
"""simple docstring"""







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

import black


lowerCamelCase__ :    Optional[int]        =		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.
lowerCamelCase__ :    List[Any]        =		"""    def __init__(self, config):
        super().__init__()
        self.transform = BertPredictionHeadTransform(config)

        # The output weights are the same as the input embeddings, but there is
        # an output-only bias for each token.
        self.decoder = nn.Linear(config.hidden_size, config.vocab_size, bias=False)

        self.bias = nn.Parameter(torch.zeros(config.vocab_size))

        # Need a link between the two variables so that the bias is correctly resized with `resize_token_embeddings`
        self.decoder.bias = self.bias

    def forward(self, hidden_states):
        hidden_states = self.transform(hidden_states)
        hidden_states = self.decoder(hidden_states)
        return hidden_states
"""




class 			A__	(     unittest.TestCase):

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				tempfile.mkdtemp()
			os.makedirs(os.path.join(self.transformer_dir	,		'models/bert/'			)			)
			__lowerCAmelCase      :						Dict						      =				self.transformer_dir
			shutil.copy(
			    os.path.join(_lowerCamelCase	,		'src/transformers/models/bert/modeling_bert.py'			)	,		os.path.join(self.transformer_dir	,		'models/bert/modeling_bert.py'			)	,		)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Optional[Any]						      =				'''src/transformers'''
			shutil.rmtree(self.transformer_dir			)

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

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[str]						      =				check_copies.find_code_in_transformers('models.bert.modeling_bert.BertLMPredictionHead'			)
			self.assertEqual(_lowerCamelCase	,		_lowerCamelCase			)

		def 							__lowerCamelCase							(				self			):
			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'	,		_lowerCamelCase	,		)

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

			# Copy consistency with a really long name
			__lowerCAmelCase      :						List[Any]						      =				'''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'	,		_lowerCamelCase	,		_lowerCamelCase			)	,		)

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







		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						List[Any]						      =				check_copies.LOCALIZED_READMES['''README_zh-hans.md''']

			__lowerCAmelCase      :						List[str]						      =				(
			    '''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.'''
			)
			__lowerCAmelCase      :						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'''
			)
			__lowerCAmelCase      :						Optional[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'''
			)

			__lowerCAmelCase      :						Optional[Any]						      =				check_copies.convert_to_localized_md(
			    _lowerCamelCase	,		_lowerCamelCase	,		localized_readme['format_model_list']			)

			self.assertFalse(_lowerCamelCase			)
			self.assertEqual(_lowerCamelCase	,		_lowerCamelCase			)

			__lowerCAmelCase      :						Optional[Any]						      =				check_copies.convert_to_localized_md(
			    _lowerCamelCase	,		_lowerCamelCase	,		localized_readme['format_model_list']			)

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

			__lowerCAmelCase      :						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.'''
			)
			__lowerCAmelCase      :						Optional[int]						      =				(
			    '''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'''
			)
			__lowerCAmelCase      :						str						      =				(
			    '''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'''
			)

			__lowerCAmelCase      :						Dict						      =				check_copies.convert_to_localized_md(
			    _lowerCamelCase	,		_lowerCamelCase	,		localized_readme['format_model_list']			)

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

"""simple docstring"""







from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels