


"""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
lowercase  		=			"""src/diffusers"""
lowercase  		=			"""docs/source/en"""
lowercase  		=			"""."""



def 			A__		(					_UpperCAmelCase    :      Optional[Any]				,    _UpperCAmelCase    :      Optional[int]				,    _UpperCAmelCase    :      str	)							->	Optional[Any]:

	'''simple docstring'''


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

	snake_case__  :						Union[str, 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 |
lowercase  		=			"""Model|Encoder|Decoder|ForConditionalGeneration"""
# Regexes that match TF/Flax/PT model names.
lowercase  		=			re.compile(r"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
lowercase  		=			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.
lowercase  		=			re.compile(r"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")


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



def 			A__		(					_UpperCAmelCase    :      Union[str, Any]	)							->	Tuple:

	'''simple docstring'''


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



def 			A__		(					_UpperCAmelCase    :      Any				,    _UpperCAmelCase    :      List[str]	)							->	Optional[int]:

	'''simple docstring'''


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



def 			A__		(					)							->	Any:

	'''simple docstring'''


	snake_case__  :						Optional[Any]		=      diffusers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
	snake_case__  :						Optional[int]		=      {
	    name: config_mapping_names[code]
	    for code, name in diffusers_module.MODEL_NAMES_MAPPING.items()
	    if code in config_mapping_names
	}
	snake_case__  :						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.
	snake_case__  :						Optional[Any]		=      collections.defaultdict(_UpperCAmelCase	)
	snake_case__  :						Optional[Any]		=      collections.defaultdict(_UpperCAmelCase	)
	snake_case__  :						Tuple		=      collections.defaultdict(_UpperCAmelCase	)
	snake_case__  :						List[Any]		=      collections.defaultdict(_UpperCAmelCase	)
	snake_case__  :						List[Any]		=      collections.defaultdict(_UpperCAmelCase	)

	# Let's lookup through all diffusers object (once).
	for attr_name in dir(_UpperCAmelCase	):
		snake_case__  :						str		=      None
		if attr_name.endswith("Tokenizer"	):
			snake_case__  :						Optional[int]		=      slow_tokenizers
			snake_case__  :						List[Any]		=      attr_name[:-9]
		elif attr_name.endswith("TokenizerFast"	):
			snake_case__  :						Optional[Any]		=      fast_tokenizers
			snake_case__  :						Tuple		=      attr_name[:-13]
		elif _re_tf_models.match(_UpperCAmelCase	) is not None:
			snake_case__  :						str		=      tf_models
			snake_case__  :						List[Any]		=      _re_tf_models.match(_UpperCAmelCase	).groups()[0]
		elif _re_flax_models.match(_UpperCAmelCase	) is not None:
			snake_case__  :						Dict		=      flax_models
			snake_case__  :						int		=      _re_flax_models.match(_UpperCAmelCase	).groups()[0]
		elif _re_pt_models.match(_UpperCAmelCase	) is not None:
			snake_case__  :						Optional[int]		=      pt_models
			snake_case__  :						List[Any]		=      _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():
					snake_case__  :						Optional[Any]		=      True
					break
				# Try again after removing the last word in the name
				snake_case__  :						List[str]		=      "".join(camel_case_split(_UpperCAmelCase	)[:-1]	)

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

	# Build the table per se
	snake_case__  :						Optional[int]		=      "|" + "|".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"

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



def 			A__		(					_UpperCAmelCase    :      str=False	)							->	List[Any]:

	'''simple docstring'''


	snake_case__,					snake_case__,					snake_case__,					snake_case__  :						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-->"				,    )
	snake_case__  :						Any		=      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__":
					lowercase  		=			argparse.ArgumentParser()
					parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
					lowercase  		=			parser.parse_args()

					check_model_table(args.fix_and_overwrite)













"""simple docstring"""



import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
						import jax




@require_flax
class 							__lowercase:






						def 		lowerCAmelCase (       self)      ->	str:




											"""simple docstring"""





											lowerCamelCase__					,  lowerCamelCase__					=self.prepare_init_args_and_inputs_for_common()

											lowerCamelCase__					=self.model_class(**_SCREAMING_SNAKE_CASE)
											lowerCamelCase__					=model.init(inputs_dict['prng_key']     ,    inputs_dict['sample'])
											jax.lax.stop_gradient(_SCREAMING_SNAKE_CASE)

											lowerCamelCase__					=model.apply(_SCREAMING_SNAKE_CASE     ,    inputs_dict['sample'])

											if isinstance(_SCREAMING_SNAKE_CASE     ,    _SCREAMING_SNAKE_CASE):
																lowerCamelCase__					=output.sample

											self.assertIsNotNone(_SCREAMING_SNAKE_CASE)
											lowerCamelCase__					=inputs_dict['sample'].shape
											self.assertEqual(output.shape     ,    _SCREAMING_SNAKE_CASE     ,    'Input and output shapes do not match')






						def 		lowerCAmelCase (       self)      ->	Optional[Any]:




											"""simple docstring"""





											lowerCamelCase__					,  lowerCamelCase__					=self.prepare_init_args_and_inputs_for_common()

											lowerCamelCase__					=16
											lowerCamelCase__					=(16, 32)

											lowerCamelCase__					=self.model_class(**_SCREAMING_SNAKE_CASE)
											lowerCamelCase__					=model.init(inputs_dict['prng_key']     ,    inputs_dict['sample'])
											jax.lax.stop_gradient(_SCREAMING_SNAKE_CASE)

											lowerCamelCase__					=model.apply(_SCREAMING_SNAKE_CASE     ,    inputs_dict['sample'])

											if isinstance(_SCREAMING_SNAKE_CASE     ,    _SCREAMING_SNAKE_CASE):
																lowerCamelCase__					=output.sample

											self.assertIsNotNone(_SCREAMING_SNAKE_CASE)
											lowerCamelCase__					=inputs_dict['sample'].shape
											self.assertEqual(output.shape     ,    _SCREAMING_SNAKE_CASE     ,    'Input and output shapes do not match')






						def 		lowerCAmelCase (       self)      ->	Optional[Any]:




											"""simple docstring"""





											lowerCamelCase__					='kwargs' in inspect.signature(self.model_class.__init__).parameters
											lowerCamelCase__					=len(self.model_class._deprecated_kwargs) > 0

											if has_kwarg_in_model_class and not has_deprecated_kwarg:
																raise ValueError(
																    F"{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs"
																    ' under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are'
																    ' no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ='
																    ' [<deprecated_argument>]`')

											if not has_kwarg_in_model_class and has_deprecated_kwarg:
																raise ValueError(
																    F"{self.model_class} doesn't have `**kwargs` in its __init__ method but has defined deprecated kwargs"
																    ' under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to'
																    F" {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument"
																    ' from `_deprecated_kwargs = [<deprecated_argument>]`')