    ->   Dict:





           '''simple docstring'''
           A_						       =   find_backend("""    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"""							)
           self.assertIsNone(UpperCamelCase__							)

           A_						       =   find_backend("""    if not is_tokenizers_available():"""							)
           self.assertEqual(UpperCamelCase__		,					"""tokenizers"""							)

           A_						       =   find_backend("""    if not is_tensorflow_text_available():"""							)
           self.assertEqual(UpperCamelCase__		,					"""tensorflow_text"""							)

           A_						       =   find_backend("""    if not (is_sentencepiece_available() and is_tokenizers_available()):"""							)
           self.assertEqual(UpperCamelCase__		,					"""sentencepiece_and_tokenizers"""							)

           A_						       =   find_backend(
               """    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"""							)
           self.assertEqual(UpperCamelCase__		,					"""sentencepiece_and_tensorflow_text"""							)

           A_						       =   find_backend(
               """    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):"""							)
           self.assertEqual(UpperCamelCase__		,					"""sentencepiece_and_tokenizers_and_vision"""							)



    def        snake_case_      (       self							)    ->   int:





           '''simple docstring'''
           A_						       =   read_init()
           # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
           self.assertIn("""torch"""		,					UpperCamelCase__							)
           self.assertIn("""tensorflow_text"""		,					UpperCamelCase__							)
           self.assertIn("""sentencepiece_and_tokenizers"""		,					UpperCamelCase__							)

           # Likewise, we can't assert on the exact content of a key
           self.assertIn("""BertModel"""		,					objects["""torch"""]							)
           self.assertIn("""TFBertModel"""		,					objects["""tf"""]							)
           self.assertIn("""FlaxBertModel"""		,					objects["""flax"""]							)
           self.assertIn("""BertModel"""		,					objects["""torch"""]							)
           self.assertIn("""TFBertTokenizer"""		,					objects["""tensorflow_text"""]							)
           self.assertIn("""convert_slow_tokenizer"""		,					objects["""sentencepiece_and_tokenizers"""]							)



    def        snake_case_      (       self							)    ->   str:





           '''simple docstring'''
           A_						       =   create_dummy_object("""CONSTANT"""		,					"""'torch'"""							)
           self.assertEqual(UpperCamelCase__		,					"""\nCONSTANT = None\n"""							)

           A_						       =   create_dummy_object("""function"""		,					"""'torch'"""							)
           self.assertEqual(
               UpperCamelCase__		,					"""\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"""							)

           A_						       =   """
class FakeClass(metaclass=DummyObject):
    _backends = 'torch'

    def __init__(self, *args, **kwargs):
        requires_backends(self, 'torch')
"""
           A_						       =   create_dummy_object("""FakeClass"""		,					"""'torch'"""							)
           self.assertEqual(UpperCamelCase__		,					UpperCamelCase__							)







    def        snake_case_      (       self							)    ->   str:





           '''simple docstring'''
           A_						       =   """# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, [\"torch\"])


class FakeClass(metaclass=DummyObject):
    _backends = [\"torch\"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, [\"torch\"])
"""
           A_						       =   create_dummy_files({"""torch""": ["""CONSTANT""", """function""", """FakeClass"""]}							)
           self.assertEqual(dummy_files["""torch"""]		,					UpperCamelCase__							)
