





'''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
snake_case_  :							Union[str, Any]            =	"src/diffusers"
snake_case_  :							List[str]            =	"docs/source/en"
snake_case_  :							str            =	"."





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      Union[str, Any],      SCREAMING_SNAKE_CASE__   :      Tuple,      SCREAMING_SNAKE_CASE__   :      Optional[int] )			->						Tuple:






						with open(__UpperCAmelCase,      '''r''',      encoding='''utf-8''',      newline='''\n''' ) as f:
												UpperCAmelCase_      :   int      =	f.readlines()
						# Find the start prompt.
						UpperCAmelCase_      :   int      =	0
						while not lines[start_index].startswith(__UpperCAmelCase ):
												start_index += 1
						start_index += 1

						UpperCAmelCase_      :   Optional[Any]      =	start_index
						while not lines[end_index].startswith(__UpperCAmelCase ):
												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 |
snake_case_  :							List[Any]            =	"Model|Encoder|Decoder|ForConditionalGeneration"
# Regexes that match TF/Flax/PT model names.
snake_case_  :							Optional[int]            =	re.compile(r"TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")
snake_case_  :							str            =	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.
snake_case_  :							Optional[Any]            =	re.compile(r"(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)")


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





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      List[Any] )			->						str:
						UpperCAmelCase_      :   List[Any]      =	re.finditer('''.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)''',      __UpperCAmelCase )
						return [m.group(0 ) for m in matches]





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      List[str],      SCREAMING_SNAKE_CASE__   :      Any )			->						Dict:
						UpperCAmelCase_      :   Union[str, Any]      =	2 if text == '''✅''' or text == '''❌''' else len(__UpperCAmelCase )
						UpperCAmelCase_      :   Dict      =	(width - text_length) // 2
						UpperCAmelCase_      :   int      =	width - text_length - left_indent
						return " " * left_indent + text + " " * right_indent





def 							lowerCamelCase_   (	)			->						Optional[Any]:
						UpperCAmelCase_      :   Optional[Any]      =	diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
						UpperCAmelCase_      :   int      =	{
						    name: config_mapping_names[code]
						    for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
						    if code in config_mapping_names
						}
						UpperCAmelCase_      :   int      =	{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.
						UpperCAmelCase_      :   Tuple      =	collections.defaultdict(__UpperCAmelCase )
						UpperCAmelCase_      :   str      =	collections.defaultdict(__UpperCAmelCase )
						UpperCAmelCase_      :   Optional[int]      =	collections.defaultdict(__UpperCAmelCase )
						UpperCAmelCase_      :   List[Any]      =	collections.defaultdict(__UpperCAmelCase )
						UpperCAmelCase_      :   Optional[int]      =	collections.defaultdict(__UpperCAmelCase )

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

												if lookup_dict is not None:
																		while len(__UpperCAmelCase ) > 0:
																								if attr_name in model_name_to_prefix.values():
																														UpperCAmelCase_      :   Any      =	True
																														break
																								# Try again after removing the last word in the name
																								UpperCAmelCase_      :   Optional[Any]      =	''''''.join(camel_case_split(__UpperCAmelCase )[:-1] )

    # Let's build that table!
						UpperCAmelCase_      :   Dict      =	list(model_name_to_config.keys() )
						model_names.sort(key=str.lower )
						UpperCAmelCase_      :   int      =	['''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).
						UpperCAmelCase_      :   Any      =	[len(__UpperCAmelCase ) + 2 for c in columns]
						UpperCAmelCase_      :   Optional[Any]      =	max([len(__UpperCAmelCase ) for name in model_names] ) + 2

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

						UpperCAmelCase_      :   Tuple      =	{True: '''✅''', False: '''❌'''}
						for name in model_names:
												UpperCAmelCase_      :   Tuple      =	model_name_to_prefix[name]
												UpperCAmelCase_      :   int      =	[
												    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(__UpperCAmelCase,      __UpperCAmelCase ) for l, w in zip(__UpperCAmelCase,      __UpperCAmelCase )] ) + "|\n"
						return table





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      List[str]=False )			->						Dict:
						UpperCAmelCase_    ,							UpperCAmelCase_    ,							UpperCAmelCase_    ,							UpperCAmelCase_      :   List[str]      =	_find_text_in_file(
						    filename=os.path.join(__UpperCAmelCase,      '''index.mdx''' ),      start_prompt='''<!--This table is updated automatically from the auto modules''',      end_prompt='''<!-- End table-->''',      )
						UpperCAmelCase_      :   List[str]      =	get_model_table_from_auto_modules()

						if current_table != new_table:
												if overwrite:
																		with open(os.path.join(__UpperCAmelCase,      '''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__":
					snake_case_  :							List[Any]            =	argparse.ArgumentParser()
					parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
					snake_case_  :							int            =	parser.parse_args()

					check_model_table(args.fix_and_overwrite)










def 							A     (						__UpperCAmelCase				,   __UpperCAmelCase      )			->			int:



						'''simple docstring'''






						print('''\nVertex Distance'''      )
						for i in range(__UpperCAmelCase      ):
												if dist[i] != float('''inf'''      ):
																		print(__UpperCAmelCase				,   '''\t'''				,   int(dist[i]      )				,   end='''\t'''      )
												else:
																		print(__UpperCAmelCase				,   '''\t'''				,   '''INF'''				,   end='''\t'''      )
												print()







def 							A     (						__UpperCAmelCase				,   __UpperCAmelCase				,   __UpperCAmelCase      )			->			str:



						'''simple docstring'''






						UpperCAmelCase_					=	float('''inf'''      )
						UpperCAmelCase_					=	-1
						for i in range(__UpperCAmelCase      ):
												if (not vset[i]) and mdist[i] < min_val:
																		UpperCAmelCase_					=	i
																		UpperCAmelCase_					=	mdist[i]
						return min_ind







def 							A     (						__UpperCAmelCase				,   __UpperCAmelCase				,   __UpperCAmelCase      )			->			Optional[Any]:



						'''simple docstring'''






						UpperCAmelCase_					=	[float('''inf'''      ) for _ in range(__UpperCAmelCase      )]
						UpperCAmelCase_					=	[False for _ in range(__UpperCAmelCase      )]
						UpperCAmelCase_					=	0.0

						for _ in range(v - 1      ):
												UpperCAmelCase_					=	min_dist(__UpperCAmelCase				,   __UpperCAmelCase				,   __UpperCAmelCase      )
												UpperCAmelCase_					=	True

												for i in range(__UpperCAmelCase      ):
																		if (
																		    (not vset[i])
																		    and graph[u][i] != float('''inf'''      )
																		    and mdist[u] + graph[u][i] < mdist[i]
																		):
																								UpperCAmelCase_					=	mdist[u] + graph[u][i]

						print_dist(__UpperCAmelCase				,   __UpperCAmelCase      )


if __name__ == "__main__":
							UpperCamelCase_      			=  int(input("Enter number of vertices: ").strip())
							UpperCamelCase_      			=  int(input("Enter number of edges: ").strip())

							UpperCamelCase_      			=  [[float("inf") for i in range(V)] for j in range(V)]

							for i in range(V):
														UpperCamelCase_      			=  0.0

							for i in range(E):
														print("\nEdge ", i + 1)
														UpperCamelCase_      			=  int(input("Enter source:").strip())
														UpperCamelCase_      			=  int(input("Enter destination:").strip())
														UpperCamelCase_      			=  float(input("Enter weight:").strip())
														UpperCamelCase_      			=  weight

							UpperCamelCase_      			=  int(input("\nEnter shortest path source:").strip())
							dijkstra(graph, V, gsrc)





