



"""simple docstring"""


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

import black


snake_case_    					=	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_    					=	'    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    ):



						"""simple docstring"""






						def      UpperCAmelCase__					( self			:Union[str, Any] )    ->      List[str]:
												UpperCAmelCase					=			tempfile.mkdtemp()
												os.makedirs(os.path.join(self.transformer_dir       ,  'models/bert/' ) )
												UpperCAmelCase					=			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      UpperCAmelCase__					( self			:int )    ->      Optional[Any]:
												UpperCAmelCase					=			'''src/transformers'''
												shutil.rmtree(self.transformer_dir )






						def      UpperCAmelCase__					( self			:Tuple       ,  lowercase_			:int       ,  lowercase_			:Optional[int]       ,  lowercase_			:Any       ,  lowercase_			:Union[str, Any]=None )    ->      Tuple:
												UpperCAmelCase					=			comment + f"""\nclass {class_name}(nn.Module):\n""" + class_code
												if overwrite_result is not None:
																		UpperCAmelCase					=			comment + f"""\nclass {class_name}(nn.Module):\n""" + overwrite_result
												UpperCAmelCase					=			black.Mode(target_versions={black.TargetVersion.PYaa}       ,  line_length=1_19 )
												UpperCAmelCase					=			black.format_str(__lowerCamelCase       ,  mode=__lowerCamelCase )
												UpperCAmelCase					=			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      UpperCAmelCase__					( self			:Tuple )    ->      str:
												UpperCAmelCase					=			check_copies.find_code_in_transformers('models.bert.modeling_bert.BertLMPredictionHead' )
												self.assertEqual(__lowerCamelCase       ,  __lowerCamelCase )






						def      UpperCAmelCase__					( self			:Optional[Any] )    ->      Optional[Any]:
												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
												UpperCAmelCase					=			'''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      UpperCAmelCase__					( self			:Dict )    ->      int:
												UpperCAmelCase					=			check_copies.LOCALIZED_READMES['''README_zh-hans.md''']

												UpperCAmelCase					=			(
												    '''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					=			(
												    '''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					=			(
												    '''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					=			check_copies.convert_to_localized_md(
												    __lowerCamelCase       ,  __lowerCamelCase       ,  localized_readme['format_model_list'] )

												self.assertFalse(__lowerCamelCase )
												self.assertEqual(__lowerCamelCase       ,  __lowerCamelCase )

												UpperCAmelCase					=			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 )

												UpperCAmelCase					=			(
												    '''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					=			(
												    '''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					=			(
												    '''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					=			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"""


# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case_    					=	{
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_    					=	[
				    """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """CpmAntForCausalLM""",
				    """CpmAntModel""",
				    """CpmAntPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
				from .tokenization_cpmant import CpmAntTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_cpmant import (
								    CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    CpmAntForCausalLM,
								    CpmAntModel,
								    CpmAntPreTrainedModel,
								)


else:
				import sys

				snake_case_    					=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





