




"""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       UpperCAmelCase__ (snake_case__							:      Dict					):
		"""simple docstring"""

		if _re_test_backend.search(_snake_case					) is None:
				return None
		_snake_case							:	Union[str, Any]			=						[b[0] for b in _re_backend.findall(_snake_case					)]
		backends.sort()
		return "_and_".join(_snake_case					)


def       UpperCAmelCase__ (snake_case__							:      Optional[Any]					):
		"""simple docstring"""

		with open(_snake_case	,     """r"""	,     encoding="""utf-8"""	,     newline="""\n"""					) as f:
				_snake_case							:	Optional[int]			=						f.readlines()

		_snake_case							:	Optional[Any]			=						0
		while line_index < len(_snake_case					) and not lines[line_index].startswith("""_import_structure = {"""					):
				line_index += 1

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

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

		_snake_case							:	List[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.
				_snake_case							:	Union[str, Any]			=						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:
						_snake_case							:	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

						_snake_case							:	Any			=						[]
						# Until we unindent, add backend objects to the list
						while len(lines[line_index]					) <= 1 or lines[line_index].startswith(""" """ * 4					):
								_snake_case							:	str			=						lines[line_index]
								if _re_import_struct_add_one.search(_snake_case					) is not None:
										objects.append(_re_import_struct_add_one.search(_snake_case					).groups()[0]					)
								elif _re_import_struct_add_many.search(_snake_case					) is not None:
										_snake_case							:	int			=						_re_import_struct_add_many.search(_snake_case					).groups()[0].split(""", """					)
										_snake_case							:	Optional[int]			=						[obj[1:-1] for obj in imports if len(_snake_case					) > 0]
										objects.extend(_snake_case					)
								elif _re_between_brackets.search(_snake_case					) is not None:
										_snake_case							:	List[Any]			=						_re_between_brackets.search(_snake_case					).groups()[0].split(""", """					)
										_snake_case							:	List[Any]			=						[obj[1:-1] for obj in imports if len(_snake_case					) > 0]
										objects.extend(_snake_case					)
								elif _re_quote_object.search(_snake_case					) is not None:
										objects.append(_re_quote_object.search(_snake_case					).groups()[0]					)
								elif line.startswith(""" """ * 8 + """\""""					):
										objects.append(line[9:-3]					)
								elif line.startswith(""" """ * 12 + """\""""					):
										objects.append(line[13:-3]					)
								line_index += 1

						_snake_case							:	Optional[Any]			=						objects
				else:
						line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
		_snake_case							:	Optional[int]			=						[]
		while (
		    line_index < len(_snake_case					)
		    and find_backend(lines[line_index]					) is None
		    and not lines[line_index].startswith("""else"""					)
		):
				_snake_case							:	List[Any]			=						lines[line_index]
				_snake_case							:	int			=						_re_import.search(_snake_case					)
				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

		_snake_case							:	Any			=						{"""none""": objects}
		# Let's continue with backend-specific objects
		while line_index < len(_snake_case					):
				# If the line is an if is_backend_available, we grab all objects associated.
				_snake_case							:	Optional[int]			=						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:
						_snake_case							:	Union[str, 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

						_snake_case							:	Union[str, Any]			=						[]
						# Until we unindent, add backend objects to the list
						while len(lines[line_index]					) <= 1 or lines[line_index].startswith(""" """ * 8					):
								_snake_case							:	int			=						lines[line_index]
								_snake_case							:	Any			=						_re_import.search(_snake_case					)
								if single_line_import_search is not None:
										objects.extend(single_line_import_search.groups()[0].split(""", """					)					)
								elif line.startswith(""" """ * 12					):
										objects.append(line[12:-2]					)
								line_index += 1

						_snake_case							:	Optional[Any]			=						objects
				else:
						line_index += 1

		return import_dict_objects, type_hint_objects


def       UpperCAmelCase__ (snake_case__							:      Tuple	,     snake_case__							:      Optional[Any]					):
		"""simple docstring"""

		def find_duplicates(snake_case__							:      Optional[Any]					):
				return [k for k, v in collections.Counter(_snake_case					).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!"]

		_snake_case							:	List[Any]			=						[]
		for key in import_dict_objects.keys():
				_snake_case							:	int			=						find_duplicates(import_dict_objects[key]					)
				if duplicate_imports:
						errors.append(F"Duplicate _import_structure definitions for: {duplicate_imports}"					)
				_snake_case							:	Tuple			=						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]					)					):
						_snake_case							:	Dict			=						"""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       UpperCAmelCase__ ():
		"""simple docstring"""

		_snake_case							:	str			=						[]
		for root, _, files in os.walk(_snake_case					):
				if "__init__.py" in files:
						_snake_case							:	List[str]			=						os.path.join(_snake_case	,     """__init__.py"""					)
						_snake_case							:	Tuple			=						parse_init(_snake_case					)
						if objects is not None:
								_snake_case							:	str			=						analyze_results(*_snake_case					)
								if len(_snake_case					) > 0:
										_snake_case							:	int			=						F"Problem in {fname}, both halves do not define the same objects.\n{errors[0]}"
										failures.append("""\n""".join(_snake_case					)					)
		if len(_snake_case					) > 0:
				raise ValueError("""\n\n""".join(_snake_case					)					)


def       UpperCAmelCase__ ():
		"""simple docstring"""

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


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


def       UpperCAmelCase__ ():
		"""simple docstring"""

		_snake_case							:	Tuple			=						importlib.util.spec_from_file_location(
		    """transformers"""	,     os.path.join(_snake_case	,     """__init__.py"""					)	,     submodule_search_locations=[PATH_TO_TRANSFORMERS]	,     )
		_snake_case							:	Tuple			=						spec.loader.load_module()

		_snake_case							:	List[str]			=						[
		    module
		    for module in get_transformers_submodules()
		    if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
		]
		if len(_snake_case					) > 0:
				_snake_case							:	Tuple			=						"""\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"""


import tempfile

import torch

from diffusers import IPNDMScheduler

from .test_schedulers import SchedulerCommonTest






class       lowercase(  __a				):







 '''simple docstring'''





 lowercase__				      =      (IPNDMScheduler,)
 lowercase__				      =      (("num_inference_steps", 50),)


 def 				UpperCamelCase_     (       self:	Union[str, Any],   **a_:	Union[str, Any]	):




   '''simple docstring'''



   _snake_case							:	List[Any]			=						{"""num_train_timesteps""": 1_000}
   config.update(**a_	)
   return config


 def 				UpperCamelCase_     (       self:	Tuple,   a_:	Optional[int]=0,   **a_:	int	):




   '''simple docstring'''



   _snake_case							:	Optional[int]			=						dict(self.forward_default_kwargs	)
   _snake_case							:	Optional[Any]			=						kwargs.pop("""num_inference_steps""",   a_	)
   _snake_case							:	Optional[Any]			=						self.dummy_sample
   _snake_case							:	Dict			=						0.1 * sample
   _snake_case							:	Any			=						[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]

   for scheduler_class in self.scheduler_classes:
     _snake_case							:	int			=						self.get_scheduler_config(**a_	)
     _snake_case							:	Dict			=						scheduler_class(**a_	)
     scheduler.set_timesteps(a_	)
     # copy over dummy past residuals
     _snake_case							:	int			=						dummy_past_residuals[:]

     if time_step is None:
       _snake_case							:	Union[str, Any]			=						scheduler.timesteps[len(scheduler.timesteps	) // 2]

     with tempfile.TemporaryDirectory() as tmpdirname:
       scheduler.save_config(a_	)
       _snake_case							:	Tuple			=						scheduler_class.from_pretrained(a_	)
       new_scheduler.set_timesteps(a_	)
       # copy over dummy past residuals
       _snake_case							:	Optional[Any]			=						dummy_past_residuals[:]

     _snake_case							:	List[Any]			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample
     _snake_case							:	str			=						new_scheduler.step(a_,   a_,   a_,   **a_	).prev_sample

     assert torch.sum(torch.abs(output - new_output	)	) < 1E-5, "Scheduler outputs are not identical"

     _snake_case							:	Optional[Any]			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample
     _snake_case							:	Optional[int]			=						new_scheduler.step(a_,   a_,   a_,   **a_	).prev_sample

     assert torch.sum(torch.abs(output - new_output	)	) < 1E-5, "Scheduler outputs are not identical"


 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   pass


 def 				UpperCamelCase_     (       self:	str,   a_:	Any=0,   **a_:	Tuple	):




   '''simple docstring'''



   _snake_case							:	str			=						dict(self.forward_default_kwargs	)
   _snake_case							:	List[Any]			=						kwargs.pop("""num_inference_steps""",   a_	)
   _snake_case							:	Optional[int]			=						self.dummy_sample
   _snake_case							:	Tuple			=						0.1 * sample
   _snake_case							:	Optional[int]			=						[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]

   for scheduler_class in self.scheduler_classes:
     _snake_case							:	Any			=						self.get_scheduler_config()
     _snake_case							:	Tuple			=						scheduler_class(**a_	)
     scheduler.set_timesteps(a_	)

     # copy over dummy past residuals (must be after setting timesteps)
     _snake_case							:	Union[str, Any]			=						dummy_past_residuals[:]

     if time_step is None:
       _snake_case							:	Tuple			=						scheduler.timesteps[len(scheduler.timesteps	) // 2]

     with tempfile.TemporaryDirectory() as tmpdirname:
       scheduler.save_config(a_	)
       _snake_case							:	List[str]			=						scheduler_class.from_pretrained(a_	)
       # copy over dummy past residuals
       new_scheduler.set_timesteps(a_	)

       # copy over dummy past residual (must be after setting timesteps)
       _snake_case							:	List[str]			=						dummy_past_residuals[:]

     _snake_case							:	str			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample
     _snake_case							:	Any			=						new_scheduler.step(a_,   a_,   a_,   **a_	).prev_sample

     assert torch.sum(torch.abs(output - new_output	)	) < 1E-5, "Scheduler outputs are not identical"

     _snake_case							:	str			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample
     _snake_case							:	int			=						new_scheduler.step(a_,   a_,   a_,   **a_	).prev_sample

     assert torch.sum(torch.abs(output - new_output	)	) < 1E-5, "Scheduler outputs are not identical"


 def 				UpperCamelCase_     (       self:	List[Any],   **a_:	Optional[int]	):




   '''simple docstring'''



   _snake_case							:	Union[str, Any]			=						self.scheduler_classes[0]
   _snake_case							:	Any			=						self.get_scheduler_config(**a_	)
   _snake_case							:	List[Any]			=						scheduler_class(**a_	)

   _snake_case							:	Union[str, Any]			=						10
   _snake_case							:	Union[str, Any]			=						self.dummy_model()
   _snake_case							:	List[Any]			=						self.dummy_sample_deter
   scheduler.set_timesteps(a_	)

   for i, t in enumerate(scheduler.timesteps	):
     _snake_case							:	Optional[Any]			=						model(a_,   a_	)
     _snake_case							:	Any			=						scheduler.step(a_,   a_,   a_	).prev_sample

   for i, t in enumerate(scheduler.timesteps	):
     _snake_case							:	Union[str, Any]			=						model(a_,   a_	)
     _snake_case							:	Any			=						scheduler.step(a_,   a_,   a_	).prev_sample

   return sample


 def 				UpperCamelCase_     (       self:	Any	):




   '''simple docstring'''



   _snake_case							:	str			=						dict(self.forward_default_kwargs	)

   _snake_case							:	int			=						kwargs.pop("""num_inference_steps""",   a_	)

   for scheduler_class in self.scheduler_classes:
     _snake_case							:	Union[str, Any]			=						self.get_scheduler_config()
     _snake_case							:	Tuple			=						scheduler_class(**a_	)

     _snake_case							:	Dict			=						self.dummy_sample
     _snake_case							:	List[str]			=						0.1 * sample

     if num_inference_steps is not None and hasattr(a_,   """set_timesteps"""	):
       scheduler.set_timesteps(a_	)
     elif num_inference_steps is not None and not hasattr(a_,   """set_timesteps"""	):
       _snake_case							:	Dict			=						num_inference_steps

     # copy over dummy past residuals (must be done after set_timesteps)
     _snake_case							:	Union[str, Any]			=						[residual + 0.2, residual + 0.15, residual + 0.1, residual + 0.05]
     _snake_case							:	List[str]			=						dummy_past_residuals[:]

     _snake_case							:	Optional[int]			=						scheduler.timesteps[5]
     _snake_case							:	Optional[Any]			=						scheduler.timesteps[6]

     _snake_case							:	str			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample
     _snake_case							:	List[str]			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample

     self.assertEqual(output_a.shape,   sample.shape	)
     self.assertEqual(output_a.shape,   output_a.shape	)

     _snake_case							:	Any			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample
     _snake_case							:	Any			=						scheduler.step(a_,   a_,   a_,   **a_	).prev_sample

     self.assertEqual(output_a.shape,   sample.shape	)
     self.assertEqual(output_a.shape,   output_a.shape	)


 def 				UpperCamelCase_     (       self:	Optional[Any]	):




   '''simple docstring'''



   for timesteps in [100, 1_000]:
     self.check_over_configs(num_train_timesteps=a_,   time_step=a_	)


 def 				UpperCamelCase_     (       self:	Any	):




   '''simple docstring'''



   for t, num_inference_steps in zip([1, 5, 10],   [10, 50, 100]	):
     self.check_over_forward(num_inference_steps=a_,   time_step=a_	)


 def 				UpperCamelCase_     (       self:	Optional[Any]	):




   '''simple docstring'''



   _snake_case							:	Optional[int]			=						self.full_loop()
   _snake_case							:	Optional[int]			=						torch.mean(torch.abs(a_	)	)

   assert abs(result_mean.item() - 2_540_529	) < 10


