

'''simple docstring'''







import torch

from diffusers import LMSDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest
class 					__a   (		_snake_case  ):
						__SCREAMING_SNAKE_CASE     :					Union[str, Any]  =      (LMSDiscreteScheduler,)
						__SCREAMING_SNAKE_CASE     :					Tuple  =      1_0

						def 	_UpperCAmelCase							(		self	:						Optional[int]    ,			**lowercase__	:						List[Any])						->int:

							"""simple docstring"""



							_lowercase							=     {
							    """num_train_timesteps""": 11_00,
							    """beta_start""": 0.0001,
							    """beta_end""": 0.02,
							    """beta_schedule""": """linear""",
							}

							config.update(**lowercase__)
							return config

						def 	_UpperCAmelCase							(		self	:						Tuple)						->Tuple:

							"""simple docstring"""



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

						def 	_UpperCAmelCase							(		self	:						Union[str, Any])						->Optional[Any]:

							"""simple docstring"""



							for beta_start, beta_end in zip([0.00001, 0.0001, 0.001]    ,			[0.0002, 0.002, 0.02]):
								self.check_over_configs(beta_start=lowercase__    ,			beta_end=lowercase__)

						def 	_UpperCAmelCase							(		self	:						int)						->int:

							"""simple docstring"""



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

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

							"""simple docstring"""



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

						def 	_UpperCAmelCase							(		self	:						Optional[Any])						->Union[str, Any]:

							"""simple docstring"""



							for t in [0, 5_00, 8_00]:
								self.check_over_forward(time_step=lowercase__)

						def 	_UpperCAmelCase							(		self	:						Optional[int])						->Any:

							"""simple docstring"""



							_lowercase							=     self.scheduler_classes[0]
							_lowercase							=     self.get_scheduler_config()
							_lowercase							=     scheduler_class(**lowercase__)

							scheduler.set_timesteps(self.num_inference_steps)

							_lowercase							=     self.dummy_model()
							_lowercase							=     self.dummy_sample_deter * scheduler.init_noise_sigma

							for i, t in enumerate(scheduler.timesteps):
								_lowercase							=     scheduler.scale_model_input(lowercase__    ,			lowercase__)

								_lowercase							=     model(lowercase__    ,			lowercase__)

								_lowercase							=     scheduler.step(lowercase__    ,			lowercase__    ,			lowercase__)
								_lowercase							=     output.prev_sample

							_lowercase							=     torch.sum(torch.abs(lowercase__))
							_lowercase							=     torch.mean(torch.abs(lowercase__))

							assert abs(result_sum.item() - 1006.388) < 1e-2
							assert abs(result_mean.item() - 1.31) < 1e-3

						def 	_UpperCAmelCase							(		self	:						List[str])						->List[Any]:

							"""simple docstring"""



							_lowercase							=     self.scheduler_classes[0]
							_lowercase							=     self.get_scheduler_config(prediction_type="""v_prediction""")
							_lowercase							=     scheduler_class(**lowercase__)

							scheduler.set_timesteps(self.num_inference_steps)

							_lowercase							=     self.dummy_model()
							_lowercase							=     self.dummy_sample_deter * scheduler.init_noise_sigma

							for i, t in enumerate(scheduler.timesteps):
								_lowercase							=     scheduler.scale_model_input(lowercase__    ,			lowercase__)

								_lowercase							=     model(lowercase__    ,			lowercase__)

								_lowercase							=     scheduler.step(lowercase__    ,			lowercase__    ,			lowercase__)
								_lowercase							=     output.prev_sample

							_lowercase							=     torch.sum(torch.abs(lowercase__))
							_lowercase							=     torch.mean(torch.abs(lowercase__))

							assert abs(result_sum.item() - 0.0017) < 1e-2
							assert abs(result_mean.item() - 2.2676e-06) < 1e-3

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

							"""simple docstring"""



							_lowercase							=     self.scheduler_classes[0]
							_lowercase							=     self.get_scheduler_config()
							_lowercase							=     scheduler_class(**lowercase__)

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

							_lowercase							=     self.dummy_model()
							_lowercase							=     self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
							_lowercase							=     sample.to(lowercase__)

							for i, t in enumerate(scheduler.timesteps):
								_lowercase							=     scheduler.scale_model_input(lowercase__    ,			lowercase__)

								_lowercase							=     model(lowercase__    ,			lowercase__)

								_lowercase							=     scheduler.step(lowercase__    ,			lowercase__    ,			lowercase__)
								_lowercase							=     output.prev_sample

							_lowercase							=     torch.sum(torch.abs(lowercase__))
							_lowercase							=     torch.mean(torch.abs(lowercase__))

							assert abs(result_sum.item() - 1006.388) < 1e-2
							assert abs(result_mean.item() - 1.31) < 1e-3


						def 	_UpperCAmelCase							(		self	:						Union[str, Any])						->List[str]:

							"""simple docstring"""



							_lowercase							=     self.scheduler_classes[0]
							_lowercase							=     self.get_scheduler_config()
							_lowercase							=     scheduler_class(**lowercase__    ,			use_karras_sigmas=lowercase__)

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

							_lowercase							=     self.dummy_model()
							_lowercase							=     self.dummy_sample_deter.to(lowercase__) * scheduler.init_noise_sigma
							_lowercase							=     sample.to(lowercase__)

							for t in scheduler.timesteps:
								_lowercase							=     scheduler.scale_model_input(lowercase__    ,			lowercase__)

								_lowercase							=     model(lowercase__    ,			lowercase__)

								_lowercase							=     scheduler.step(lowercase__    ,			lowercase__    ,			lowercase__)
								_lowercase							=     output.prev_sample

							_lowercase							=     torch.sum(torch.abs(lowercase__))
							_lowercase							=     torch.mean(torch.abs(lowercase__))

							assert abs(result_sum.item() - 3812.9927) < 2e-2
							assert abs(result_mean.item() - 4.9648) < 1e-3







'''simple docstring'''







import argparse
import glob
import inspect
import os
import re
import unittest

from get_test_info import get_test_classes

from tests.test_pipeline_mixin import pipeline_test_mapping


_lowerCamelCase    =  {}
for task, _ in pipeline_test_mapping.items():
							_lowerCamelCase    =  {'pt': None, 'tf': None}


# DO **NOT** add item to this set (unless the reason is approved)
_lowerCamelCase    =  {
    'tests/models/esm/test_modeling_esmfold.py',  # The pipeline test mapping is added to `test_modeling_esm.py`
}






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):

	if "ModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
		return "pt"
	elif "TFModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
		return "tf"
	elif "FlaxModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
		return "flax"
	else:
		return None






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	# Use the cached results
	if PIPELINE_TEST_MAPPING[task].get(snake_case_							,       snake_case_	) is not None:
		return PIPELINE_TEST_MAPPING[task][framework]

	_lowercase							=     pipeline_test_mapping[task]["""test"""]
	_lowercase							=     None

	if framework == "pt":
		_lowercase							=     getattr(snake_case_							,       """model_mapping"""							,       snake_case_	)
	elif framework == "tf":
		_lowercase							=     getattr(snake_case_							,       """tf_model_mapping"""							,       snake_case_	)

	if mapping is not None:
		_lowercase							=     dict(mapping.items()	)

	# cache the results
	_lowercase							=     mapping
	return mapping






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_	):
	_lowercase							=     get_framework(snake_case_	)
	if framework is None:
		return None
	_lowercase							=     get_mapping_for_task(snake_case_							,       snake_case_	)
	if mapping is None:
		return None

	_lowercase							=     list({model_class.config_class for model_class in test_class.all_model_classes}	)
	if len(snake_case_	) != 1:
		raise ValueError("""There should be exactly one configuration class from `test_class.all_model_classes`."""	)

	# This could be a list/tuple of model classes, but it's rare.
	_lowercase							=     mapping.get(config_classes[0]							,       snake_case_	)
	if isinstance(snake_case_							,       (tuple, list)	):
		_lowercase							=     sorted(snake_case_							,       key=lambda snake_case_	: x.__name__	)

	return model_class






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     [(task, get_model_for_pipeline_test(snake_case_							,       snake_case_	)) for task in pipeline_test_mapping]
	_lowercase							=     sorted([(task, model) for task, model in mapping if model is not None]							,       key=lambda snake_case_	: x[0]	)

	return dict(snake_case_	)






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     get_framework(snake_case_	)
	if framework == "pt":
		_lowercase							=     """torch"""
	_lowercase							=     """{}"""

	_lowercase							=     get_pipeline_model_mapping(snake_case_	)
	if len(snake_case_	) == 0:
		return ""

	_lowercase							=     []
	for task, model_classes in mapping.items():
		if isinstance(snake_case_							,       (tuple, list)	):
			# A list/tuple of model classes
			_lowercase							=     """(""" + """, """.join([x.__name__ for x in model_classes]	) + """)"""
		else:
			# A single model class
			_lowercase							=     model_classes.__name__
		texts.append(F"""\"{task}\": {value}"""	)
	_lowercase							=     """{""" + """, """.join(snake_case_	) + """}"""
	_lowercase							=     F"""pipeline_model_mapping = {text} if is_{framework}_available() else {default_value}"""

	return text






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     {"""ModelTesterMixin""", """TFModelTesterMixin""", """FlaxModelTesterMixin"""}
	if not issubclass(snake_case_							,       unittest.TestCase	):
		return False
	return len(base_class_names.intersection([x.__name__ for x in test_class.__bases__]	)	) > 0






def 					_SCREAMING_SNAKE_CASE		(						snake_case_	):
	_lowercase							=     [x for x in get_test_classes(snake_case_	) if is_valid_test_class(snake_case_	)]

	_lowercase							=     None
	for test_class in test_classes:
		# If a test class has defined `pipeline_model_mapping`, let's take it
		if getattr(snake_case_							,       """pipeline_model_mapping"""							,       snake_case_	) is not None:
			_lowercase							=     test_class
			break
    # Take the test class with the shortest name (just a heuristic)
	if target_test_class is None and len(snake_case_	) > 0:
		_lowercase							=     sorted(snake_case_							,       key=lambda snake_case_	: (len(x.__name__	), x.__name__)	)[0]

	return target_test_class






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_							,       snake_case_	):
	_lowercase							=     start_idx
	for idx, line in enumerate(lines[start_idx:]	):
		_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
		if idx == 0 or indent > indent_level or (indent == indent_level and line.strip() == ")"):
			_lowercase							=     start_idx + idx
		elif idx > 0 and indent <= indent_level:
			# Outside the definition block of `pipeline_model_mapping`
			break

	return end_idx






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_=False	):
	if getattr(snake_case_							,       """pipeline_model_mapping"""							,       snake_case_	) is not None:
		if not overwrite:
			return "", -1

	_lowercase							=     get_pipeline_model_mapping_string(snake_case_	)
	if len(snake_case_	) == 0:
		return "", -1
	_lowercase							=     line_to_add + """\n"""

	# The code defined the class `test_class`
	_lowercase		,		_lowercase							=     inspect.getsourcelines(snake_case_	)
	# `inspect` gives the code for an object, including decorator(s) if any.
	# We (only) need the exact line of the class definition.
	for idx, line in enumerate(snake_case_	):
		if line.lstrip().startswith("""class """	):
			_lowercase							=     class_lines[idx:]
			class_start_line_no += idx
			break
	_lowercase							=     class_start_line_no + len(snake_case_	) - 1

	# The index in `class_lines` that starts the definition of `all_model_classes`, `all_generative_model_classes` or
	# `pipeline_model_mapping`. This assumes they are defined in such order, and we take the start index of the last
	# block that appears in a `test_class`.
	_lowercase							=     None
	# The indent level of the line at `class_lines[start_idx]` (if defined)
	_lowercase							=     0
	# To record if `pipeline_model_mapping` is found in `test_class`.
	_lowercase							=     None
	for idx, line in enumerate(snake_case_	):
		if line.strip().startswith("""all_model_classes = """	):
			_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
			_lowercase							=     idx
		elif line.strip().startswith("""all_generative_model_classes = """	):
			_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
			_lowercase							=     idx
		elif line.strip().startswith("""pipeline_model_mapping = """	):
			_lowercase							=     len(snake_case_	) - len(line.lstrip()	)
			_lowercase							=     idx
			_lowercase							=     line
			break

	if start_idx is None:
		return "", -1
	# Find the ending index (inclusive) of the above found block.
	_lowercase							=     find_block_ending(snake_case_							,       snake_case_							,       snake_case_	)

	# Extract `is_xxx_available()` from existing blocks: some models require specific libraries like `timm` and use
	# `is_timm_available()` instead of `is_torch_available()`.
	# Keep leading and trailing whitespaces
	_lowercase							=     re.compile(r"""\s(is_\S+?_available\(\))\s"""	)
	for line in class_lines[start_idx : end_idx + 1]:
		_lowercase							=     r.search(snake_case_	)
		if backend_condition is not None:
			# replace the leading and trailing whitespaces to the space character " ".
			_lowercase							=     """ """ + backend_condition[0][1:-1] + """ """
			_lowercase							=     r.sub(snake_case_							,       snake_case_	)
			break

	if def_line is None:
		# `pipeline_model_mapping` is not defined. The target index is set to the ending index (inclusive) of
		# `all_model_classes` or `all_generative_model_classes`.
		_lowercase							=     end_idx
	else:
		# `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
		_lowercase							=     start_idx - 1
		# mark the lines of the currently existing `pipeline_model_mapping` to be removed.
		for idx in range(snake_case_							,       end_idx + 1	):
			# These lines are going to be removed before writing to the test file.
			_lowercase							=     None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
	_lowercase							=     [x.__name__ for x in test_class.__bases__]
	if "PipelineTesterMixin" not in parent_classes:
		# Put `PipelineTesterMixin` just before `unittest.TestCase`
		_lowercase							=     [x for x in parent_classes if x != """TestCase"""] + ["""PipelineTesterMixin"""]
		if "TestCase" in parent_classes:
			# Here we **assume** the original string is always with `unittest.TestCase`.
			_parent_classes.append("""unittest.TestCase"""	)
		_lowercase							=     """, """.join(_parent_classes	)
		for idx, line in enumerate(snake_case_	):
			# Find the ending of the declaration of `test_class`
			if line.strip().endswith("""):"""	):
				# mark the lines of the declaration of `test_class` to be removed
				for _idx in range(idx + 1	):
					_lowercase							=     None  # noqa
				break
        # Add the new, one-line, class declaration for `test_class`
		_lowercase							=     F"""class {test_class.__name__}({parent_classes}):\n"""

	# Add indentation
	_lowercase							=     """ """ * indent_level + line_to_add
	# Insert `pipeline_model_mapping` to `class_lines`.
	# (The line at `target_idx` should be kept by definition!)
	_lowercase							=     class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
	# Remove the lines that are marked to be removed
	_lowercase							=     [x for x in class_lines if x is not None]

	# Move from test class to module (in order to write to the test file)
	_lowercase							=     inspect.getsourcelines(inspect.getmodule(snake_case_	)	)[0]
	# Be careful with the 1-off between line numbers and array indices
	_lowercase							=     module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
	_lowercase							=     """""".join(snake_case_	)

	_lowercase							=     inspect.getsourcefile(snake_case_	)
	with open(snake_case_							,       """w"""							,       encoding="""UTF-8"""							,       newline="""\n"""	) as fp:
		fp.write(snake_case_	)

	return line_to_add






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_=False	):
	_lowercase							=     find_test_class(snake_case_	)
	if test_class:
		add_pipeline_model_mapping(snake_case_							,       overwrite=snake_case_	)


if __name__ == "__main__":
							_lowerCamelCase    =  argparse.ArgumentParser()
							parser.add_argument(
							    '--test_file', type=str, help='A path to the test file, starting with the repository\'s `tests` directory.'
							)
							parser.add_argument(
							    '--all',
							    action='store_true',
							    help='If to check and modify all test files.',
							)
							parser.add_argument(
							    '--overwrite',
							    action='store_true',
							    help='If to overwrite a test class if it has already defined `pipeline_model_mapping`.',
							)
							_lowerCamelCase    =  parser.parse_args()

							if not args.all and not args.test_file:
														raise ValueError('Please specify either `test_file` or pass `--all` to check/modify all test files.')
							elif args.all and args.test_file:
														raise ValueError('Only one of `--test_file` and `--all` could be specified.')

							_lowerCamelCase    =  []
							if args.test_file:
														_lowerCamelCase    =  [args.test_file]
							else:
														_lowerCamelCase    =  os.path.join('tests', 'models', '**', 'test_modeling_*.py')
														for test_file in glob.glob(pattern):
																					# `Flax` is not concerned at this moment
																					if not test_file.startswith('test_modeling_flax_'):
																												test_files.append(test_file)

							for test_file in test_files:
														if test_file in TEST_FILE_TO_IGNORE:
																					print(F"""[SKIPPED] {test_file} is skipped as it is in `TEST_FILE_TO_IGNORE` in the file {__file__}.""")
																					continue
														add_pipeline_model_mapping_to_test_file(test_file, overwrite=args.overwrite)




