

'''simple docstring'''
import argparse
import os
import re


_lowerCamelCase      					=     """src/diffusers"""

# Pattern that looks at the indentation in a line.
_lowerCamelCase      					=     re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCamelCase      					=     re.compile(R"""^\s*\"([^\"]+)\":""")
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
_lowerCamelCase      					=     re.compile(R"""^\s*_import_structure\[\"([^\"]+)\"\]""")
# Pattern that matches `"key",` and puts `key` in group 0.
_lowerCamelCase      					=     re.compile(R"""^\s*\"([^\"]+)\",\s*$""")
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
_lowerCamelCase      					=     re.compile(R"""\[([^\]]+)\]""")


def  a__       (    _SCREAMING_SNAKE_CASE   :       Tuple				)     ->					List[Any]:


	"""simple docstring"""





	UpperCAmelCase_     :      int						=  _re_indent.search(_SCREAMING_SNAKE_CASE				)
	return "" if search is None else search.groups()[0]


def  a__       (    _SCREAMING_SNAKE_CASE   :       Tuple	,				_SCREAMING_SNAKE_CASE   :       List[str]=""	,				_SCREAMING_SNAKE_CASE   :       Optional[Any]=None	,				_SCREAMING_SNAKE_CASE   :       Tuple=None				)     ->					Dict:


	"""simple docstring"""





	UpperCAmelCase_     :      str						=  0
	UpperCAmelCase_     :      List[Any]						=  code.split("\n"				)
	if start_prompt is not None:
		while not lines[index].startswith(_SCREAMING_SNAKE_CASE				):
			index += 1
		UpperCAmelCase_     :      Optional[Any]						=  ["\n".join(lines[:index]				)]
	else:
		UpperCAmelCase_     :      Optional[int]						=  []

	# We split into blocks until we get to the `end_prompt` (or the end of the block).
	UpperCAmelCase_     :      Tuple						=  [lines[index]]
	index += 1
	while index < len(_SCREAMING_SNAKE_CASE				) and (end_prompt is None or not lines[index].startswith(_SCREAMING_SNAKE_CASE				)):
		if len(lines[index]				) > 0 and get_indent(lines[index]				) == indent_level:
			if len(_SCREAMING_SNAKE_CASE				) > 0 and get_indent(current_block[-1]				).startswith(indent_level + " "				):
				current_block.append(lines[index]				)
				blocks.append("\n".join(_SCREAMING_SNAKE_CASE				)				)
				if index < len(_SCREAMING_SNAKE_CASE				) - 1:
					UpperCAmelCase_     :      int						=  [lines[index + 1]]
					index += 1
				else:
					UpperCAmelCase_     :      Any						=  []
			else:
				blocks.append("\n".join(_SCREAMING_SNAKE_CASE				)				)
				UpperCAmelCase_     :      str						=  [lines[index]]
		else:
			current_block.append(lines[index]				)
		index += 1

	# Adds current block if it's nonempty.
	if len(_SCREAMING_SNAKE_CASE				) > 0:
		blocks.append("\n".join(_SCREAMING_SNAKE_CASE				)				)

	# Add final block after end_prompt if provided.
	if end_prompt is not None and index < len(_SCREAMING_SNAKE_CASE				):
		blocks.append("\n".join(lines[index:]				)				)

	return blocks


def  a__       (    _SCREAMING_SNAKE_CASE   :       int				)     ->					int:


	"""simple docstring"""





	def _inner(_SCREAMING_SNAKE_CASE   :       List[Any]				):
		return key(_SCREAMING_SNAKE_CASE				).lower().replace("_"	,				""				)

	return _inner


def  a__       (    _SCREAMING_SNAKE_CASE   :       List[Any]	,				_SCREAMING_SNAKE_CASE   :       List[Any]=None				)     ->					Optional[Any]:


	"""simple docstring"""





	def noop(_SCREAMING_SNAKE_CASE   :       str				):
		return x

	if key is None:
		UpperCAmelCase_     :      Optional[Any]						=  noop
	# Constants are all uppercase, they go first.
	UpperCAmelCase_     :      str						=  [obj for obj in objects if key(_SCREAMING_SNAKE_CASE				).isupper()]
	# Classes are not all uppercase but start with a capital, they go second.
	UpperCAmelCase_     :      List[Any]						=  [obj for obj in objects if key(_SCREAMING_SNAKE_CASE				)[0].isupper() and not key(_SCREAMING_SNAKE_CASE				).isupper()]
	# Functions begin with a lowercase, they go last.
	UpperCAmelCase_     :      Any						=  [obj for obj in objects if not key(_SCREAMING_SNAKE_CASE				)[0].isupper()]

	UpperCAmelCase_     :      Tuple						=  ignore_underscore(_SCREAMING_SNAKE_CASE				)
	return sorted(_SCREAMING_SNAKE_CASE	,				key=_SCREAMING_SNAKE_CASE				) + sorted(_SCREAMING_SNAKE_CASE	,				key=_SCREAMING_SNAKE_CASE				) + sorted(_SCREAMING_SNAKE_CASE	,				key=_SCREAMING_SNAKE_CASE				)


def  a__       (    _SCREAMING_SNAKE_CASE   :       int				)     ->					str:


	"""simple docstring"""





	def _replace(_SCREAMING_SNAKE_CASE   :       int				):
		UpperCAmelCase_     :      Dict						=  match.groups()[0]
		if "," not in imports:
			return F'''[{imports}]'''
		UpperCAmelCase_     :      Union[str, Any]						=  [part.strip().replace("\""	,				""				) for part in imports.split(","				)]
		# We will have a final empty element if the line finished with a comma.
		if len(keys[-1]				) == 0:
			UpperCAmelCase_     :      Dict						=  keys[:-1]
		return "[" + ", ".join([F'''"{k}"''' for k in sort_objects(_SCREAMING_SNAKE_CASE				)]				) + "]"

	UpperCAmelCase_     :      str						=  import_statement.split("\n"				)
	if len(_SCREAMING_SNAKE_CASE				) > 3:
		# Here we have to sort internal imports that are on several lines (one per name):
		# key: [
		#     "object1",
		#     "object2",
		#     ...
		# ]

		# We may have to ignore one or two lines on each side.
		UpperCAmelCase_     :      Tuple						=  2 if lines[1].strip() == "[" else 1
		UpperCAmelCase_     :      Optional[int]						=  [(i, _re_strip_line.search(_SCREAMING_SNAKE_CASE				).groups()[0]) for i, line in enumerate(lines[idx:-idx]				)]
		UpperCAmelCase_     :      str						=  sort_objects(_SCREAMING_SNAKE_CASE	,				key=lambda _SCREAMING_SNAKE_CASE				: x[1]				)
		UpperCAmelCase_     :      Optional[int]						=  [lines[x[0] + idx] for x in sorted_indices]
		return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]				)
	elif len(_SCREAMING_SNAKE_CASE				) == 3:
		# Here we have to sort internal imports that are on one separate line:
		# key: [
		#     "object1", "object2", ...
		# ]
		if _re_bracket_content.search(lines[1]				) is not None:
			UpperCAmelCase_     :      Optional[Any]						=  _re_bracket_content.sub(_replace	,				lines[1]				)
		else:
			UpperCAmelCase_     :      Tuple						=  [part.strip().replace("\""	,				""				) for part in lines[1].split(","				)]
			# We will have a final empty element if the line finished with a comma.
			if len(keys[-1]				) == 0:
				UpperCAmelCase_     :      Union[str, Any]						=  keys[:-1]
			UpperCAmelCase_     :      Union[str, Any]						=  get_indent(lines[1]				) + ", ".join([F'''"{k}"''' for k in sort_objects(_SCREAMING_SNAKE_CASE				)]				)
		return "\n".join(_SCREAMING_SNAKE_CASE				)
	else:
		# Finally we have to deal with imports fitting on one line
		UpperCAmelCase_     :      int						=  _re_bracket_content.sub(_replace	,				_SCREAMING_SNAKE_CASE				)
		return import_statement


def  a__       (    _SCREAMING_SNAKE_CASE   :       Tuple	,				_SCREAMING_SNAKE_CASE   :       List[Any]=True				)     ->					List[str]:


	"""simple docstring"""





	with open(_SCREAMING_SNAKE_CASE	,				"r"				) as f:
		UpperCAmelCase_     :      Union[str, Any]						=  f.read()

	if "_import_structure" not in code:
		return

	# Blocks of indent level 0
	UpperCAmelCase_     :      Any						=  split_code_in_indented_blocks(
	    _SCREAMING_SNAKE_CASE	,				start_prompt="_import_structure = {"	,				end_prompt="if TYPE_CHECKING:"				)

	# We ignore block 0 (everything until start_prompt) and the last block (everything after end_prompt).
	for block_idx in range(1	,				len(_SCREAMING_SNAKE_CASE				) - 1				):
		# Check if the block contains some `_import_structure`s thingy to sort.
		UpperCAmelCase_     :      Optional[Any]						=  main_blocks[block_idx]
		UpperCAmelCase_     :      List[Any]						=  block.split("\n"				)

		# Get to the start of the imports.
		UpperCAmelCase_     :      List[Any]						=  0
		while line_idx < len(_SCREAMING_SNAKE_CASE				) and "_import_structure" not in block_lines[line_idx]:
			# Skip dummy import blocks
			if "import dummy" in block_lines[line_idx]:
				UpperCAmelCase_     :      List[str]						=  len(_SCREAMING_SNAKE_CASE				)
			else:
				line_idx += 1
		if line_idx >= len(_SCREAMING_SNAKE_CASE				):
			continue

		# Ignore beginning and last line: they don't contain anything.
		UpperCAmelCase_     :      Union[str, Any]						=  "\n".join(block_lines[line_idx:-1]				)
		UpperCAmelCase_     :      Optional[Any]						=  get_indent(block_lines[1]				)
		# Slit the internal block into blocks of indent level 1.
		UpperCAmelCase_     :      Tuple						=  split_code_in_indented_blocks(_SCREAMING_SNAKE_CASE	,				indent_level=_SCREAMING_SNAKE_CASE				)
		# We have two categories of import key: list or _import_structure[key].append/extend
		UpperCAmelCase_     :      Optional[int]						=  _re_direct_key if "_import_structure" in block_lines[0] else _re_indirect_key
		# Grab the keys, but there is a trap: some lines are empty or just comments.
		UpperCAmelCase_     :      int						=  [(pattern.search(_SCREAMING_SNAKE_CASE				).groups()[0] if pattern.search(_SCREAMING_SNAKE_CASE				) is not None else None) for b in internal_blocks]
		# We only sort the lines with a key.
		UpperCAmelCase_     :      Optional[int]						=  [(i, key) for i, key in enumerate(_SCREAMING_SNAKE_CASE				) if key is not None]
		UpperCAmelCase_     :      str						=  [x[0] for x in sorted(_SCREAMING_SNAKE_CASE	,				key=lambda _SCREAMING_SNAKE_CASE				: x[1]				)]

		# We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
		UpperCAmelCase_     :      Tuple						=  0
		UpperCAmelCase_     :      Any						=  []
		for i in range(len(_SCREAMING_SNAKE_CASE				)				):
			if keys[i] is None:
				reordered_blocks.append(internal_blocks[i]				)
			else:
				UpperCAmelCase_     :      Union[str, Any]						=  sort_objects_in_import(internal_blocks[sorted_indices[count]]				)
				reordered_blocks.append(_SCREAMING_SNAKE_CASE				)
				count += 1

        # And we put our main block back together with its first and last line.
		UpperCAmelCase_     :      Dict						=  "\n".join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]				)

	if code != "\n".join(_SCREAMING_SNAKE_CASE				):
		if check_only:
			return True
		else:
			print(F'''Overwriting {file}.'''				)
			with open(_SCREAMING_SNAKE_CASE	,				"w"				) as f:
				f.write("\n".join(_SCREAMING_SNAKE_CASE				)				)


def  a__       (    _SCREAMING_SNAKE_CASE   :       Union[str, Any]=True				)     ->					Dict:


	"""simple docstring"""





	UpperCAmelCase_     :      Tuple						=  []
	for root, _, files in os.walk(_SCREAMING_SNAKE_CASE				):
		if "__init__.py" in files:
			UpperCAmelCase_     :      str						=  sort_imports(os.path.join(_SCREAMING_SNAKE_CASE	,				"__init__.py"				)	,				check_only=_SCREAMING_SNAKE_CASE				)
			if result:
				UpperCAmelCase_     :      List[Any]						=  [os.path.join(_SCREAMING_SNAKE_CASE	,				"__init__.py"				)]
	if len(_SCREAMING_SNAKE_CASE				) > 0:
		raise ValueError(F'''Would overwrite {len(_SCREAMING_SNAKE_CASE				)} files, run `make style`.'''				)


if __name__ == "__main__":
					_lowerCamelCase      					=     argparse.ArgumentParser()
					parser.add_argument("""--check_only""", action="""store_true""", help="""Whether to only check or fix style.""")
					_lowerCamelCase      					=     parser.parse_args()

					sort_imports_in_all_inits(check_only=args.check_only)










import torch

from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest



class    lowercase_		(SCREAMING_SNAKE_CASE__ ):
						lowerCAmelCase__			      =(KDPMaDiscreteScheduler,)
						lowerCAmelCase__			      =10



						def 	__a					(			self	:   Dict					,							**snake_case__	:   str  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							{
								    'num_train_timesteps': 11_00,
								    'beta_start': 0.00_01,
								    'beta_end': 0.02,
								    'beta_schedule': 'linear',
								}

								config.update(**snake_case__  )
								return config



						def 	__a					(			self	:   str  ):

								"""simple docstring"""

								for timesteps in [10, 50, 1_00, 10_00]:
										self.check_over_configs(num_train_timesteps=snake_case__  )



						def 	__a					(			self	:   List[Any]  ):

								"""simple docstring"""

								for beta_start, beta_end in zip([0.0_00_01, 0.00_01, 0.0_01]					,							[0.00_02, 0.0_02, 0.02]  ):
										self.check_over_configs(beta_start=snake_case__					,							beta_end=snake_case__  )



						def 	__a					(			self	:   Optional[int]  ):

								"""simple docstring"""

								for schedule in ["linear", "scaled_linear"]:
										self.check_over_configs(beta_schedule=snake_case__  )



						def 	__a					(			self	:   Optional[Any]  ):

								"""simple docstring"""

								for prediction_type in ["epsilon", "v_prediction"]:
										self.check_over_configs(prediction_type=snake_case__  )



						def 	__a					(			self	:   Optional[Any]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.scheduler_classes[0]
								SCREAMING_SNAKE_CASE_					      =							self.get_scheduler_config(prediction_type='v_prediction'  )
								SCREAMING_SNAKE_CASE_					      =							scheduler_class(**snake_case__  )

								scheduler.set_timesteps(self.num_inference_steps  )

								SCREAMING_SNAKE_CASE_					      =							self.dummy_model()
								SCREAMING_SNAKE_CASE_					      =							self.dummy_sample_deter * scheduler.init_noise_sigma
								SCREAMING_SNAKE_CASE_					      =							sample.to(snake_case__  )

								for i, t in enumerate(scheduler.timesteps  ):
										SCREAMING_SNAKE_CASE_					      =							scheduler.scale_model_input(snake_case__					,							snake_case__  )

										SCREAMING_SNAKE_CASE_					      =							model(snake_case__					,							snake_case__  )

										SCREAMING_SNAKE_CASE_					      =							scheduler.step(snake_case__					,							snake_case__					,							snake_case__  )
										SCREAMING_SNAKE_CASE_					      =							output.prev_sample

								SCREAMING_SNAKE_CASE_					      =							torch.sum(torch.abs(snake_case__  )  )
								SCREAMING_SNAKE_CASE_					      =							torch.mean(torch.abs(snake_case__  )  )

								if torch_device in ["cpu", "mps"]:
										assert abs(result_sum.item() - 4.69_34e-07  ) < 1e-2
										assert abs(result_mean.item() - 6.11_12e-10  ) < 1e-3
								else:
										# CUDA
										assert abs(result_sum.item() - 4.6_93_42_86_50_17_09_72e-07  ) < 1e-2
										assert abs(result_mean.item() - 0.00_02  ) < 1e-3



						def 	__a					(			self	:   Union[str, Any]  ):

								"""simple docstring"""

								if torch_device == "mps":
										return
								SCREAMING_SNAKE_CASE_					      =							self.scheduler_classes[0]
								SCREAMING_SNAKE_CASE_					      =							self.get_scheduler_config()
								SCREAMING_SNAKE_CASE_					      =							scheduler_class(**snake_case__  )

								scheduler.set_timesteps(self.num_inference_steps  )

								SCREAMING_SNAKE_CASE_					      =							self.dummy_model()
								SCREAMING_SNAKE_CASE_					      =							self.dummy_sample_deter * scheduler.init_noise_sigma
								SCREAMING_SNAKE_CASE_					      =							sample.to(snake_case__  )

								for i, t in enumerate(scheduler.timesteps  ):
										SCREAMING_SNAKE_CASE_					      =							scheduler.scale_model_input(snake_case__					,							snake_case__  )

										SCREAMING_SNAKE_CASE_					      =							model(snake_case__					,							snake_case__  )

										SCREAMING_SNAKE_CASE_					      =							scheduler.step(snake_case__					,							snake_case__					,							snake_case__  )
										SCREAMING_SNAKE_CASE_					      =							output.prev_sample

								SCREAMING_SNAKE_CASE_					      =							torch.sum(torch.abs(snake_case__  )  )
								SCREAMING_SNAKE_CASE_					      =							torch.mean(torch.abs(snake_case__  )  )

								if torch_device in ["cpu", "mps"]:
										assert abs(result_sum.item() - 20.41_25  ) < 1e-2
										assert abs(result_mean.item() - 0.02_66  ) < 1e-3
								else:
										# CUDA
										assert abs(result_sum.item() - 20.41_25  ) < 1e-2
										assert abs(result_mean.item() - 0.02_66  ) < 1e-3






						def 	__a					(			self	:   Optional[int]  ):

								"""simple docstring"""

								if torch_device == "mps":
										return
								SCREAMING_SNAKE_CASE_					      =							self.scheduler_classes[0]
								SCREAMING_SNAKE_CASE_					      =							self.get_scheduler_config()
								SCREAMING_SNAKE_CASE_					      =							scheduler_class(**snake_case__  )

								scheduler.set_timesteps(self.num_inference_steps					,							device=snake_case__  )

								SCREAMING_SNAKE_CASE_					      =							self.dummy_model()
								SCREAMING_SNAKE_CASE_					      =							self.dummy_sample_deter.to(snake_case__  ) * scheduler.init_noise_sigma

								for t in scheduler.timesteps:
										SCREAMING_SNAKE_CASE_					      =							scheduler.scale_model_input(snake_case__					,							snake_case__  )

										SCREAMING_SNAKE_CASE_					      =							model(snake_case__					,							snake_case__  )

										SCREAMING_SNAKE_CASE_					      =							scheduler.step(snake_case__					,							snake_case__					,							snake_case__  )
										SCREAMING_SNAKE_CASE_					      =							output.prev_sample

								SCREAMING_SNAKE_CASE_					      =							torch.sum(torch.abs(snake_case__  )  )
								SCREAMING_SNAKE_CASE_					      =							torch.mean(torch.abs(snake_case__  )  )

								if str(snake_case__  ).startswith('cpu'  ):
										# The following sum varies between 148 and 156 on mps. Why?
										assert abs(result_sum.item() - 20.41_25  ) < 1e-2
										assert abs(result_mean.item() - 0.02_66  ) < 1e-3
								else:
										# CUDA
										assert abs(result_sum.item() - 20.41_25  ) < 1e-2
										assert abs(result_mean.item() - 0.02_66  ) < 1e-3