
import argparse

import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download

from transformers import (
    CLIPTokenizer,
    CLIPTokenizerFast,
    VideoMAEImageProcessor,
    XCLIPConfig,
    XCLIPModel,
    XCLIPProcessor,
    XCLIPTextConfig,
    XCLIPVisionConfig,
)



def   __lowerCAmelCase    (				UpperCAmelCase__					:   Tuple      ,					UpperCAmelCase__					:   Optional[int]							)	->     Tuple:
							lowerCamelCase_					=       XCLIPTextConfig()

							# derive patch size from model name
							lowerCamelCase_					=       model_name.find("""patch"""							)
							lowerCamelCase_					=       int(model_name[start_idx + len("""patch"""							) : start_idx + len("""patch"""							) + 2]							)
							lowerCamelCase_					=       XCLIPVisionConfig(patch_size=UpperCAmelCase__      ,					num_frames=UpperCAmelCase__							)

							if "large" in model_name:
														lowerCamelCase_					=       7_6_8
														lowerCamelCase_					=       3_0_7_2
														lowerCamelCase_					=       1_2

														lowerCamelCase_					=       1_0_2_4
														lowerCamelCase_					=       4_0_9_6
														lowerCamelCase_					=       1_6
														lowerCamelCase_					=       2_4
														lowerCamelCase_					=       7_6_8
														lowerCamelCase_					=       3_0_7_2

							if model_name == "xclip-large-patch14-16-frames":
														lowerCamelCase_					=       3_3_6

							lowerCamelCase_					=       XCLIPConfig.from_text_vision_configs(UpperCAmelCase__      ,					UpperCAmelCase__							)

							if "large" in model_name:
														lowerCamelCase_					=       7_6_8

							return config



def   __lowerCAmelCase    (				UpperCAmelCase__					:   List[Any]							)	->     Tuple:
							# text encoder
							if name == "token_embedding.weight":
														lowerCamelCase_					=       name.replace("""token_embedding.weight"""      ,					"""text_model.embeddings.token_embedding.weight"""							)
							if name == "positional_embedding":
														lowerCamelCase_					=       name.replace("""positional_embedding"""      ,					"""text_model.embeddings.position_embedding.weight"""							)
							if "ln_1" in name:
														lowerCamelCase_					=       name.replace("""ln_1"""      ,					"""layer_norm1"""							)
							if "ln_2" in name:
														lowerCamelCase_					=       name.replace("""ln_2"""      ,					"""layer_norm2"""							)
							if "c_fc" in name:
														lowerCamelCase_					=       name.replace("""c_fc"""      ,					"""fc1"""							)
							if "c_proj" in name:
														lowerCamelCase_					=       name.replace("""c_proj"""      ,					"""fc2"""							)
							if name.startswith("""transformer.resblocks"""							):
														lowerCamelCase_					=       name.replace("""transformer.resblocks"""      ,					"""text_model.encoder.layers"""							)
							if "attn.out_proj" in name and "message" not in name:
														lowerCamelCase_					=       name.replace("""attn.out_proj"""      ,					"""self_attn.out_proj"""							)
							if "ln_final" in name:
														lowerCamelCase_					=       name.replace("""ln_final"""      ,					"""text_model.final_layer_norm"""							)
							# visual encoder
							if name == "visual.class_embedding":
														lowerCamelCase_					=       name.replace("""visual.class_embedding"""      ,					"""vision_model.embeddings.class_embedding"""							)
							if name == "visual.positional_embedding":
														lowerCamelCase_					=       name.replace("""visual.positional_embedding"""      ,					"""vision_model.embeddings.position_embedding.weight"""							)
							if name.startswith("""visual.transformer.resblocks"""							):
														lowerCamelCase_					=       name.replace("""visual.transformer.resblocks"""      ,					"""vision_model.encoder.layers"""							)
							if "visual.conv1" in name:
														lowerCamelCase_					=       name.replace("""visual.conv1"""      ,					"""vision_model.embeddings.patch_embedding"""							)
							if "visual.ln_pre" in name:
														lowerCamelCase_					=       name.replace("""visual.ln_pre"""      ,					"""vision_model.pre_layernorm"""							)
							if "visual.ln_post" in name:
														lowerCamelCase_					=       name.replace("""visual.ln_post"""      ,					"""vision_model.post_layernorm"""							)
							if "visual.proj" in name:
														lowerCamelCase_					=       name.replace("""visual.proj"""      ,					"""visual_projection.weight"""							)
							if "text_projection" in name:
														lowerCamelCase_					=       name.replace("""text_projection"""      ,					"""text_projection.weight"""							)
							# things on top
							if "prompts_visual_proj" in name:
														lowerCamelCase_					=       name.replace("""prompts_visual_proj"""      ,					"""prompts_visual_projection"""							)
							if "prompts_visual_ln" in name:
														lowerCamelCase_					=       name.replace("""prompts_visual_ln"""      ,					"""prompts_visual_layernorm"""							)
							# mit
							if name == "mit.positional_embedding":
														lowerCamelCase_					=       name.replace("""positional"""      ,					"""position"""							)
							if name.startswith("""mit.resblocks"""							):
														lowerCamelCase_					=       name.replace("""mit.resblocks"""      ,					"""mit.encoder.layers"""							)
							# prompts generator
							if name.startswith("""prompts_generator.norm"""							):
														lowerCamelCase_					=       name.replace("""prompts_generator.norm"""      ,					"""prompts_generator.layernorm"""							)

							return name



def   __lowerCAmelCase    (				UpperCAmelCase__					:   List[str]      ,					UpperCAmelCase__					:   List[str]							)	->     List[Any]:
							for key in orig_state_dict.copy().keys():
														lowerCamelCase_					=       orig_state_dict.pop(UpperCAmelCase__							)

														if "attn.in_proj" in key:
																					lowerCamelCase_					=       key.split("""."""							)
																					if key.startswith("""visual"""							):
																												lowerCamelCase_					=       key_split[3]
																												lowerCamelCase_					=       config.vision_config.hidden_size
																												if "message_attn" in key:
																																			if "weight" in key:
																																										lowerCamelCase_					=       val[
																																										    :dim, :
																																										]
																																										lowerCamelCase_					=       val[
																																										    dim : dim * 2, :
																																										]
																																										lowerCamelCase_					=       val[
																																										    -dim:, :
																																										]
																																			else:
																																										lowerCamelCase_					=       val[
																																										    :dim
																																										]
																																										lowerCamelCase_					=       val[
																																										    dim : dim * 2
																																										]
																																										lowerCamelCase_					=       val[
																																										    -dim:
																																										]
																												else:
																																			if "weight" in key:
																																										lowerCamelCase_					=       val[
																																										    :dim, :
																																										]
																																										lowerCamelCase_					=       val[
																																										    dim : dim * 2, :
																																										]
																																										lowerCamelCase_					=       val[
																																										    -dim:, :
																																										]
																																			else:
																																										lowerCamelCase_					=       val[:dim]
																																										lowerCamelCase_					=       val[
																																										    dim : dim * 2
																																										]
																																										lowerCamelCase_					=       val[-dim:]
																					elif key.startswith("""mit"""							):
																												lowerCamelCase_					=       key_split[2]
																												lowerCamelCase_					=       config.vision_config.mit_hidden_size
																												if "weight" in key:
																																			lowerCamelCase_					=       val[:dim, :]
																																			lowerCamelCase_					=       val[dim : dim * 2, :]
																																			lowerCamelCase_					=       val[-dim:, :]
																												else:
																																			lowerCamelCase_					=       val[:dim]
																																			lowerCamelCase_					=       val[dim : dim * 2]
																																			lowerCamelCase_					=       val[-dim:]
																					else:
																												lowerCamelCase_					=       key_split[2]
																												lowerCamelCase_					=       config.text_config.hidden_size
																												if "weight" in key:
																																			lowerCamelCase_					=       val[:dim, :]
																																			lowerCamelCase_					=       val[
																																			    dim : dim * 2, :
																																			]
																																			lowerCamelCase_					=       val[-dim:, :]
																												else:
																																			lowerCamelCase_					=       val[:dim]
																																			lowerCamelCase_					=       val[
																																			    dim : dim * 2
																																			]
																																			lowerCamelCase_					=       val[-dim:]
														else:
																					lowerCamelCase_					=       rename_key(UpperCAmelCase__							)
																					if new_key_name in ["visual_projection.weight", "text_projection.weight"]:
																												lowerCamelCase_					=       val.T
																					lowerCamelCase_					=       val

							return orig_state_dict



def   __lowerCAmelCase    (				UpperCAmelCase__					:   Dict							)	->     List[Any]:
							if num_frames == 8:
														lowerCamelCase_					=       """eating_spaghetti_8_frames.npy"""
							elif num_frames == 1_6:
														lowerCamelCase_					=       """eating_spaghetti.npy"""
							elif num_frames == 3_2:
														lowerCamelCase_					=       """eating_spaghetti_32_frames.npy"""
							lowerCamelCase_					=       hf_hub_download(
							    repo_id="""hf-internal-testing/spaghetti-video"""      ,					filename=UpperCAmelCase__      ,					repo_type="""dataset"""      ,					)
							lowerCamelCase_					=       np.load(UpperCAmelCase__							)
							return list(UpperCAmelCase__							)



def   __lowerCAmelCase    (				UpperCAmelCase__					:   Any      ,					UpperCAmelCase__					:   Any=None      ,					UpperCAmelCase__					:   List[str]=False							)	->     Tuple:
							lowerCamelCase_					=       {
							    # fully supervised kinetics-400 checkpoints
							    """xclip-base-patch32""": """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/k400_32_8.pth""",
							    """xclip-base-patch32-16-frames""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/k400_32_16.pth"""
							    ),
							    """xclip-base-patch16""": """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/k400_16_8.pth""",
							    """xclip-base-patch16-16-frames""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/k400_16_16.pth"""
							    ),
							    """xclip-large-patch14""": """https://drive.google.com/u/0/uc?id=1NUOImq0o5DlQTST17iIP3vG7DgmHQuCx&amp;export=download&amp;confirm=t&amp;uuid=b26caedc-88e2-473e-830a-9d158b653cdb""",
							    """xclip-large-patch14-16-frames""": """https://drive.google.com/u/0/uc?id=1FOYgnJc097OJ4lGwtRCCydQyVPJEOH7d&amp;export=download&amp;confirm=t&amp;uuid=538fa810-e671-4050-b385-9a623f89804f""",
							    # fully supervised kinetics-600 checkpoints
							    """xclip-base-patch16-kinetics-600""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/k600_16_8.pth"""
							    ),
							    """xclip-base-patch16-kinetics-600-16-frames""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/k600_16_16.pth"""
							    ),
							    """xclip-large-patch14-kinetics-600""": """https://drive.google.com/u/0/uc?id=1FV8C1INuM91sLAN4ImjzePLIlpMSihwV&amp;export=download&amp;confirm=t&amp;uuid=141d4977-4a65-44ae-864f-4b0c19f838be""",
							    # few shot
							    """xclip-base-patch16-hmdb-2-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_hmdb_2.pth"""
							    ),
							    """xclip-base-patch16-hmdb-4-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_hmdb_4.pth"""
							    ),
							    """xclip-base-patch16-hmdb-8-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_hmdb_8.pth"""
							    ),
							    """xclip-base-patch16-hmdb-16-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_hmdb_16.pth"""
							    ),
							    """xclip-base-patch16-ucf-2-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_ucf_2.pth"""
							    ),
							    """xclip-base-patch16-ucf-4-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_ucf_4.pth"""
							    ),
							    """xclip-base-patch16-ucf-8-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_ucf_8.pth"""
							    ),
							    """xclip-base-patch16-ucf-16-shot""": (
							        """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/few_ucf_16.pth"""
							    ),
							    # zero shot
							    """xclip-base-patch16-zero-shot""": """https://github.com/nbl97/X-CLIP_Model_Zoo/releases/download/v1.0/zero.pth""",
							}

							lowerCamelCase_					=       model_to_url[model_name]
							lowerCamelCase_					=       8
							if "16-frames" in model_name:
														lowerCamelCase_					=       1_6
							elif "shot" in model_name:
														lowerCamelCase_					=       3_2

							lowerCamelCase_					=       get_xclip_config(UpperCAmelCase__      ,					UpperCAmelCase__							)
							lowerCamelCase_					=       XCLIPModel(UpperCAmelCase__							)
							model.eval()

							if "drive" in checkpoint_url:
														lowerCamelCase_					=       """pytorch_model.bin"""
														gdown.cached_download(UpperCAmelCase__      ,					UpperCAmelCase__      ,					quiet=UpperCAmelCase__							)
														lowerCamelCase_					=       torch.load(UpperCAmelCase__      ,					map_location="""cpu"""							)["""model"""]
							else:
														lowerCamelCase_					=       torch.hub.load_state_dict_from_url(UpperCAmelCase__							)["""model"""]

							lowerCamelCase_					=       convert_state_dict(UpperCAmelCase__      ,					UpperCAmelCase__							)

							lowerCamelCase_					=       XCLIPModel(UpperCAmelCase__							)
							lowerCamelCase_	, lowerCamelCase_					=       model.load_state_dict(UpperCAmelCase__      ,					strict=UpperCAmelCase__							)
							assert missing_keys == ["text_model.embeddings.position_ids", "vision_model.embeddings.position_ids"]
							model.eval()

							lowerCamelCase_					=       3_3_6 if model_name == """xclip-large-patch14-16-frames""" else 2_2_4
							lowerCamelCase_					=       VideoMAEImageProcessor(size=UpperCAmelCase__							)
							lowerCamelCase_					=       CLIPTokenizer.from_pretrained("""openai/clip-vit-base-patch32"""							)
							lowerCamelCase_					=       CLIPTokenizerFast.from_pretrained("""openai/clip-vit-base-patch32"""							)
							lowerCamelCase_					=       XCLIPProcessor(image_processor=UpperCAmelCase__      ,					tokenizer=UpperCAmelCase__							)

							lowerCamelCase_					=       prepare_video(UpperCAmelCase__							)
							lowerCamelCase_					=       processor(
							    text=["""playing sports""", """eating spaghetti""", """go shopping"""]      ,					videos=UpperCAmelCase__      ,					return_tensors="""pt"""      ,					padding=UpperCAmelCase__							)

							print("""Shape of pixel values:"""      ,					inputs.pixel_values.shape							)

							with torch.no_grad():
														lowerCamelCase_					=       model(**UpperCAmelCase__							)

							# Verify outputs
							lowerCamelCase_					=       outputs.logits_per_video
							lowerCamelCase_					=       logits_per_video.softmax(dim=1							)
							print("""Probs:"""      ,					UpperCAmelCase__							)
							# kinetics-400
							if model_name == "xclip-base-patch32":
														lowerCamelCase_					=       torch.tensor([[0.0_0_1_9, 0.9_9_5_1, 0.0_0_3_0]]							)
							elif model_name == "xclip-base-patch32-16-frames":
														lowerCamelCase_					=       torch.tensor([[7.0_999e-04, 9.9_883e-01, 4.5_580e-04]]							)
							elif model_name == "xclip-base-patch16":
														lowerCamelCase_					=       torch.tensor([[0.0_0_8_3, 0.9_6_8_1, 0.0_2_3_6]]							)
							elif model_name == "xclip-base-patch16-16-frames":
														lowerCamelCase_					=       torch.tensor([[7.6_937e-04, 9.9_728e-01, 1.9_473e-03]]							)
							elif model_name == "xclip-large-patch14":
														lowerCamelCase_					=       torch.tensor([[0.0_0_6_2, 0.9_8_6_4, 0.0_0_7_5]]							)
							elif model_name == "xclip-large-patch14-16-frames":
														lowerCamelCase_					=       torch.tensor([[3.3_877e-04, 9.9_937e-01, 2.8_888e-04]]							)
							# kinetics-600
							elif model_name == "xclip-base-patch16-kinetics-600":
														lowerCamelCase_					=       torch.tensor([[0.0_5_5_5, 0.8_9_1_4, 0.0_5_3_1]]							)
							elif model_name == "xclip-base-patch16-kinetics-600-16-frames":
														lowerCamelCase_					=       torch.tensor([[3.8_554e-04, 9.9_929e-01, 3.2_754e-04]]							)
							elif model_name == "xclip-large-patch14-kinetics-600":
														lowerCamelCase_					=       torch.tensor([[0.0_0_3_6, 0.9_9_2_0, 0.0_0_4_5]]							)
							# few shot
							elif model_name == "xclip-base-patch16-hmdb-2-shot":
														lowerCamelCase_					=       torch.tensor([[7.1_890e-06, 9.9_994e-01, 5.6_559e-05]]							)
							elif model_name == "xclip-base-patch16-hmdb-4-shot":
														lowerCamelCase_					=       torch.tensor([[1.0_320e-05, 9.9_993e-01, 6.2_435e-05]]							)
							elif model_name == "xclip-base-patch16-hmdb-8-shot":
														lowerCamelCase_					=       torch.tensor([[4.1_377e-06, 9.9_990e-01, 9.8_386e-05]]							)
							elif model_name == "xclip-base-patch16-hmdb-16-shot":
														lowerCamelCase_					=       torch.tensor([[4.1_347e-05, 9.9_962e-01, 3.3_411e-04]]							)
							elif model_name == "xclip-base-patch16-ucf-2-shot":
														lowerCamelCase_					=       torch.tensor([[8.5_857e-05, 9.9_928e-01, 6.3_291e-04]]							)
							elif model_name == "xclip-base-patch16-ucf-4-shot":
														lowerCamelCase_					=       torch.tensor([[8.5_857e-05, 9.9_928e-01, 6.3_291e-04]]							)
							elif model_name == "xclip-base-patch16-ucf-8-shot":
														lowerCamelCase_					=       torch.tensor([[0.0_0_2_7, 0.9_9_0_4, 0.0_0_7_0]]							)
							elif model_name == "xclip-base-patch16-ucf-16-shot":
														lowerCamelCase_					=       torch.tensor([[9.8_219e-04, 9.9_593e-01, 3.0_863e-03]]							)
							# zero shot
							elif model_name == "xclip-base-patch16-zero-shot":
														lowerCamelCase_					=       torch.tensor([[3.5_082e-04, 9.9_785e-01, 1.7_966e-03]]							)
							else:
														raise ValueError(F'''Model name {model_name} not supported'''							)
							assert torch.allclose(UpperCAmelCase__      ,					UpperCAmelCase__      ,					atol=1e-3							)
							print("""Looks ok!"""							)

							if pytorch_dump_folder_path is not None:
														print(F'''Saving model {model_name} to {pytorch_dump_folder_path}'''							)
														model.save_pretrained(UpperCAmelCase__							)

							if push_to_hub:
														print("""Pushing model, processor and slow tokenizer files to the hub..."""							)
														model.push_to_hub(UpperCAmelCase__      ,					organization="""nielsr"""							)
														processor.push_to_hub(UpperCAmelCase__      ,					organization="""nielsr"""							)
														slow_tokenizer.push_to_hub(UpperCAmelCase__      ,					organization="""nielsr"""							)


if __name__ == "__main__":
		lowercase   =	argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    '''--model_name''',
		    default='''xclip-base-patch32''',
		    type=str,
		    help='''Name of the model.''',
		)
		parser.add_argument(
		    '''--pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model directory.'''
		)
		parser.add_argument(
		    '''--push_to_hub''', action='''store_true''', help='''Whether or not to push the converted model to the 🤗 hub.'''
		)

		lowercase   =	parser.parse_args()
		convert_xclip_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)







import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


lowercase   =	{
    '''<''': operator.lt,
    '''<=''': operator.le,
    '''==''': operator.eq,
    '''!=''': operator.ne,
    '''>=''': operator.ge,
    '''>''': operator.gt,
}



def   __lowerCAmelCase    (				UpperCAmelCase__					:   Tuple      ,					UpperCAmelCase__					:   int      ,					UpperCAmelCase__					:   Optional[int]      ,					UpperCAmelCase__					:   Optional[int]      ,					UpperCAmelCase__					:   Optional[int]      ,					UpperCAmelCase__					:   int							)	->     Union[str, Any]:
							if got_ver is None or want_ver is None:
														raise ValueError(
														    F'''Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider'''
														    F''' reinstalling {pkg}.'''							)
							if not ops[op](version.parse(UpperCAmelCase__							)      ,					version.parse(UpperCAmelCase__							)							):
														raise ImportError(
														    F'''{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}'''							)



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str      ,					UpperCAmelCase__					:   Optional[str] = None							)	->     None:
							lowerCamelCase_					=       F'''\n{hint}''' if hint is not None else """"""

							# non-versioned check
							if re.match(R"""^[\w_\-\d]+$"""      ,					UpperCAmelCase__							):
														lowerCamelCase_	, lowerCamelCase_	, lowerCamelCase_					=       requirement, None, None
							else:
														lowerCamelCase_					=       re.findall(R"""^([^!=<>\s]+)([\s!=<>]{1,2}.+)"""      ,					UpperCAmelCase__							)
														if not match:
																					raise ValueError(
																					    """requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but"""
																					    F''' got {requirement}'''							)
														lowerCamelCase_	, lowerCamelCase_					=       match[0]
														lowerCamelCase_					=       want_full.split(""","""							)  # there could be multiple requirements
														lowerCamelCase_					=       {}
														for w in want_range:
																					lowerCamelCase_					=       re.findall(R"""^([\s!=<>]{1,2})(.+)"""      ,					UpperCAmelCase__							)
																					if not match:
																												raise ValueError(
																												    """requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,"""
																												    F''' but got {requirement}'''							)
																					lowerCamelCase_	, lowerCamelCase_					=       match[0]
																					lowerCamelCase_					=       want_ver
																					if op not in ops:
																												raise ValueError(F'''{requirement}: need one of {list(ops.keys()							)}, but got {op}'''							)

    # special case
							if pkg == "python":
														lowerCamelCase_					=       """.""".join([str(UpperCAmelCase__							) for x in sys.version_info[:3]]							)
														for op, want_ver in wanted.items():
																					_compare_versions(UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__							)
														return

							# check if any version is installed
							try:
														lowerCamelCase_					=       importlib.metadata.version(UpperCAmelCase__							)
							except importlib.metadata.PackageNotFoundError:
														raise importlib.metadata.PackageNotFoundError(
														    F'''The \'{requirement}\' distribution was not found and is required by this application. {hint}'''							)

							# check that the right version is installed if version number or a range was provided
							if want_ver is not None:
														for op, want_ver in wanted.items():
																					_compare_versions(UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__      ,					UpperCAmelCase__							)



def   __lowerCAmelCase    (				UpperCAmelCase__					:   List[str]							)	->     Dict:
							lowerCamelCase_					=       """Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main"""
							return require_version(UpperCAmelCase__      ,					UpperCAmelCase__							)





