




import os
import re
import shutil
import sys
import tempfile
import unittest

import black


__lowerCAmelCase	:       Tuple     =	os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
__lowerCAmelCase	:       List[str]     =	'    \"""\n    Output class for the scheduler\'s step function output.\n\n    Args:\n        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the\n            denoising loop.\n        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):\n            The predicted denoised sample (x_{0}) based on the model output from the current timestep.\n            `pred_original_sample` can be used to preview progress or for guidance.\n    \"""\n\n    prev_sample: torch.FloatTensor\n    pred_original_sample: Optional[torch.FloatTensor] = None\n'




class 					snake_case__							(unittest.TestCase     ):
				"""simple docstring"""



				def 							__UpperCAmelCase							(   self       :  Dict							)      ->  Union[str, Any]:
							a					=    tempfile.mkdtemp()
							os.makedirs(os.path.join(self.diffusers_dir      ,   "schedulers/"							)							)
							a					=    self.diffusers_dir
							shutil.copy(
							    os.path.join(__lowerCamelCase      ,   "src/diffusers/schedulers/scheduling_ddpm.py"							)      ,   os.path.join(self.diffusers_dir      ,   "schedulers/scheduling_ddpm.py"							)      ,   )





				def 							__UpperCAmelCase							(   self       :  Tuple							)      ->  List[str]:
							a					=    "src/diffusers"
							shutil.rmtree(self.diffusers_dir							)





				def 							__UpperCAmelCase							(   self       :  Optional[int]      ,   __lowerCamelCase       :  List[Any]      ,   __lowerCamelCase       :  Union[str, Any]      ,   __lowerCamelCase       :  List[Any]      ,   __lowerCamelCase       :  Optional[int]=None							)      ->  str:
							a					=    comment + f"""\nclass {class_name}(nn.Module):\n""" + class_code
							if overwrite_result is not None:
										a					=    comment + f"""\nclass {class_name}(nn.Module):\n""" + overwrite_result
							a					=    black.Mode(target_versions={black.TargetVersion.PYaa}      ,   line_length=1_19							)
							a					=    black.format_str(__lowerCamelCase      ,   mode=__lowerCamelCase							)
							a					=    os.path.join(self.diffusers_dir      ,   "new_code.py"							)
							with open(__lowerCamelCase      ,   "w"      ,   newline="\n"							) as f:
										f.write(__lowerCamelCase							)
							if overwrite_result is None:
										self.assertTrue(len(check_copies.is_copy_consistent(__lowerCamelCase							)							) == 0							)
							else:
										check_copies.is_copy_consistent(f.name      ,   overwrite=__lowerCamelCase							)
										with open(__lowerCamelCase      ,   "r"							) as f:
													self.assertTrue(f.read()      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Tuple							)      ->  Dict:
							a					=    check_copies.find_code_in_diffusers("schedulers.scheduling_ddpm.DDPMSchedulerOutput"							)
							self.assertEqual(__lowerCamelCase      ,   __lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  str							)      ->  Optional[Any]:
							# Base copy consistency
							self.check_copy_consistency(
							    "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"      ,   "DDPMSchedulerOutput"      ,   REFERENCE_CODE + "\n"      ,   )

							# With no empty line at the end
							self.check_copy_consistency(
							    "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput"      ,   "DDPMSchedulerOutput"      ,   __lowerCamelCase      ,   )

							# Copy consistency with rename
							self.check_copy_consistency(
							    "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"      ,   "TestSchedulerOutput"      ,   re.sub("DDPM"      ,   "Test"      ,   __lowerCamelCase							)      ,   )

							# Copy consistency with a really long name
							a					=    "TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason"
							self.check_copy_consistency(
							    f"""# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}"""      ,   f"""{long_class_name}SchedulerOutput"""      ,   re.sub("Bert"      ,   __lowerCamelCase      ,   __lowerCamelCase							)      ,   )

							# Copy consistency with overwrite
							self.check_copy_consistency(
							    "# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test"      ,   "TestSchedulerOutput"      ,   __lowerCamelCase      ,   overwrite_result=re.sub("DDPM"      ,   "Test"      ,   __lowerCamelCase							)      ,   )












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCAmelCase	:       Any     =	{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		pass

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Optional[Any]     =	[
		    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'RoCBertForCausalLM',
		    'RoCBertForMaskedLM',
		    'RoCBertForMultipleChoice',
		    'RoCBertForPreTraining',
		    'RoCBertForQuestionAnswering',
		    'RoCBertForSequenceClassification',
		    'RoCBertForTokenClassification',
		    'RoCBertLayer',
		    'RoCBertModel',
		    'RoCBertPreTrainedModel',
		    'load_tf_weights_in_roc_bert',
		]

if TYPE_CHECKING:
		from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
		from .tokenization_roc_bert import RoCBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				raise OptionalDependencyNotAvailable()

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_roc_bert import (
				    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RoCBertForCausalLM,
				    RoCBertForMaskedLM,
				    RoCBertForMultipleChoice,
				    RoCBertForPreTraining,
				    RoCBertForQuestionAnswering,
				    RoCBertForSequenceClassification,
				    RoCBertForTokenClassification,
				    RoCBertLayer,
				    RoCBertModel,
				    RoCBertPreTrainedModel,
				    load_tf_weights_in_roc_bert,
				)


else:
		import sys

		__lowerCAmelCase	:       Union[str, Any]     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






