



"""simple docstring"""





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

import black


SCREAMING_SNAKE_CASE					:  str        =						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.
SCREAMING_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    __lowerCamelCase						( unittest.TestCase     ):







   def 				A__    (self					):




      '''simple docstring'''




      _lowerCAmelCase         =		tempfile.mkdtemp()
      os.makedirs(os.path.join(self.transformer_dir							,						"""models/bert/"""					)					)
      _lowerCAmelCase         =		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 				A__    (self					):




      '''simple docstring'''




      _lowerCAmelCase         =		"""src/transformers"""
      shutil.rmtree(self.transformer_dir					)







   def 				A__    (self							,						lowerCamelCase							,						lowerCamelCase							,						lowerCamelCase							,						lowerCamelCase=None					):




      '''simple docstring'''




      _lowerCAmelCase         =		comment + f"""\nclass {class_name}(nn.Module):\n""" + class_code
      if overwrite_result is not None:
         _lowerCAmelCase         =		comment + f"""\nclass {class_name}(nn.Module):\n""" + overwrite_result
      _lowerCAmelCase         =		black.Mode(target_versions={black.TargetVersion.PYaa}							,						line_length=119					)
      _lowerCAmelCase         =		black.format_str(lowerCamelCase							,						mode=lowerCamelCase					)
      _lowerCAmelCase         =		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 				A__    (self					):




      '''simple docstring'''




      _lowerCAmelCase         =		check_copies.find_code_in_transformers("""models.bert.modeling_bert.BertLMPredictionHead"""					)
      self.assertEqual(lowerCamelCase							,						lowerCamelCase					)







   def 				A__    (self					):




      '''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"""							,						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         =		"""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 				A__    (self					):




      '''simple docstring'''




      _lowerCAmelCase         =		check_copies.LOCALIZED_READMES["""README_zh-hans.md"""]

      _lowerCAmelCase         =		(
          """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         =		(
          """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         =		(
          """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  ,    _lowerCAmelCase         =		check_copies.convert_to_localized_md(
          lowerCamelCase							,						lowerCamelCase							,						localized_readme["""format_model_list"""]					)

      self.assertFalse(lowerCamelCase					)
      self.assertEqual(lowerCamelCase							,						lowerCamelCase					)

      _lowerCAmelCase  ,    _lowerCAmelCase         =		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         =		(
          """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         =		(
          """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         =		(
          """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  ,    _lowerCAmelCase         =		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'''





def lowerCAmelCase    (__A):



     """simple docstring"""



     return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))




def lowerCAmelCase    (__A):



     """simple docstring"""



     _a           =    credit_card_number
     _a           =    0
     _a           =    len(__A) - 2
     for i in range(__A    ,      -1    ,      -2):
          #  double the value of every second digit
          _a           =    int(cc_number[i])
          digit *= 2
          # If doubling of a number results in a two digit number
          # i.e greater than 9(e.g., 6 × 2 = 12),
          # then add the digits of the product (e.g., 12: 1 + 2 = 3, 15: 1 + 5 = 6),
          # to get a single digit number.
          if digit > 9:
               digit %= 10
               digit += 1
          _a           =    cc_number[:i] + str(__A) + cc_number[i + 1 :]
          total += digit

     # Sum up the remaining digits
     for i in range(len(__A) - 1    ,      -1    ,      -2):
          total += int(cc_number[i])

     return total % 10 == 0




def lowerCAmelCase    (__A):



     """simple docstring"""



     _a           =    F'''{credit_card_number} is an invalid credit card number because'''
     if not credit_card_number.isdigit():
          print(F'''{error_message} it has nonnumerical characters.''')
          return False

     if not 13 <= len(__A) <= 16:
          print(F'''{error_message} of its length.''')
          return False

     if not validate_initial_digits(__A):
          print(F'''{error_message} of its first two digits.''')
          return False

     if not luhn_validation(__A):
          print(F'''{error_message} it fails the Luhn check.''')
          return False

     print(F'''{credit_card_number} is a valid credit card number.''')
     return True


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  validate_credit_card_number("4111111111111111")
  validate_credit_card_number("32323")



