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

import black


_lowerCamelCase					:   List[Any]							=		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					:   Dict							=		'''    \"\"\"\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 						lowercase    (     unittest.TestCase     ):




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



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       tempfile.mkdtemp()
												os.makedirs(os.path.join(self.diffusers_dir	,							"schedulers/"      )      )
												SCREAMING_SNAKE_CASE    			=       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 	__snake_case(						self   :					Dict      )					->				Union[str, Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       "src/diffusers"
												shutil.rmtree(self.diffusers_dir      )




							def 	__snake_case(						self   :					List[str]	,							_UpperCamelCase   :					Any	,							_UpperCamelCase   :					Any	,							_UpperCamelCase   :					Dict	,							_UpperCamelCase   :					str=None      )					->				Optional[Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       comment + F"\nclass {class_name}(nn.Module):\n" + class_code
												if overwrite_result is not None:
																	SCREAMING_SNAKE_CASE    			=       comment + F"\nclass {class_name}(nn.Module):\n" + overwrite_result
												SCREAMING_SNAKE_CASE    			=       black.Mode(target_versions={black.TargetVersion.PYaa}	,							line_length=119      )
												SCREAMING_SNAKE_CASE    			=       black.format_str(__lowerCAmelCase	,							mode=__lowerCAmelCase      )
												SCREAMING_SNAKE_CASE    			=       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 	__snake_case(						self   :					Any      )					->				Dict:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       check_copies.find_code_in_diffusers("schedulers.scheduling_ddpm.DDPMSchedulerOutput"      )
												self.assertEqual(__lowerCAmelCase	,							__lowerCAmelCase      )





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



												'''simple docstring'''

												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
												SCREAMING_SNAKE_CASE    			=       "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_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCamelCase					:   Optional[int]							=		{
    '''configuration_blenderbot''': [
        '''BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotConfig''',
        '''BlenderbotOnnxConfig''',
    ],
    '''tokenization_blenderbot''': ['''BlenderbotTokenizer'''],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   List[Any]							=		['''BlenderbotTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   Tuple							=		[
							    '''BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''BlenderbotForCausalLM''',
							    '''BlenderbotForConditionalGeneration''',
							    '''BlenderbotModel''',
							    '''BlenderbotPreTrainedModel''',
							]


try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   List[str]							=		[
							    '''TFBlenderbotForConditionalGeneration''',
							    '''TFBlenderbotModel''',
							    '''TFBlenderbotPreTrainedModel''',
							]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCamelCase					:   Optional[int]							=		[
							    '''FlaxBlenderbotForConditionalGeneration''',
							    '''FlaxBlenderbotModel''',
							    '''FlaxBlenderbotPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_blenderbot import (
							    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    BlenderbotConfig,
							    BlenderbotOnnxConfig,
							)
							from .tokenization_blenderbot import BlenderbotTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_blenderbot import (
														    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BlenderbotForCausalLM,
														    BlenderbotForConditionalGeneration,
														    BlenderbotModel,
														    BlenderbotPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_blenderbot import (
														    TFBlenderbotForConditionalGeneration,
														    TFBlenderbotModel,
														    TFBlenderbotPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_blenderbot import (
														    FlaxBlenderbotForConditionalGeneration,
														    FlaxBlenderbotModel,
														    FlaxBlenderbotPreTrainedModel,
														)

else:
							import sys

							_lowerCamelCase					:   Dict							=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




