





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

import black


__UpperCAmelCase	:       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.
__UpperCAmelCase	:       Union[str, Any]    	=							"    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    __snake_case	(							unittest.TestCase      ):





       '''simple docstring'''







       def 							UpperCAmelCase__			(  self			:   List[str]		):
         __snake_case:						Union[str, Any]			  =						tempfile.mkdtemp()
         os.makedirs(os.path.join(self.transformer_dir							,    """models/bert/"""		)		)
         __snake_case:						Union[str, Any]			  =						self.transformer_dir
         shutil.copy(
             os.path.join(A							,    """src/transformers/models/bert/modeling_bert.py"""		)							,    os.path.join(self.transformer_dir							,    """models/bert/modeling_bert.py"""		)							,    )




       def 							UpperCAmelCase__			(  self			:   int		):
         __snake_case:						str			  =						"""src/transformers"""
         shutil.rmtree(self.transformer_dir		)




       def 							UpperCAmelCase__			(  self			:   int							,    A			:   str							,    A			:   Optional[Any]							,    A			:   Dict							,    A			:   Optional[Any]=None		):
         __snake_case:						Any			  =						comment + f'''\nclass {class_name}(nn.Module):\n''' + class_code
         if overwrite_result is not None:
           __snake_case:						List[Any]			  =						comment + f'''\nclass {class_name}(nn.Module):\n''' + overwrite_result
         __snake_case:						Any			  =						black.Mode(target_versions={black.TargetVersion.PYaa}							,    line_length=119		)
         __snake_case:						Any			  =						black.format_str(A							,    mode=A		)
         __snake_case:						List[Any]			  =						os.path.join(self.transformer_dir							,    """new_code.py"""		)
         with open(A							,    """w"""							,    newline="""\n"""		) as f:
           f.write(A		)
         if overwrite_result is None:
           self.assertTrue(len(check_copies.is_copy_consistent(A		)		) == 0		)
         else:
           check_copies.is_copy_consistent(f.name							,    overwrite=A		)
           with open(A							,    """r"""		) as f:
             self.assertTrue(f.read()							,    A		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         __snake_case:						List[str]			  =						check_copies.find_code_in_transformers("""models.bert.modeling_bert.BertLMPredictionHead"""		)
         self.assertEqual(A							,    A		)




       def 							UpperCAmelCase__			(  self			:   Dict		):
         # Base copy consistency
         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"""							,    A							,    )

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

         # Copy consistency with a really long name
         __snake_case:						Dict			  =						"""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"""							,    A							,    A		)							,    )

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






       def 							UpperCAmelCase__			(  self			:   List[str]		):
         __snake_case:						List[Any]			  =						check_copies.LOCALIZED_READMES["""README_zh-hans.md"""]

         __snake_case:						Tuple			  =						(
             """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."""
         )
         __snake_case:						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"""
         )
         __snake_case:						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。\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"""
         )

         __snake_case  ,       __snake_case:						int			  =						check_copies.convert_to_localized_md(
             A							,    A							,    localized_readme["""format_model_list"""]		)

         self.assertFalse(A		)
         self.assertEqual(A							,    A		)

         __snake_case  ,       __snake_case:						Union[str, Any]			  =						check_copies.convert_to_localized_md(
             A							,    A							,    localized_readme["""format_model_list"""]		)

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

         __snake_case:						Tuple			  =						(
             """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."""
         )
         __snake_case:						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"""
         )
         __snake_case:						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"""
         )

         __snake_case  ,       __snake_case:						str			  =						check_copies.convert_to_localized_md(
             A							,    A							,    localized_readme["""format_model_list"""]		)

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













import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    "The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
    " StableDiffusionImg2ImgPipeline` instead."
)






