

"""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__ :    Dict 					=							"src/diffusers"
UpperCamelCase__ :    Tuple 					=							"docs/source/en"
UpperCamelCase__ :    Optional[Any] 					=							"."




def       snake_case__	(       lowerCAmelCase   :		Optional[Any]				,					lowerCAmelCase   :		Dict				,					lowerCAmelCase   :		int		):
					with open(lowerCAmelCase				,					"""r"""				,					encoding="""utf-8"""				,					newline="""\n"""		) as f:
										__snake_case          =	f.readlines()
					# Find the start prompt.
					__snake_case          =	0
					while not lines[start_index].startswith(lowerCAmelCase		):
										start_index += 1
					start_index += 1

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


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




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




def       snake_case__	(       lowerCAmelCase   :		List[Any]				,					lowerCAmelCase   :		Any		):
					__snake_case          =	2 if text == """✅""" or text == """❌""" else len(lowerCAmelCase		)
					__snake_case          =	(width - text_length) // 2
					__snake_case          =	width - text_length - left_indent
					return " " * left_indent + text + " " * right_indent




def       snake_case__	(       ):
					__snake_case          =	diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
					__snake_case          =	{
					    name: config_mapping_names[code]
					    for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
					    if code in config_mapping_names
					}
					__snake_case          =	{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.
					__snake_case          =	collections.defaultdict(lowerCAmelCase		)
					__snake_case          =	collections.defaultdict(lowerCAmelCase		)
					__snake_case          =	collections.defaultdict(lowerCAmelCase		)
					__snake_case          =	collections.defaultdict(lowerCAmelCase		)
					__snake_case          =	collections.defaultdict(lowerCAmelCase		)

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

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

    # Let's build that table!
					__snake_case          =	list(model_name_to_config.keys()		)
					model_names.sort(key=str.lower		)
					__snake_case          =	["""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).
					__snake_case          =	[len(lowerCAmelCase		) + 2 for c in columns]
					__snake_case          =	max([len(lowerCAmelCase		) for name in model_names]		) + 2

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

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




def       snake_case__	(       lowerCAmelCase   :		Optional[Any]=False		):
					__snake_case      ,      __snake_case      ,      __snake_case      ,      __snake_case          =	_find_text_in_file(
					    filename=os.path.join(lowerCAmelCase				,					"""index.mdx"""		)				,					start_prompt="""<!--This table is updated automatically from the auto modules"""				,					end_prompt="""<!-- End table-->"""				,					)
					__snake_case          =	get_model_table_from_auto_modules()

					if current_table != new_table:
										if overwrite:
															with open(os.path.join(lowerCAmelCase				,					"""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__ :    Union[str, Any] 					=							argparse.ArgumentParser()
		parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
		UpperCamelCase__ :    Optional[Any] 					=							parser.parse_args()

		check_model_table(args.fix_and_overwrite)








"""simple docstring"""

import functools
from math import sqrt
from time import time




def       snake_case__	(       lowerCAmelCase   :		int				,					*lowerCAmelCase   :		str				,					**lowerCAmelCase   :		List[Any]		):
					__snake_case          =	time()
					__snake_case          =	func(*lowerCAmelCase				,					**lowerCAmelCase		)
					__snake_case          =	time()
					if int(end - start		) > 0:
										print(F'''{func.__name__} runtime: {(end - start):0.4f} s'''		)
					else:
										print(F'''{func.__name__} runtime: {(end - start) * 1_000:0.4f} ms'''		)
					return output




def       snake_case__	(       lowerCAmelCase   :		int		):
					if n < 0:
										raise Exception("""n is negative"""		)
					if n == 0:
										return [0]
					__snake_case          =	[0, 1]
					for _ in range(n - 1		):
										fib.append(fib[-1] + fib[-2]		)
					return fib




def       snake_case__	(       lowerCAmelCase   :		int		):

					def fib_recursive_term(lowerCAmelCase   :		int		) -> int:
										if i < 0:
															raise Exception("""n is negative"""		)
										if i < 2:
															return i
										return fib_recursive_term(i - 1		) + fib_recursive_term(i - 2		)

					if n < 0:
										raise Exception("""n is negative"""		)
					return [fib_recursive_term(lowerCAmelCase		) for i in range(n + 1		)]




def       snake_case__	(       lowerCAmelCase   :		int		):

					@functools.cache
					def fib_recursive_term(lowerCAmelCase   :		int		) -> int:
										if i < 0:
															raise Exception("""n is negative"""		)
										if i < 2:
															return i
										return fib_recursive_term(i - 1		) + fib_recursive_term(i - 2		)

					if n < 0:
										raise Exception("""n is negative"""		)
					return [fib_recursive_term(lowerCAmelCase		) for i in range(n + 1		)]




def       snake_case__	(       lowerCAmelCase   :		int		):
					if n < 0:
										raise Exception("""n is negative"""		)
					# Cache must be outside recursuive function
					# other it will reset every time it calls itself.
					__snake_case          =	{0: 0, 1: 1, 2: 1}  # Prefilled cache

					def rec_fn_memoized(lowerCAmelCase   :		int		) -> int:
										if num in cache:
															return cache[num]

										__snake_case          =	rec_fn_memoized(num - 1		) + rec_fn_memoized(num - 2		)
										__snake_case          =	value
										return value

					return [rec_fn_memoized(lowerCAmelCase		) for i in range(n + 1		)]




def       snake_case__	(       lowerCAmelCase   :		int		):
					if n < 0:
										raise Exception("""n is negative"""		)
					if n >= 1_475:
										raise Exception("""n is too large"""		)
					__snake_case          =	sqrt(5		)
					__snake_case          =	(1 + sqrt_a) / 2
					return [round(phi**i / sqrt_a		) for i in range(n + 1		)]


if __name__ == "__main__":
		UpperCamelCase__ :    Optional[Any] 					=							30
		time_func(fib_iterative, num)
		time_func(fib_recursive, num)  # Around 3s runtime
		time_func(fib_recursive_cached, num)  # Around 0ms runtime
		time_func(fib_memoization, num)
		time_func(fib_binet, num)


