






"""simple docstring"""





import argparse
import collections
import importlib.util
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
UpperCamelCase					=     """src/diffusers"""
UpperCamelCase					=     """docs/source/en"""
UpperCamelCase					=     """."""






def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       with open(snake_case_		,  "r"		,  encoding="utf-8"		,  newline="\n"						) as f:
              lowercase__:							int         =     f.readlines()
       # Find the start prompt.
       lowercase__:							Union[str, Any]         =     0
       while not lines[start_index].startswith(snake_case_						):
              start_index += 1
       start_index += 1

       lowercase__:							Union[str, Any]         =     start_index
       while not lines[end_index].startswith(snake_case_						):
              end_index += 1
       end_index -= 1

       while len(lines[start_index]						) <= 1:
              start_index += 1
       while len(lines[end_index]						) <= 1:
              end_index -= 1
       end_index += 1
       return "".join(lines[start_index:end_index]						), start_index, end_index, lines


# Add here suffixes that are used to identify models, separated by |
UpperCamelCase					=     """Model|Encoder|Decoder|ForConditionalGeneration"""
# Regexes that match TF/Flax/PT model names.
UpperCamelCase					=     re.compile(r"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
UpperCamelCase					=     re.compile(r"""Flax(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
# Will match any TF or Flax model too so need to be in an else branch afterthe two previous regexes.
UpperCamelCase					=     re.compile(r"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")


# This is to make sure the diffusers module imported is the one in the repo.
UpperCamelCase					=     importlib.util.spec_from_file_location(
    """diffusers""",
    os.path.join(TRANSFORMERS_PATH, """__init__.py"""),
    submodule_search_locations=[TRANSFORMERS_PATH],
)
UpperCamelCase					=     spec.loader.load_module()






def 							A(    snake_case_						):
       """simple docstring"""





       lowercase__:							Union[str, Any]         =     re.finditer(".+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)"		,  snake_case_						)
       return [m.group(0						) for m in matches]






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							str         =     2 if text == "✅" or text == "❌" else len(snake_case_						)
       lowercase__:							Union[str, Any]         =     (width - text_length) // 2
       lowercase__:							int         =     width - text_length - left_indent
       return " " * left_indent + text + " " * right_indent






def 							A(    ):
       """simple docstring"""





       lowercase__:							List[str]         =     diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
       lowercase__:							Optional[Any]         =     {
           name: config_mapping_names[code]
           for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
           if code in config_mapping_names
       }
       lowercase__:							Optional[Any]         =     {name: config.replace("ConfigMixin"		,  ""						) for name, config in model_name_to_config.items()}

       # Dictionaries flagging if each model prefix has a slow/fast tokenizer, backend in PT/TF/Flax.
       lowercase__:							List[str]         =     collections.defaultdict(snake_case_						)
       lowercase__:							Union[str, Any]         =     collections.defaultdict(snake_case_						)
       lowercase__:							Optional[int]         =     collections.defaultdict(snake_case_						)
       lowercase__:							int         =     collections.defaultdict(snake_case_						)
       lowercase__:							int         =     collections.defaultdict(snake_case_						)

       # Let's lookup through all diffusers object (once).
       for attr_name in dir(snake_case_						):
              lowercase__:							Union[str, Any]         =     None
              if attr_name.endswith("Tokenizer"						):
                     lowercase__:							str         =     slow_tokenizers
                     lowercase__:							str         =     attr_name[:-9]
              elif attr_name.endswith("TokenizerFast"						):
                     lowercase__:							Union[str, Any]         =     fast_tokenizers
                     lowercase__:							Optional[int]         =     attr_name[:-13]
              elif _re_tf_models.match(snake_case_						) is not None:
                     lowercase__:							List[str]         =     tf_models
                     lowercase__:							List[Any]         =     _re_tf_models.match(snake_case_						).groups()[0]
              elif _re_flax_models.match(snake_case_						) is not None:
                     lowercase__:							Union[str, Any]         =     flax_models
                     lowercase__:							Optional[int]         =     _re_flax_models.match(snake_case_						).groups()[0]
              elif _re_pt_models.match(snake_case_						) is not None:
                     lowercase__:							Any         =     pt_models
                     lowercase__:							Optional[Any]         =     _re_pt_models.match(snake_case_						).groups()[0]

              if lookup_dict is not None:
                     while len(snake_case_						) > 0:
                            if attr_name in model_name_to_prefix.values():
                                   lowercase__:							Dict         =     True
                                   break
                            # Try again after removing the last word in the name
                            lowercase__:							List[str]         =     "".join(camel_case_split(snake_case_						)[:-1]						)

    # Let's build that table!
       lowercase__:							str         =     list(model_name_to_config.keys()						)
       model_names.sort(key=str.lower						)
       lowercase__:							Any         =     ["Model", "Tokenizer slow", "Tokenizer fast", "PyTorch support", "TensorFlow support", "Flax Support"]
       # We'll need widths to properly display everything in the center (+2 is to leave one extra space on each side).
       lowercase__:							List[str]         =     [len(snake_case_						) + 2 for c in columns]
       lowercase__:							Optional[int]         =     max([len(snake_case_						) for name in model_names]						) + 2

       # Build the table per se
       lowercase__:							List[Any]         =     "|" + "|".join([_center_text(snake_case_		,  snake_case_						) for c, w in zip(snake_case_		,  snake_case_						)]						) + "|\n"
       # Use ":-----:" format to center-aligned table cell texts
       table += "|" + "|".join([":" + "-" * (w - 2) + ":" for w in widths]						) + "|\n"

       lowercase__:							Dict         =     {True: "✅", False: "❌"}
       for name in model_names:
              lowercase__:							str         =     model_name_to_prefix[name]
              lowercase__:							Union[str, Any]         =     [
                  name,
                  check[slow_tokenizers[prefix]],
                  check[fast_tokenizers[prefix]],
                  check[pt_models[prefix]],
                  check[tf_models[prefix]],
                  check[flax_models[prefix]],
              ]
              table += "|" + "|".join([_center_text(snake_case_		,  snake_case_						) for l, w in zip(snake_case_		,  snake_case_						)]						) + "|\n"
       return table






def 							A(    snake_case_=False						):
       """simple docstring"""





       lowercase__    ,      lowercase__    ,      lowercase__    ,      lowercase__:							Any         =     _find_text_in_file(
           filename=os.path.join(snake_case_		,  "index.mdx"						)		,  start_prompt="<!--This table is updated automatically from the auto modules"		,  end_prompt="<!-- End table-->"		,  )
       lowercase__:							Any         =     get_model_table_from_auto_modules()

       if current_table != new_table:
              if overwrite:
                     with open(os.path.join(snake_case_		,  "index.mdx"						)		,  "w"		,  encoding="utf-8"		,  newline="\n"						) as f:
                            f.writelines(lines[:start_index] + [new_table] + lines[end_index:]						)
              else:
                     raise ValueError(
                         "The model table in the `index.mdx` has not been updated. Run `make fix-copies` to fix this."						)


if __name__ == "__main__":
  UpperCamelCase					=     argparse.ArgumentParser()
  parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
  UpperCamelCase					=     parser.parse_args()

  check_model_table(args.fix_and_overwrite)











import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase







@require_tokenizers
class 				a_    (						unittest.TestCase							):
						UpperCamelCase__ :		Any										=EsmTokenizer

						def       __a			(       self      :Optional[int])						->   Optional[int]:
												super().setUp()
												UpperCAmelCase_					=	tempfile.mkdtemp()
												# fmt: off
												UpperCAmelCase_					=	["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
												# fmt: on
												UpperCAmelCase_					=	os.path.join(self.tmpdirname  ,		VOCAB_FILES_NAMES['''vocab_file'''])
												with open(self.vocab_file  ,		'''w'''  ,		encoding='''utf-8''') as vocab_writer:
																		vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]))

						def       __a			(       self      :List[str]  ,		**_lowercase      :Union[str, Any])						->   List[PreTrainedTokenizerBase]:
												return [self.get_tokenizer(**_lowercase)]

						def       __a			(       self      :Optional[int]  ,		**_lowercase      :List[str])						->   PreTrainedTokenizer:
												return self.tokenizer_class.from_pretrained(self.tmpdirname  ,		**_lowercase)

						def       __a			(       self      :int)						->   Any:
												UpperCAmelCase_					=	self.tokenizer_class(self.vocab_file)

												UpperCAmelCase_					=	tokenizer.tokenize('''LAGVS''')
												self.assertListEqual(_lowercase  ,		['''L''', '''A''', '''G''', '''V''', '''S'''])
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase)  ,		[4, 5, 6, 7, 8])

						def       __a			(       self      :List[Any])						->   Optional[int]:
												UpperCAmelCase_					=	self.tokenizer_class(self.vocab_file)

												UpperCAmelCase_					=	'''LAGVS'''
												self.assertListEqual(tokenizer.encode(_lowercase)  ,		[0, 4, 5, 6, 7, 8, 2])

						def       __a			(       self      :Tuple)						->   Union[str, Any]:
												UpperCAmelCase_					=	self.tokenizer_class(self.vocab_file)

												UpperCAmelCase_					=	['''LAGVS''', '''WCB''']
												UpperCAmelCase_					=	tokenizer(_lowercase  ,		padding=_lowercase)['''input_ids''']

												self.assertListEqual(_lowercase  ,		[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]])

						def       __a			(       self      :str)						->   Any:
												UpperCAmelCase_					=	self.tokenizer_class(self.vocab_file)

												UpperCAmelCase_					=	['''LAGVS''', '''WCB''']
												UpperCAmelCase_					=	tokenizer(_lowercase  ,		padding=_lowercase)['''input_ids''']

												self.assertListEqual(_lowercase  ,		[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]])




						def       __a			(       self      :Dict)						->   Optional[int]:
												UpperCAmelCase_					=	self.get_tokenizers(fast=_lowercase)
												for tokenizer in tokenizers:
																		with self.subTest(f"{tokenizer.__class__.__name__}"):
																								UpperCAmelCase_					=	'''<unk>'''
																								UpperCAmelCase_					=	'''<mask>'''

																								UpperCAmelCase_					=	tokenizer.tokenize(_lowercase)
																								UpperCAmelCase_					=	tokenizer.tokenize(_lowercase)

																								self.assertEqual(len(_lowercase)  ,		1)
																								self.assertEqual(len(_lowercase)  ,		1)
																								self.assertEqual(token_a[0]  ,		_lowercase)
																								self.assertEqual(token_a[0]  ,		_lowercase)





