





'''simple docstring'''







import os
import re
import shutil
import sys
import tempfile
import unittest

import black


snake_case_     :       Any						=  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_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If BertLMPredictionHead is changed in modeling_bert.py, this code needs to be manually updated.
snake_case_     :       str						=  "    def __init__(self, config):\n        super().__init__()\n        self.transform = BertPredictionHeadTransform(config)\n\n        # The output weights are the same as the input embeddings, but there is\n        # an output-only bias for each token.\n        self.decoder = nn.Linear(config.hidden_size, config.vocab_size, bias=False)\n\n        self.bias = nn.Parameter(torch.zeros(config.vocab_size))\n\n        # Need a link between the two variables so that the bias is correctly resized with `resize_token_embeddings`\n        self.decoder.bias = self.bias\n\n    def forward(self, hidden_states):\n        hidden_states = self.transform(hidden_states)\n        hidden_states = self.decoder(hidden_states)\n        return hidden_states\n"


class 					__a      (unittest.TestCase     ):

							def     UpperCAmelCase__	(							self							:     Tuple   )					->       str:







													"""simple docstring"""
													UpperCAmelCase_			:      Any     						=  tempfile.mkdtemp()
													os.makedirs(os.path.join(self.transformer_dir       ,     '''models/bert/'''   )   )
													UpperCAmelCase_			:      Union[str, Any]     						=  self.transformer_dir
													shutil.copy(
													    os.path.join(__magic_name__       ,     '''src/transformers/models/bert/modeling_bert.py'''   )       ,     os.path.join(self.transformer_dir       ,     '''models/bert/modeling_bert.py'''   )       ,     )

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







													"""simple docstring"""
													UpperCAmelCase_			:      Tuple     						=  '''src/transformers'''
													shutil.rmtree(self.transformer_dir   )

							def     UpperCAmelCase__	(							self							:     Optional[Any]       ,     __magic_name__							:     Any       ,     __magic_name__							:     Optional[Any]       ,     __magic_name__							:     Tuple       ,     __magic_name__							:     Union[str, Any]=None   )					->       Optional[Any]:







													"""simple docstring"""
													UpperCAmelCase_			:      Optional[int]     						=  comment + F"""\nclass {class_name}(nn.Module):\n""" + class_code
													if overwrite_result is not None:
																			UpperCAmelCase_			:      Tuple     						=  comment + F"""\nclass {class_name}(nn.Module):\n""" + overwrite_result
													UpperCAmelCase_			:      Any     						=  black.Mode(target_versions={black.TargetVersion.PYaa}       ,     line_length=1_19   )
													UpperCAmelCase_			:      Tuple     						=  black.format_str(__magic_name__       ,     mode=__magic_name__   )
													UpperCAmelCase_			:      Union[str, Any]     						=  os.path.join(self.transformer_dir       ,     '''new_code.py'''   )
													with open(__magic_name__       ,     '''w'''       ,     newline='''\n'''   ) as f:
																			f.write(__magic_name__   )
													if overwrite_result is None:
																			self.assertTrue(len(check_copies.is_copy_consistent(__magic_name__   )   ) == 0   )
													else:
																			check_copies.is_copy_consistent(f.name       ,     overwrite=__magic_name__   )
																			with open(__magic_name__       ,     '''r'''   ) as f:
																									self.assertTrue(f.read()       ,     __magic_name__   )

							def     UpperCAmelCase__	(							self							:     Any   )					->       List[str]:







													"""simple docstring"""
													UpperCAmelCase_			:      Union[str, Any]     						=  check_copies.find_code_in_transformers('''models.bert.modeling_bert.BertLMPredictionHead'''   )
													self.assertEqual(__magic_name__       ,     __magic_name__   )

							def     UpperCAmelCase__	(							self							:     str   )					->       List[Any]:







													"""simple docstring"""
													self.check_copy_consistency(
													    '''# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead'''       ,     '''BertLMPredictionHead'''       ,     REFERENCE_CODE + '''\n'''       ,     )

													# With no empty line at the end
													self.check_copy_consistency(
													    '''# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead'''       ,     '''BertLMPredictionHead'''       ,     __magic_name__       ,     )

													# Copy consistency with rename
													self.check_copy_consistency(
													    '''# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead with Bert->TestModel'''       ,     '''TestModelLMPredictionHead'''       ,     re.sub('''Bert'''       ,     '''TestModel'''       ,     __magic_name__   )       ,     )

													# Copy consistency with a really long name
													UpperCAmelCase_			:      Tuple     						=  '''TestModelWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason'''
													self.check_copy_consistency(
													    F"""# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead with Bert->{long_class_name}"""       ,     F"""{long_class_name}LMPredictionHead"""       ,     re.sub('''Bert'''       ,     __magic_name__       ,     __magic_name__   )       ,     )

													# Copy consistency with overwrite
													self.check_copy_consistency(
													    '''# Copied from transformers.models.bert.modeling_bert.BertLMPredictionHead with Bert->TestModel'''       ,     '''TestModelLMPredictionHead'''       ,     __magic_name__       ,     overwrite_result=re.sub('''Bert'''       ,     '''TestModel'''       ,     __magic_name__   )       ,     )



							def     UpperCAmelCase__	(							self							:     Optional[Any]   )					->       List[str]:







													"""simple docstring"""
													UpperCAmelCase_			:      Optional[int]     						=  check_copies.LOCALIZED_READMES['''README_zh-hans.md''']

													UpperCAmelCase_			:      Dict     						=  (
													    '''1. **[ALBERT](https://huggingface.co/transformers/model_doc/albert.html)** (from Google Research and the'''
													    ''' Toyota Technological Institute at Chicago) released with the paper [ALBERT: A Lite BERT for'''
													    ''' Self-supervised Learning of Language Representations](https://arxiv.org/abs/1909.11942), by Zhenzhong'''
													    ''' Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut.\n1.'''
													    ''' **[DistilBERT](https://huggingface.co/transformers/model_doc/distilbert.html)** (from HuggingFace),'''
													    ''' released together with the paper [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and'''
													    ''' lighter](https://arxiv.org/abs/1910.01108) by Victor Sanh, Lysandre Debut and Thomas Wolf. The same'''
													    ''' method has been applied to compress GPT2 into'''
													    ''' [DistilGPT2](https://github.com/huggingface/transformers/tree/main/examples/distillation), RoBERTa into'''
													    ''' [DistilRoBERTa](https://github.com/huggingface/transformers/tree/main/examples/distillation),'''
													    ''' Multilingual BERT into'''
													    ''' [DistilmBERT](https://github.com/huggingface/transformers/tree/main/examples/distillation) and a German'''
													    ''' version of DistilBERT.\n1. **[ELECTRA](https://huggingface.co/transformers/model_doc/electra.html)**'''
													    ''' (from Google Research/Stanford University) released with the paper [ELECTRA: Pre-training text encoders'''
													    ''' as discriminators rather than generators](https://arxiv.org/abs/2003.10555) by Kevin Clark, Minh-Thang'''
													    ''' Luong, Quoc V. Le, Christopher D. Manning.'''
													)
													UpperCAmelCase_			:      List[Any]     						=  (
													    '''1. **[ALBERT](https://huggingface.co/transformers/model_doc/albert.html)** (来自 Google Research and the'''
													    ''' Toyota Technological Institute at Chicago) 伴随论文 [ALBERT: A Lite BERT for Self-supervised Learning of'''
													    ''' Language Representations](https://arxiv.org/abs/1909.11942), 由 Zhenzhong Lan, Mingda Chen, Sebastian'''
													    ''' Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut 发布。\n'''
													)
													UpperCAmelCase_			:      Any     						=  (
													    '''1. **[ALBERT](https://huggingface.co/transformers/model_doc/albert.html)** (来自 Google Research and the'''
													    ''' Toyota Technological Institute at Chicago) 伴随论文 [ALBERT: A Lite BERT for Self-supervised Learning of'''
													    ''' Language Representations](https://arxiv.org/abs/1909.11942), 由 Zhenzhong Lan, Mingda Chen, Sebastian'''
													    ''' Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut 发布。\n1.'''
													    ''' **[DistilBERT](https://huggingface.co/transformers/model_doc/distilbert.html)** (来自 HuggingFace) 伴随论文'''
													    ''' [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and'''
													    ''' lighter](https://arxiv.org/abs/1910.01108) 由 Victor Sanh, Lysandre Debut and Thomas Wolf 发布。 The same'''
													    ''' method has been applied to compress GPT2 into'''
													    ''' [DistilGPT2](https://github.com/huggingface/transformers/tree/main/examples/distillation), RoBERTa into'''
													    ''' [DistilRoBERTa](https://github.com/huggingface/transformers/tree/main/examples/distillation),'''
													    ''' Multilingual BERT into'''
													    ''' [DistilmBERT](https://github.com/huggingface/transformers/tree/main/examples/distillation) and a German'''
													    ''' version of DistilBERT.\n1. **[ELECTRA](https://huggingface.co/transformers/model_doc/electra.html)** (来自'''
													    ''' Google Research/Stanford University) 伴随论文 [ELECTRA: Pre-training text encoders as discriminators rather'''
													    ''' than generators](https://arxiv.org/abs/2003.10555) 由 Kevin Clark, Minh-Thang Luong, Quoc V. Le,'''
													    ''' Christopher D. Manning 发布。\n'''
													)

													UpperCAmelCase_			:      Optional[int]     						=  check_copies.convert_to_localized_md(
													    __magic_name__       ,     __magic_name__       ,     localized_readme['''format_model_list''']   )

													self.assertFalse(__magic_name__   )
													self.assertEqual(__magic_name__       ,     __magic_name__   )

													UpperCAmelCase_			:      Tuple     						=  check_copies.convert_to_localized_md(
													    __magic_name__       ,     __magic_name__       ,     localized_readme['''format_model_list''']   )

													# Check whether the number of models is equal to README.md after conversion.
													self.assertTrue(__magic_name__   )

													UpperCAmelCase_			:      Union[str, Any]     						=  (
													    '''1. **[ALBERT](https://huggingface.co/transformers/model_doc/albert.html)** (from Google Research and the'''
													    ''' Toyota Technological Institute at Chicago) released with the paper [ALBERT: A Lite BERT for'''
													    ''' Self-supervised Learning of Language Representations](https://arxiv.org/abs/1909.11942), by Zhenzhong'''
													    ''' Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut.'''
													)
													UpperCAmelCase_			:      Union[str, Any]     						=  (
													    '''1. **[ALBERT](https://huggingface.co/transformers/main/model_doc/albert.html)** (来自 Google Research and'''
													    ''' the Toyota Technological Institute at Chicago) 伴随论文 [ALBERT: A Lite BERT for Self-supervised Learning of'''
													    ''' Language Representations](https://arxiv.org/abs/1909.11942), 由 Zhenzhong Lan, Mingda Chen, Sebastian'''
													    ''' Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut 发布。\n'''
													)
													UpperCAmelCase_			:      Optional[int]     						=  (
													    '''1. **[ALBERT](https://huggingface.co/transformers/model_doc/albert.html)** (来自 Google Research and the'''
													    ''' Toyota Technological Institute at Chicago) 伴随论文 [ALBERT: A Lite BERT for Self-supervised Learning of'''
													    ''' Language Representations](https://arxiv.org/abs/1909.11942), 由 Zhenzhong Lan, Mingda Chen, Sebastian'''
													    ''' Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut 发布。\n'''
													)

													UpperCAmelCase_			:      Any     						=  check_copies.convert_to_localized_md(
													    __magic_name__       ,     __magic_name__       ,     localized_readme['''format_model_list''']   )

													# Check if the model link is synchronized.
													self.assertEqual(__magic_name__       ,     __magic_name__   )












'''simple docstring'''







def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			int   ) ->	str:
						if number > 0:
												raise ValueError('''input must be a negative integer'''   )
						UpperCAmelCase_			:      Union[str, Any]     						=  len(bin(SCREAMING_SNAKE_CASE__   )[3:]   )
						UpperCAmelCase_			:      Union[str, Any]     						=  bin(abs(SCREAMING_SNAKE_CASE__   ) - (1 << binary_number_length)   )[3:]
						UpperCAmelCase_			:      Optional[Any]     						=  (
						    (
						        '''1'''
						        + '''0''' * (binary_number_length - len(SCREAMING_SNAKE_CASE__   ))
						        + twos_complement_number
						    )
						    if number < 0
						    else '''0'''
						)
						return "0b" + twos_complement_number


if __name__ == "__main__":
					import doctest

					doctest.testmod()





