






"""simple docstring"""



import collections
import importlib.util
import os
import re
from pathlib import Path


A_      =							'''src/transformers'''


# Matches is_xxx_available()
A_      =							re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
A_      =							re.compile(r'''^_import_structure\s+=\s+\{([^\}]+)\}''')
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
A_      =							re.compile(r'''\s+"\S*":\s+\[([^\]]*)\]''')
# Catches a line if not is_foo_available
A_      =							re.compile(r'''^\s*if\s+not\s+is\_[a-z_]*\_available\(\)''')
# Catches a line _import_struct["bla"].append("foo")
A_      =							re.compile(r'''^\s*_import_structure\["\S*"\]\.append\("(\S*)"\)''')
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
A_      =							re.compile(r'''^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]''')
# Catches a line with an object between quotes and a comma:     "MyModel",
A_      =							re.compile('''^\s+"([^"]+)",''')
# Catches a line with objects between brackets only:    ["foo", "bar"],
A_      =							re.compile('''^\s+\[([^\]]+)\]''')
# Catches a line with from foo import bar, bla, boo
A_      =							re.compile(r'''\s+from\s+\S*\s+import\s+([^\(\s].*)\n''')
# Catches a line with try:
A_      =							re.compile(r'''^\s*try:''')
# Catches a line with else:
A_      =							re.compile(r'''^\s*else:''')




def        _lowerCAmelCase						(							UpperCAmelCase__    :   str )						->Union[str, Any]:
						if _re_test_backend.search(UpperCAmelCase__ ) is None:
												return None
						A__  :					Tuple											=					[b[0] for b in _re_backend.findall(UpperCAmelCase__ )]
						backends.sort()
						return "_and_".join(UpperCAmelCase__ )




def        _lowerCAmelCase						(							UpperCAmelCase__    :   str )						->str:
						with open(UpperCAmelCase__,  """r""",  encoding="""utf-8""",  newline="""\n""" ) as f:
												A__  :					Union[str, Any]											=					f.readlines()

						A__  :					List[str]											=					0
						while line_index < len(UpperCAmelCase__ ) and not lines[line_index].startswith("""_import_structure = {""" ):
												line_index += 1

						# If this is a traditional init, just return.
						if line_index >= len(UpperCAmelCase__ ):
												return None

						# First grab the objects without a specific backend in _import_structure
						A__  :					List[Any]											=					[]
						while not lines[line_index].startswith("""if TYPE_CHECKING""" ) and find_backend(lines[line_index] ) is None:
												A__  :					Optional[Any]											=					lines[line_index]
												# If we have everything on a single line, let's deal with it.
												if _re_one_line_import_struct.search(UpperCAmelCase__ ):
																		A__  :					Optional[int]											=					_re_one_line_import_struct.search(UpperCAmelCase__ ).groups()[0]
																		A__  :					int											=					re.findall("""\[([^\]]+)\]""",  UpperCAmelCase__ )
																		for imp in imports:
																								objects.extend([obj[1:-1] for obj in imp.split(""", """ )] )
																		line_index += 1
																		continue
												A__  :					Optional[Any]											=					_re_import_struct_key_value.search(UpperCAmelCase__ )
												if single_line_import_search is not None:
																		A__  :					List[str]											=					[obj[1:-1] for obj in single_line_import_search.groups()[0].split(""", """ ) if len(UpperCAmelCase__ ) > 0]
																		objects.extend(UpperCAmelCase__ )
												elif line.startswith(""" """ * 8 + """\"""" ):
																		objects.append(line[9:-3] )
												line_index += 1

						A__  :					str											=					{"""none""": objects}
						# Let's continue with backend-specific objects in _import_structure
						while not lines[line_index].startswith("""if TYPE_CHECKING""" ):
												# If the line is an if not is_backend_available, we grab all objects associated.
												A__  :					str											=					find_backend(lines[line_index] )
												# Check if the backend declaration is inside a try block:
												if _re_try.search(lines[line_index - 1] ) is None:
																		A__  :					List[str]											=					None

												if backend is not None:
																		line_index += 1

																		# Scroll until we hit the else block of try-except-else
																		while _re_else.search(lines[line_index] ) is None:
																								line_index += 1

																		line_index += 1

																		A__  :					Tuple											=					[]
																		# Until we unindent, add backend objects to the list
																		while len(lines[line_index] ) <= 1 or lines[line_index].startswith(""" """ * 4 ):
																								A__  :					Any											=					lines[line_index]
																								if _re_import_struct_add_one.search(UpperCAmelCase__ ) is not None:
																														objects.append(_re_import_struct_add_one.search(UpperCAmelCase__ ).groups()[0] )
																								elif _re_import_struct_add_many.search(UpperCAmelCase__ ) is not None:
																														A__  :					Optional[int]											=					_re_import_struct_add_many.search(UpperCAmelCase__ ).groups()[0].split(""", """ )
																														A__  :					Tuple											=					[obj[1:-1] for obj in imports if len(UpperCAmelCase__ ) > 0]
																														objects.extend(UpperCAmelCase__ )
																								elif _re_between_brackets.search(UpperCAmelCase__ ) is not None:
																														A__  :					Any											=					_re_between_brackets.search(UpperCAmelCase__ ).groups()[0].split(""", """ )
																														A__  :					Tuple											=					[obj[1:-1] for obj in imports if len(UpperCAmelCase__ ) > 0]
																														objects.extend(UpperCAmelCase__ )
																								elif _re_quote_object.search(UpperCAmelCase__ ) is not None:
																														objects.append(_re_quote_object.search(UpperCAmelCase__ ).groups()[0] )
																								elif line.startswith(""" """ * 8 + """\"""" ):
																														objects.append(line[9:-3] )
																								elif line.startswith(""" """ * 1_2 + """\"""" ):
																														objects.append(line[1_3:-3] )
																								line_index += 1

																		A__  :					str											=					objects
												else:
																		line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
						A__  :					Union[str, Any]											=					[]
						while (
						    line_index < len(UpperCAmelCase__ )
						    and find_backend(lines[line_index] ) is None
						    and not lines[line_index].startswith("""else""" )
						):
												A__  :					Optional[Any]											=					lines[line_index]
												A__  :					List[str]											=					_re_import.search(UpperCAmelCase__ )
												if single_line_import_search is not None:
																		objects.extend(single_line_import_search.groups()[0].split(""", """ ) )
												elif line.startswith(""" """ * 8 ):
																		objects.append(line[8:-2] )
												line_index += 1

						A__  :					List[Any]											=					{"""none""": objects}
						# Let's continue with backend-specific objects
						while line_index < len(UpperCAmelCase__ ):
												# If the line is an if is_backend_available, we grab all objects associated.
												A__  :					Dict											=					find_backend(lines[line_index] )
												# Check if the backend declaration is inside a try block:
												if _re_try.search(lines[line_index - 1] ) is None:
																		A__  :					List[Any]											=					None

												if backend is not None:
																		line_index += 1

																		# Scroll until we hit the else block of try-except-else
																		while _re_else.search(lines[line_index] ) is None:
																								line_index += 1

																		line_index += 1

																		A__  :					Optional[int]											=					[]
																		# Until we unindent, add backend objects to the list
																		while len(lines[line_index] ) <= 1 or lines[line_index].startswith(""" """ * 8 ):
																								A__  :					int											=					lines[line_index]
																								A__  :					List[Any]											=					_re_import.search(UpperCAmelCase__ )
																								if single_line_import_search is not None:
																														objects.extend(single_line_import_search.groups()[0].split(""", """ ) )
																								elif line.startswith(""" """ * 1_2 ):
																														objects.append(line[1_2:-2] )
																								line_index += 1

																		A__  :					Tuple											=					objects
												else:
																		line_index += 1

						return import_dict_objects, type_hint_objects




def        _lowerCAmelCase						(							UpperCAmelCase__    :   int,  UpperCAmelCase__    :   int )						->List[str]:

						def find_duplicates(UpperCAmelCase__    :   str ):
												return [k for k, v in collections.Counter(UpperCAmelCase__ ).items() if v > 1]

						if list(import_dict_objects.keys() ) != list(type_hint_objects.keys() ):
												return ["Both sides of the init do not have the same backends!"]

						A__  :					int											=					[]
						for key in import_dict_objects.keys():
												A__  :					Tuple											=					find_duplicates(import_dict_objects[key] )
												if duplicate_imports:
																		errors.append(f'Duplicate _import_structure definitions for: {duplicate_imports}' )
												A__  :					Optional[Any]											=					find_duplicates(type_hint_objects[key] )
												if duplicate_type_hints:
																		errors.append(f'Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}' )

												if sorted(set(import_dict_objects[key] ) ) != sorted(set(type_hint_objects[key] ) ):
																		A__  :					List[Any]											=					"""base imports""" if key == """none""" else f'{key} backend'
																		errors.append(f'Differences for {name}:' )
																		for a in type_hint_objects[key]:
																								if a not in import_dict_objects[key]:
																														errors.append(f'  {a} in TYPE_HINT but not in _import_structure.' )
																		for a in import_dict_objects[key]:
																								if a not in type_hint_objects[key]:
																														errors.append(f'  {a} in _import_structure but not in TYPE_HINT.' )
						return errors




def        _lowerCAmelCase						(							)						->Optional[Any]:
						A__  :					str											=					[]
						for root, _, files in os.walk(UpperCAmelCase__ ):
												if "__init__.py" in files:
																		A__  :					str											=					os.path.join(UpperCAmelCase__,  """__init__.py""" )
																		A__  :					Tuple											=					parse_init(UpperCAmelCase__ )
																		if objects is not None:
																								A__  :					str											=					analyze_results(*UpperCAmelCase__ )
																								if len(UpperCAmelCase__ ) > 0:
																														A__  :					Any											=					f'Problem in {fname}, both halves do not define the same objects.\n{errors[0]}'
																														failures.append("""\n""".join(UpperCAmelCase__ ) )
						if len(UpperCAmelCase__ ) > 0:
												raise ValueError("""\n\n""".join(UpperCAmelCase__ ) )




def        _lowerCAmelCase						(							)						->Optional[int]:
						A__  :					List[Any]											=					[]
						for path, directories, files in os.walk(UpperCAmelCase__ ):
												for folder in directories:
																		# Ignore private modules
																		if folder.startswith("""_""" ):
																								directories.remove(UpperCAmelCase__ )
																								continue
																		# Ignore leftovers from branches (empty folders apart from pycache)
																		if len(list((Path(UpperCAmelCase__ ) / folder).glob("""*.py""" ) ) ) == 0:
																								continue
																		A__  :					Any											=					str((Path(UpperCAmelCase__ ) / folder).relative_to(UpperCAmelCase__ ) )
																		A__  :					Optional[int]											=					short_path.replace(os.path.sep,  """.""" )
																		submodules.append(UpperCAmelCase__ )
												for fname in files:
																		if fname == "__init__.py":
																								continue
																		A__  :					Union[str, Any]											=					str((Path(UpperCAmelCase__ ) / fname).relative_to(UpperCAmelCase__ ) )
																		A__  :					Any											=					short_path.replace(""".py""",  """""" ).replace(os.path.sep,  """.""" )
																		if len(submodule.split(""".""" ) ) == 1:
																								submodules.append(UpperCAmelCase__ )
						return submodules


A_      =							[
    '''convert_pytorch_checkpoint_to_tf2''',
    '''modeling_flax_pytorch_utils''',
]




def        _lowerCAmelCase						(							)						->Optional[int]:
						# This is to make sure the transformers module imported is the one in the repo.
						A__  :					Dict											=					importlib.util.spec_from_file_location(
						    """transformers""",  os.path.join(UpperCAmelCase__,  """__init__.py""" ),  submodule_search_locations=[PATH_TO_TRANSFORMERS],  )
						A__  :					Any											=					spec.loader.load_module()

						A__  :					Optional[Any]											=					[
						    module
						    for module in get_transformers_submodules()
						    if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
						]
						if len(UpperCAmelCase__ ) > 0:
												A__  :					Any											=					"""\n""".join(f'- {module}' for module in module_not_registered )
												raise ValueError(
												    """The following submodules are not properly registered in the main init of Transformers:\n"""
												    f'{list_of_modules}\n'
												    """Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value.""" )


if __name__ == "__main__":
						check_all_inits()
						check_submodules()














"""simple docstring"""



from sklearn.metrics import mean_squared_error

import datasets


A_      =							'''\
@article{scikit-learn,
 title={Scikit-learn: Machine Learning in {P}ython},
 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
 journal={Journal of Machine Learning Research},
 volume={12},
 pages={2825--2830},
 year={2011}
}
'''

A_      =							'''\
Mean Squared Error(MSE) is the average of the square of difference between the predicted
and actual values.
'''


A_      =							'''
Args:
    predictions: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Estimated target values.
    references: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Ground truth (correct) target values.
    sample_weight: array-like of shape (n_samples,), default=None
        Sample weights.
    multioutput: {"raw_values", "uniform_average"} or array-like of shape (n_outputs,), default="uniform_average"
        Defines aggregating of multiple output values. Array-like value defines weights used to average errors.

        "raw_values" : Returns a full set of errors in case of multioutput input.

        "uniform_average" : Errors of all outputs are averaged with uniform weight.

    squared : bool, default=True
        If True returns MSE value, if False returns RMSE (Root Mean Squared Error) value.

Returns:
    mse : mean squared error.
Examples:

    >>> mse_metric = datasets.load_metric("mse")
    >>> predictions = [2.5, 0.0, 2, 8]
    >>> references = [3, -0.5, 2, 7]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mse\': 0.375}
    >>> rmse_result = mse_metric.compute(predictions=predictions, references=references, squared=False)
    >>> print(rmse_result)
    {\'mse\': 0.6123724356957945}

    If you\'re using multi-dimensional lists, then set the config as follows :

    >>> mse_metric = datasets.load_metric("mse", "multilist")
    >>> predictions = [[0.5, 1], [-1, 1], [7, -6]]
    >>> references = [[0, 2], [-1, 2], [8, -5]]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mse\': 0.7083333333333334}
    >>> results = mse_metric.compute(predictions=predictions, references=references, multioutput=\'raw_values\')
    >>> print(results) # doctest: +NORMALIZE_WHITESPACE
    {\'mse\': array([0.41666667, 1. ])}
'''






@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION    ,						_KWARGS_DESCRIPTION						)
class 							__SCREAMING_SNAKE_CASE  (			datasets.Metric						):


							def   _UpperCamelCase    (     self :  Dict							):
													'''simple docstring'''





													return datasets.MetricInfo(
													    description=_DESCRIPTION     ,      citation=_CITATION     ,      inputs_description=_KWARGS_DESCRIPTION     ,      features=datasets.Features(self._get_feature_types()							)     ,      reference_urls=[
													        """https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html"""
													    ]     ,      )


							def   _UpperCamelCase    (     self :  Tuple							):
													'''simple docstring'''





													if self.config_name == "multilist":
																			return {
																			    "predictions": datasets.Sequence(datasets.Value("""float"""							)							),
																			    "references": datasets.Sequence(datasets.Value("""float"""							)							),
																			}
													else:
																			return {
																			    "predictions": datasets.Value("""float"""							),
																			    "references": datasets.Value("""float"""							),
																			}


							def   _UpperCamelCase    (     self :  List[str]     ,      snake_case :  Dict     ,      snake_case :  List[Any]     ,      snake_case :  List[str]=None     ,      snake_case :  List[Any]="uniform_average"     ,      snake_case :  int=True							):
													'''simple docstring'''





													A__  :					Optional[int]											=					mean_squared_error(
													    snake_case     ,      snake_case     ,      sample_weight=snake_case     ,      multioutput=snake_case     ,      squared=snake_case							)

													return {"mse": mse}






