


import argparse
import json
import os

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import ConvNextImageProcessor, ConvNextVaConfig, ConvNextVaForImageClassification
from transformers.image_utils import PILImageResampling
from transformers.utils import logging


logging.set_verbosity_info()
__magic_name__       					=      logging.get_logger(__name__)







def     __magic_name__  (      lowerCAmelCase_):
	'''simple docstring'''


	lowerCamelCase_			:							Any      =       ConvNextVaConfig()

	if "atto" in checkpoint_url:
		lowerCamelCase_			:							Tuple      =       [2, 2, 6, 2]
		lowerCamelCase_			:							Optional[Any]      =       [40, 80, 160, 320]
	if "femto" in checkpoint_url:
		lowerCamelCase_			:							Tuple      =       [2, 2, 6, 2]
		lowerCamelCase_			:							List[str]      =       [48, 96, 192, 384]
	if "pico" in checkpoint_url:
		lowerCamelCase_			:							Optional[Any]      =       [2, 2, 6, 2]
		lowerCamelCase_			:							Any      =       [64, 128, 256, 512]
	if "nano" in checkpoint_url:
		lowerCamelCase_			:							List[str]      =       [2, 2, 8, 2]
		lowerCamelCase_			:							List[Any]      =       [80, 160, 320, 640]
	if "tiny" in checkpoint_url:
		lowerCamelCase_			:							Dict      =       [3, 3, 9, 3]
		lowerCamelCase_			:							List[str]      =       [96, 192, 384, 768]
	if "base" in checkpoint_url:
		lowerCamelCase_			:							Union[str, Any]      =       [3, 3, 27, 3]
		lowerCamelCase_			:							Tuple      =       [128, 256, 512, 1024]
	if "large" in checkpoint_url:
		lowerCamelCase_			:							Optional[int]      =       [3, 3, 27, 3]
		lowerCamelCase_			:							Union[str, Any]      =       [192, 384, 768, 1536]
	if "huge" in checkpoint_url:
		lowerCamelCase_			:							int      =       [3, 3, 27, 3]
		lowerCamelCase_			:							Dict      =       [352, 704, 1408, 2816]

	lowerCamelCase_			:							Any      =       1000
	lowerCamelCase_			:							List[Any]      =       "imagenet-1k-id2label.json"
	lowerCamelCase_			:							Dict      =       (1, 1000)

	lowerCamelCase_			:							Dict      =       "huggingface/label-files"
	lowerCamelCase_			:							List[str]      =       num_labels
	lowerCamelCase_			:							Tuple      =       json.load(open(hf_hub_download(lowerCAmelCase_      ,					lowerCAmelCase_      ,					repo_type="dataset")      ,					"r"))
	lowerCamelCase_			:							Tuple      =       {int(lowerCAmelCase_): v for k, v in idalabel.items()}

	lowerCamelCase_			:							Optional[Any]      =       idalabel
	lowerCamelCase_			:							Union[str, Any]      =       {v: k for k, v in idalabel.items()}
	lowerCamelCase_			:							List[str]      =       hidden_sizes
	lowerCamelCase_			:							List[str]      =       depths

	return config, expected_shape







def     __magic_name__  (      lowerCAmelCase_):
	'''simple docstring'''


	if "downsample_layers.0.0" in name:
		lowerCamelCase_			:							List[Any]      =       name.replace("downsample_layers.0.0"      ,					"embeddings.patch_embeddings")
	if "downsample_layers.0.1" in name:
		lowerCamelCase_			:							List[Any]      =       name.replace("downsample_layers.0.1"      ,					"embeddings.norm")  # we rename to layernorm later on
	if "downsample_layers.1.0" in name:
		lowerCamelCase_			:							Optional[int]      =       name.replace("downsample_layers.1.0"      ,					"stages.1.downsampling_layer.0")
	if "downsample_layers.1.1" in name:
		lowerCamelCase_			:							List[Any]      =       name.replace("downsample_layers.1.1"      ,					"stages.1.downsampling_layer.1")
	if "downsample_layers.2.0" in name:
		lowerCamelCase_			:							List[Any]      =       name.replace("downsample_layers.2.0"      ,					"stages.2.downsampling_layer.0")
	if "downsample_layers.2.1" in name:
		lowerCamelCase_			:							int      =       name.replace("downsample_layers.2.1"      ,					"stages.2.downsampling_layer.1")
	if "downsample_layers.3.0" in name:
		lowerCamelCase_			:							List[str]      =       name.replace("downsample_layers.3.0"      ,					"stages.3.downsampling_layer.0")
	if "downsample_layers.3.1" in name:
		lowerCamelCase_			:							str      =       name.replace("downsample_layers.3.1"      ,					"stages.3.downsampling_layer.1")
	if "stages" in name and "downsampling_layer" not in name:
		# stages.0.0. for instance should be renamed to stages.0.layers.0.
		lowerCamelCase_			:							str      =       name[: len("stages.0")] + ".layers" + name[len("stages.0") :]
	if "gamma" in name:
		lowerCamelCase_			:							Tuple      =       name.replace("gamma"      ,					"weight")
	if "beta" in name:
		lowerCamelCase_			:							str      =       name.replace("beta"      ,					"bias")
	if "stages" in name:
		lowerCamelCase_			:							str      =       name.replace("stages"      ,					"encoder.stages")
	if "norm" in name:
		lowerCamelCase_			:							Optional[Any]      =       name.replace("norm"      ,					"layernorm")
	if "head" in name:
		lowerCamelCase_			:							str      =       name.replace("head"      ,					"classifier")

	return name







def     __magic_name__  (      ):
	'''simple docstring'''


	lowerCamelCase_			:							Optional[int]      =       "http://images.cocodataset.org/val2017/000000039769.jpg"
	lowerCamelCase_			:							List[str]      =       Image.open(requests.get(lowerCAmelCase_      ,					stream=lowerCAmelCase_).raw)
	return im







def     __magic_name__  (      lowerCAmelCase_):
	'''simple docstring'''


	if "224" in checkpoint_url:
		lowerCamelCase_			:							List[str]      =       224
		lowerCamelCase_			:							Optional[Any]      =       224 / 256
	elif "384" in checkpoint_url:
		lowerCamelCase_			:							List[str]      =       384
		lowerCamelCase_			:							List[Any]      =       None
	else:
		lowerCamelCase_			:							Dict      =       512
		lowerCamelCase_			:							List[Any]      =       None

	return ConvNextImageProcessor(
	    size=lowerCAmelCase_      ,					crop_pct=lowerCAmelCase_      ,					image_mean=[0.4_85, 0.4_56, 0.4_06]      ,					image_std=[0.2_29, 0.2_24, 0.2_25]      ,					resample=PILImageResampling.BICUBIC      ,					)







@torch.no_grad()
def     __magic_name__  (      lowerCAmelCase_      ,					lowerCAmelCase_      ,					lowerCAmelCase_      ,					lowerCAmelCase_):
	'''simple docstring'''


	print("Downloading original model from checkpoint...")
	# define ConvNeXTV2 configuration based on URL
	lowerCamelCase_   ,lowerCamelCase_			:							Union[str, Any]      =       get_convnextva_config(lowerCAmelCase_)
	# load original state_dict from URL
	lowerCamelCase_			:							Union[str, Any]      =       torch.hub.load_state_dict_from_url(lowerCAmelCase_)["model"]

	print("Converting model parameters...")
	# rename keys
	for key in state_dict.copy().keys():
		lowerCamelCase_			:							Optional[int]      =       state_dict.pop(lowerCAmelCase_)
		lowerCamelCase_			:							Dict      =       val
	# add prefix to all keys expect classifier head
	for key in state_dict.copy().keys():
		lowerCamelCase_			:							Optional[int]      =       state_dict.pop(lowerCAmelCase_)
		if not key.startswith("classifier"):
			lowerCamelCase_			:							Optional[Any]      =       "convnextv2." + key
		lowerCamelCase_			:							Optional[int]      =       val

	# load HuggingFace model
	lowerCamelCase_			:							Dict      =       ConvNextVaForImageClassification(lowerCAmelCase_)
	model.load_state_dict(lowerCAmelCase_)
	model.eval()

	# Check outputs on an image, prepared by ConvNextImageProcessor
	lowerCamelCase_			:							List[str]      =       convert_preprocessor(lowerCAmelCase_)
	lowerCamelCase_			:							Tuple      =       preprocessor(images=prepare_img()      ,					return_tensors="pt")
	lowerCamelCase_			:							Union[str, Any]      =       model(**lowerCAmelCase_).logits

	# note: the logits below were obtained without center cropping
	if checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_atto_1k_224_ema.pt":
		lowerCamelCase_			:							Tuple      =       torch.tensor([-0.39_30, 0.17_47, -0.52_46, 0.41_77, 0.42_95])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_femto_1k_224_ema.pt":
		lowerCamelCase_			:							List[str]      =       torch.tensor([-0.17_27, -0.53_41, -0.78_18, -0.47_45, -0.65_66])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_pico_1k_224_ema.pt":
		lowerCamelCase_			:							Dict      =       torch.tensor([-0.03_33, 0.15_63, -0.91_37, 0.10_54, 0.03_81])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_nano_1k_224_ema.pt":
		lowerCamelCase_			:							Tuple      =       torch.tensor([-0.17_44, -0.15_55, -0.07_13, 0.09_50, -0.14_31])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_tiny_1k_224_ema.pt":
		lowerCamelCase_			:							Dict      =       torch.tensor([0.99_96, 0.19_66, -0.43_86, -0.34_72, 0.66_61])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_base_1k_224_ema.pt":
		lowerCamelCase_			:							List[str]      =       torch.tensor([-0.25_53, -0.67_08, -0.13_59, 0.25_18, -0.24_88])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_large_1k_224_ema.pt":
		lowerCamelCase_			:							Optional[Any]      =       torch.tensor([-0.06_73, -0.56_27, -0.37_53, -0.27_22, 0.01_78])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_huge_1k_224_ema.pt":
		lowerCamelCase_			:							Tuple      =       torch.tensor([-0.63_77, -0.74_58, -0.21_50, 0.11_84, -0.05_97])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_nano_22k_224_ema.pt":
		lowerCamelCase_			:							Union[str, Any]      =       torch.tensor([1.07_99, 0.23_22, -0.88_60, 1.02_19, 0.62_31])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_nano_22k_384_ema.pt":
		lowerCamelCase_			:							Optional[int]      =       torch.tensor([0.37_66, 0.49_17, -1.14_26, 0.99_42, 0.60_24])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_tiny_22k_224_ema.pt":
		lowerCamelCase_			:							List[str]      =       torch.tensor([0.42_20, -0.69_19, -0.43_17, -0.28_81, -0.66_09])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_tiny_22k_384_ema.pt":
		lowerCamelCase_			:							Optional[int]      =       torch.tensor([0.10_82, -0.82_86, -0.50_95, 0.46_81, -0.80_85])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_base_22k_224_ema.pt":
		lowerCamelCase_			:							str      =       torch.tensor([-0.24_19, -0.62_21, 0.21_76, -0.09_80, -0.75_27])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_base_22k_384_ema.pt":
		lowerCamelCase_			:							Dict      =       torch.tensor([0.03_91, -0.43_71, 0.37_86, 0.12_51, -0.27_84])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_large_22k_224_ema.pt":
		lowerCamelCase_			:							Any      =       torch.tensor([-0.05_04, 0.56_36, -0.17_29, -0.65_07, -0.39_49])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_large_22k_384_ema.pt":
		lowerCamelCase_			:							Any      =       torch.tensor([0.35_60, 0.94_86, 0.31_49, -0.26_67, -0.51_38])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_huge_22k_384_ema.pt":
		lowerCamelCase_			:							List[str]      =       torch.tensor([-0.24_69, -0.45_50, -0.58_53, -0.08_10, 0.03_09])
	elif checkpoint_url == "https://dl.fbaipublicfiles.com/convnext/convnextv2/im22k/convnextv2_huge_22k_512_ema.pt":
		lowerCamelCase_			:							List[str]      =       torch.tensor([-0.30_90, 0.08_02, -0.06_82, -0.19_79, -0.28_26])
	else:
		raise ValueError(F"""Unknown URL: {checkpoint_url}""")

	assert torch.allclose(logits[0, :5]      ,					lowerCAmelCase_      ,					atol=1E-3)
	assert logits.shape == expected_shape
	print("Model outputs match the original results!")

	if save_model:
		print("Saving model to local...")
		# Create folder to save model
		if not os.path.isdir(lowerCAmelCase_):
			os.mkdir(lowerCAmelCase_)

		model.save_pretrained(lowerCAmelCase_)
		preprocessor.save_pretrained(lowerCAmelCase_)

	lowerCamelCase_			:							int      =       "convnextv2"
	if "atto" in checkpoint_url:
		model_name += "-atto"
	if "femto" in checkpoint_url:
		model_name += "-femto"
	if "pico" in checkpoint_url:
		model_name += "-pico"
	if "nano" in checkpoint_url:
		model_name += "-nano"
	elif "tiny" in checkpoint_url:
		model_name += "-tiny"
	elif "base" in checkpoint_url:
		model_name += "-base"
	elif "large" in checkpoint_url:
		model_name += "-large"
	elif "huge" in checkpoint_url:
		model_name += "-huge"
	if "22k" in checkpoint_url and "1k" not in checkpoint_url:
		model_name += "-22k"
	elif "22k" in checkpoint_url and "1k" in checkpoint_url:
		model_name += "-22k-1k"
	elif "1k" in checkpoint_url:
		model_name += "-1k"
	if "224" in checkpoint_url:
		model_name += "-224"
	elif "384" in checkpoint_url:
		model_name += "-384"
	elif "512" in checkpoint_url:
		model_name += "-512"

	if push_to_hub:
		print(F"""Pushing {model_name} to the hub...""")
		model.push_to_hub(lowerCAmelCase_)
		preprocessor.push_to_hub(lowerCAmelCase_)


if __name__ == "__main__":
							__magic_name__       					=      argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    '''--checkpoint_url''',
							    default='''https://dl.fbaipublicfiles.com/convnext/convnextv2/im1k/convnextv2_atto_1k_224_ema.pt''',
							    type=str,
							    help='''URL of the original ConvNeXTV2 checkpoint you\'d like to convert.''',
							)
							parser.add_argument(
							    '''--pytorch_dump_folder_path''',
							    default='''model''',
							    type=str,
							    help='''Path to the output PyTorch model directory.''',
							)
							parser.add_argument('''--save_model''', action='''store_true''', help='''Save model to local''')
							parser.add_argument('''--push_to_hub''', action='''store_true''', help='''Push model and image preprocessor to the hub''')

							__magic_name__       					=      parser.parse_args()
							convert_convnextva_checkpoint(
							    args.checkpoint_url, args.pytorch_dump_folder_path, args.save_model, args.push_to_hub
							)





from ..utils import DummyObject, requires_backends





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		str  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[str]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Tuple  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Tuple  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		int  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[int]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Tuple  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[int]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Tuple  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		int  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[str]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Dict  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		str  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Dict  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		int  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		int  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Dict  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		str  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[int]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Dict  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		str  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		str  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Dict  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Tuple  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		int  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Optional[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[str]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Tuple  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Union[str, Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[Any]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Any  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		int  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		Dict  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		List[str]  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )





class    lowerCAmelCase__				(			metaclass=__lowerCamelCase       ):






						"""simple docstring"""
						__UpperCAmelCase   :		str  					=	['''tokenizers''']




						def __init__(   self				,							*a_				,							**a_     ):
							requires_backends(self				,							["tokenizers"]     )

