



"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest

import black


__SCREAMING_SNAKE_CASE  :						List[str]    							=      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.
__SCREAMING_SNAKE_CASE  :						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 							lowerCamelCase_(   unittest.TestCase    ):





					'''simple docstring'''



					def 			snake_case__      (    self   ):
									_lowerCamelCase        =				tempfile.mkdtemp()
									os.makedirs(os.path.join(self.diffusers_dir				,       '''schedulers/'''   )   )
									_lowerCamelCase        =				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   ):
									_lowerCamelCase        =				'''src/diffusers'''
									shutil.rmtree(self.diffusers_dir   )

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__=None   ):
									_lowerCamelCase        =				comment + F"""\nclass {class_name}(nn.Module):\n""" + class_code
									if overwrite_result is not None:
													_lowerCamelCase        =				comment + F"""\nclass {class_name}(nn.Module):\n""" + overwrite_result
									_lowerCamelCase        =				black.Mode(target_versions={black.TargetVersion.PYaa}				,       line_length=1_1_9   )
									_lowerCamelCase        =				black.format_str(lowerCamelCase__				,       mode=lowerCamelCase__   )
									_lowerCamelCase        =				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   ):
									_lowerCamelCase        =				check_copies.find_code_in_diffusers('''schedulers.scheduling_ddpm.DDPMSchedulerOutput'''   )
									self.assertEqual(lowerCamelCase__				,       lowerCamelCase__   )





					def 			snake_case__      (    self   ):
									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
									_lowerCamelCase        =				'''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__   )				,       )





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


__SCREAMING_SNAKE_CASE  :						Union[str, Any]    							=      {
    '''configuration_speecht5''': [
        '''SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP''',
        '''SpeechT5Config''',
        '''SpeechT5HifiGanConfig''',
    ],
    '''feature_extraction_speecht5''': ['''SpeechT5FeatureExtractor'''],
    '''processing_speecht5''': ['''SpeechT5Processor'''],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						Tuple    							=      ['''SpeechT5Tokenizer''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						Any    							=      [
			    '''SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''SpeechT5ForSpeechToText''',
			    '''SpeechT5ForSpeechToSpeech''',
			    '''SpeechT5ForTextToSpeech''',
			    '''SpeechT5Model''',
			    '''SpeechT5PreTrainedModel''',
			    '''SpeechT5HifiGan''',
			]

if TYPE_CHECKING:
			from .configuration_speechta import (
			    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
			    SpeechTaConfig,
			    SpeechTaHifiGanConfig,
			)
			from .feature_extraction_speechta import SpeechTaFeatureExtractor
			from .processing_speechta import SpeechTaProcessor

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_speechta import SpeechTaTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_speechta import (
						    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SpeechTaForSpeechToSpeech,
						    SpeechTaForSpeechToText,
						    SpeechTaForTextToSpeech,
						    SpeechTaHifiGan,
						    SpeechTaModel,
						    SpeechTaPreTrainedModel,
						)

else:
			import sys

			__SCREAMING_SNAKE_CASE  :						int    							=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
