
import gc
import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer

from diffusers import (
    AutoencoderKL,
    DDIMScheduler,
    EulerAncestralDiscreteScheduler,
    PNDMScheduler,
    StableDiffusionModelEditingPipeline,
    UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps

from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin


enable_full_determinism()
@skip_mps
class       A__  (		lowerCAmelCase__       ,		lowerCAmelCase__       ,		lowerCAmelCase__       ,		unittest.TestCase							):
							lowerCAmelCase__						:		Optional[int]            =				StableDiffusionModelEditingPipeline
							lowerCAmelCase__						:		List[Any]            =				TEXT_TO_IMAGE_PARAMS
							lowerCAmelCase__						:		Optional[Any]            =				TEXT_TO_IMAGE_BATCH_PARAMS
							lowerCAmelCase__						:		str            =				TEXT_TO_IMAGE_IMAGE_PARAMS
							lowerCAmelCase__						:		Any            =				TEXT_TO_IMAGE_IMAGE_PARAMS





							def      a__					(					self    :  Optional[int]							)		->						Tuple:



											"""simple docstring"""


											torch.manual_seed(0							)
											__lowercase								=   UNetaDConditionModel(
											    block_out_channels=(32, 64)	,					layers_per_block=2	,					sample_size=32	,					in_channels=4	,					out_channels=4	,					down_block_types=('DownBlock2D', 'CrossAttnDownBlock2D')	,					up_block_types=('CrossAttnUpBlock2D', 'UpBlock2D')	,					cross_attention_dim=32	,					)
											__lowercase								=   DDIMScheduler()
											torch.manual_seed(0							)
											__lowercase								=   AutoencoderKL(
											    block_out_channels=[32, 64]	,					in_channels=3	,					out_channels=3	,					down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D']	,					up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D']	,					latent_channels=4	,					)
											torch.manual_seed(0							)
											__lowercase								=   CLIPTextConfig(
											    bos_token_id=0	,					eos_token_id=2	,					hidden_size=32	,					intermediate_size=37	,					layer_norm_eps=1e-0_5	,					num_attention_heads=4	,					num_hidden_layers=5	,					pad_token_id=1	,					vocab_size=10_00	,					)
											__lowercase								=   CLIPTextModel(_UpperCAmelCase							)
											__lowercase								=   CLIPTokenizer.from_pretrained('hf-internal-testing/tiny-random-clip'							)

											__lowercase								=   {
											    'unet': unet,
											    'scheduler': scheduler,
											    'vae': vae,
											    'text_encoder': text_encoder,
											    'tokenizer': tokenizer,
											    'safety_checker': None,
											    'feature_extractor': None,
											}
											return components





							def      a__					(					self    :  Optional[Any]	,					_UpperCAmelCase    :  List[str]	,					_UpperCAmelCase    :  Dict=0							)		->						Optional[Any]:



											"""simple docstring"""


											__lowercase								=   torch.manual_seed(_UpperCAmelCase							)
											__lowercase								=   {
											    'prompt': 'A field of roses',
											    'generator': generator,
											    # Setting height and width to None to prevent OOMs on CPU.
											    'height': None,
											    'width': None,
											    'num_inference_steps': 2,
											    'guidance_scale': 6.0,
											    'output_type': 'numpy',
											}
											return inputs





							def      a__					(					self    :  Dict							)		->						List[str]:



											"""simple docstring"""


											__lowercase								=   'cpu'  # ensure determinism for the device-dependent torch.Generator
											__lowercase								=   self.get_dummy_components()
											__lowercase								=   StableDiffusionModelEditingPipeline(**_UpperCAmelCase							)
											__lowercase								=   sd_pipe.to(_UpperCAmelCase							)
											sd_pipe.set_progress_bar_config(disable=_UpperCAmelCase							)

											__lowercase								=   self.get_dummy_inputs(_UpperCAmelCase							)
											__lowercase								=   sd_pipe(**_UpperCAmelCase							).images
											__lowercase								=   image[0, -3:, -3:, -1]
											assert image.shape == (1, 64, 64, 3)

											__lowercase								=   np.array([0.4_755, 0.5_132, 0.4_976, 0.3_904, 0.3_554, 0.4_765, 0.5_139, 0.5_158, 0.4_889]							)

											assert np.abs(image_slice.flatten() - expected_slice							).max() < 1e-2





							def      a__					(					self    :  int							)		->						List[str]:



											"""simple docstring"""


											__lowercase								=   'cpu'  # ensure determinism for the device-dependent torch.Generator
											__lowercase								=   self.get_dummy_components()
											__lowercase								=   StableDiffusionModelEditingPipeline(**_UpperCAmelCase							)
											__lowercase								=   sd_pipe.to(_UpperCAmelCase							)
											sd_pipe.set_progress_bar_config(disable=_UpperCAmelCase							)

											__lowercase								=   self.get_dummy_inputs(_UpperCAmelCase							)
											__lowercase								=   'french fries'
											__lowercase								=   sd_pipe(**_UpperCAmelCase	,					negative_prompt=_UpperCAmelCase							)
											__lowercase								=   output.images
											__lowercase								=   image[0, -3:, -3:, -1]

											assert image.shape == (1, 64, 64, 3)

											__lowercase								=   np.array([0.4_992, 0.5_101, 0.5_004, 0.3_949, 0.3_604, 0.4_735, 0.5_216, 0.5_204, 0.4_913]							)

											assert np.abs(image_slice.flatten() - expected_slice							).max() < 1e-2





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



											"""simple docstring"""


											__lowercase								=   'cpu'  # ensure determinism for the device-dependent torch.Generator
											__lowercase								=   self.get_dummy_components()
											__lowercase								=   EulerAncestralDiscreteScheduler(
											    beta_start=0.00_085	,					beta_end=0.012	,					beta_schedule='scaled_linear'							)
											__lowercase								=   StableDiffusionModelEditingPipeline(**_UpperCAmelCase							)
											__lowercase								=   sd_pipe.to(_UpperCAmelCase							)
											sd_pipe.set_progress_bar_config(disable=_UpperCAmelCase							)

											__lowercase								=   self.get_dummy_inputs(_UpperCAmelCase							)
											__lowercase								=   sd_pipe(**_UpperCAmelCase							).images
											__lowercase								=   image[0, -3:, -3:, -1]

											assert image.shape == (1, 64, 64, 3)

											__lowercase								=   np.array([0.4_747, 0.5_372, 0.4_779, 0.4_982, 0.5_543, 0.4_816, 0.5_238, 0.4_904, 0.5_027]							)

											assert np.abs(image_slice.flatten() - expected_slice							).max() < 1e-2





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



											"""simple docstring"""


											__lowercase								=   'cpu'  # ensure determinism for the device-dependent torch.Generator
											__lowercase								=   self.get_dummy_components()
											__lowercase								=   PNDMScheduler()
											__lowercase								=   StableDiffusionModelEditingPipeline(**_UpperCAmelCase							)
											__lowercase								=   sd_pipe.to(_UpperCAmelCase							)
											sd_pipe.set_progress_bar_config(disable=_UpperCAmelCase							)

											__lowercase								=   self.get_dummy_inputs(_UpperCAmelCase							)
											# the pipeline does not expect pndm so test if it raises error.
											with self.assertRaises(_UpperCAmelCase							):
															__lowercase								=   sd_pipe(**_UpperCAmelCase							).images





							def      a__					(					self    :  Optional[int]							)		->						List[str]:



											"""simple docstring"""


											super().test_inference_batch_single_identical(expected_max_diff=5e-3							)





							def      a__					(					self    :  Tuple							)		->						Dict:



											"""simple docstring"""


											super().test_attention_slicing_forward_pass(expected_max_diff=5e-3							)






@slow
@require_torch_gpu
class       A__  (		unittest.TestCase							):





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



											"""simple docstring"""


											super().tearDown()
											gc.collect()
											torch.cuda.empty_cache()





							def      a__					(					self    :  Optional[int]	,					_UpperCAmelCase    :  Optional[int]=0							)		->						Optional[Any]:



											"""simple docstring"""


											__lowercase								=   torch.manual_seed(_UpperCAmelCase							)
											__lowercase								=   {
											    'prompt': 'A field of roses',
											    'generator': generator,
											    'num_inference_steps': 3,
											    'guidance_scale': 7.5,
											    'output_type': 'numpy',
											}
											return inputs





							def      a__					(					self    :  Optional[Any]							)		->						Dict:



											"""simple docstring"""


											__lowercase								=   'CompVis/stable-diffusion-v1-4'
											__lowercase								=   StableDiffusionModelEditingPipeline.from_pretrained(_UpperCAmelCase	,					safety_checker=_UpperCAmelCase							)
											pipe.to(_UpperCAmelCase							)
											pipe.set_progress_bar_config(disable=_UpperCAmelCase							)
											pipe.enable_attention_slicing()

											__lowercase								=   self.get_inputs()
											__lowercase								=   pipe(**_UpperCAmelCase							).images
											__lowercase								=   image[0, -3:, -3:, -1].flatten()

											assert image.shape == (1, 5_12, 5_12, 3)

											__lowercase								=   np.array(
											    [0.6_749_496, 0.6_386_453, 0.51_443_267, 0.66_094_905, 0.61_921_215, 0.5_491_332, 0.5_744_417, 0.58_075_106, 0.5_174_658]							)

											assert np.abs(expected_slice - image_slice							).max() < 1e-2

											# make sure image changes after editing
											pipe.edit_model('A pack of roses'	,					'A pack of blue roses'							)

											__lowercase								=   pipe(**_UpperCAmelCase							).images
											__lowercase								=   image[0, -3:, -3:, -1].flatten()

											assert image.shape == (1, 5_12, 5_12, 3)

											assert np.abs(expected_slice - image_slice							).max() > 1e-1





							def      a__					(					self    :  List[Any]							)		->						List[Any]:



											"""simple docstring"""


											torch.cuda.empty_cache()
											torch.cuda.reset_max_memory_allocated()
											torch.cuda.reset_peak_memory_stats()

											__lowercase								=   'CompVis/stable-diffusion-v1-4'
											__lowercase								=   DDIMScheduler.from_pretrained(_UpperCAmelCase	,					subfolder='scheduler'							)
											__lowercase								=   StableDiffusionModelEditingPipeline.from_pretrained(
											    _UpperCAmelCase	,					scheduler=_UpperCAmelCase	,					safety_checker=_UpperCAmelCase							)
											__lowercase								=   pipe.to(_UpperCAmelCase							)
											pipe.set_progress_bar_config(disable=_UpperCAmelCase							)
											pipe.enable_attention_slicing(1							)
											pipe.enable_sequential_cpu_offload()

											__lowercase								=   self.get_inputs()
											__lowercase								=   pipe(**_UpperCAmelCase							)

											__lowercase								=   torch.cuda.max_memory_allocated()
											# make sure that less than 4.4 GB is allocated
											assert mem_bytes < 4.4 * 10**9







from ..utils import DummyObject, requires_backends
class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





							def __init__(					self    :  str	,					*_UpperCAmelCase    :  List[str]	,					**_UpperCAmelCase    :  List[str]							)		->						int:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Dict            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Union[str, Any]            =				["tokenizers"]





							def __init__(					self    :  Union[str, Any]	,					*_UpperCAmelCase    :  Union[str, Any]	,					**_UpperCAmelCase    :  int							)		->						Dict:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		str            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[Any]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[str]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





							def __init__(					self    :  Optional[Any]	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Any							)		->						Optional[Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Dict            =				["tokenizers"]





							def __init__(					self    :  List[str]	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  List[str]							)		->						List[Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[Any]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  List[Any]	,					**_UpperCAmelCase    :  int							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





							def __init__(					self    :  List[str]	,					*_UpperCAmelCase    :  Any	,					**_UpperCAmelCase    :  str							)		->						int:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		str            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Dict            =				["tokenizers"]





							def __init__(					self    :  int	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Optional[Any]							)		->						Dict:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[Any]            =				["tokenizers"]





							def __init__(					self    :  Dict	,					*_UpperCAmelCase    :  Optional[Any]	,					**_UpperCAmelCase    :  List[Any]							)		->						Optional[Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Dict            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[str]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		int            =				["tokenizers"]





							def __init__(					self    :  Optional[Any]	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Tuple							)		->						List[str]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		int            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Tuple							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[str]            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  List[Any]	,					**_UpperCAmelCase    :  Tuple							)		->						List[Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[str]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





							def __init__(					self    :  Any	,					*_UpperCAmelCase    :  Optional[Any]	,					**_UpperCAmelCase    :  str							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		str            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Dict            =				["tokenizers"]





							def __init__(					self    :  Union[str, Any]	,					*_UpperCAmelCase    :  Dict	,					**_UpperCAmelCase    :  Any							)		->						Any:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Union[str, Any]            =				["tokenizers"]





							def __init__(					self    :  Any	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Optional[int]							)		->						int:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Union[str, Any]            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  Optional[int]	,					**_UpperCAmelCase    :  Tuple							)		->						List[str]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





							def __init__(					self    :  Dict	,					*_UpperCAmelCase    :  Optional[Any]	,					**_UpperCAmelCase    :  Optional[int]							)		->						Dict:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





							def __init__(					self    :  Optional[int]	,					*_UpperCAmelCase    :  Dict	,					**_UpperCAmelCase    :  str							)		->						Optional[int]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		int            =				["tokenizers"]





							def __init__(					self    :  Optional[Any]	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Any							)		->						str:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





							def __init__(					self    :  Dict	,					*_UpperCAmelCase    :  List[Any]	,					**_UpperCAmelCase    :  Tuple							)		->						Optional[Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[Any]            =				["tokenizers"]





							def __init__(					self    :  Any	,					*_UpperCAmelCase    :  Any	,					**_UpperCAmelCase    :  Tuple							)		->						List[str]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Union[str, Any]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[Any]            =				["tokenizers"]





							def __init__(					self    :  Optional[int]	,					*_UpperCAmelCase    :  Optional[int]	,					**_UpperCAmelCase    :  str							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





							def __init__(					self    :  Optional[int]	,					*_UpperCAmelCase    :  str	,					**_UpperCAmelCase    :  Optional[int]							)		->						Optional[int]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[str]            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Optional[Any]							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[Any]            =				["tokenizers"]





							def __init__(					self    :  int	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  Dict							)		->						Union[str, Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Union[str, Any]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[Any]            =				["tokenizers"]





							def __init__(					self    :  Dict	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  List[str]							)		->						Any:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		int            =				["tokenizers"]





							def __init__(					self    :  Optional[Any]	,					*_UpperCAmelCase    :  int	,					**_UpperCAmelCase    :  Optional[int]							)		->						Dict:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





							def __init__(					self    :  Optional[int]	,					*_UpperCAmelCase    :  Any	,					**_UpperCAmelCase    :  Tuple							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  Any	,					**_UpperCAmelCase    :  Any							)		->						List[str]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		int            =				["tokenizers"]





							def __init__(					self    :  int	,					*_UpperCAmelCase    :  Any	,					**_UpperCAmelCase    :  Any							)		->						str:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		List[Any]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[int]            =				["tokenizers"]





							def __init__(					self    :  List[Any]	,					*_UpperCAmelCase    :  Any	,					**_UpperCAmelCase    :  Dict							)		->						Optional[Any]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Optional[Any]            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





							def __init__(					self    :  Tuple	,					*_UpperCAmelCase    :  List[str]	,					**_UpperCAmelCase    :  Optional[int]							)		->						List[str]:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Any            =				["tokenizers"]





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



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Dict            =				["tokenizers"]





							def __init__(					self    :  Optional[Any]	,					*_UpperCAmelCase    :  Tuple	,					**_UpperCAmelCase    :  str							)		->						Any:



											"""simple docstring"""


											requires_backends(self	,					['tokenizers']							)





