
'''simple docstring'''





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__				:      List[Any]			,				UpperCAmelCase__				:      Union[str, Any]       )  ->    Union[str, Any]:
							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=lowercase_			,				num_frames=lowercase_       )

							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(lowercase_			,				lowercase_       )

							if "large" in model_name:
														lowerCamelCase_							  =					7_6_8

							return config



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Dict       )  ->    Dict:
							# 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__				:      str			,				UpperCAmelCase__				:      int       )  ->    Optional[Any]:
							for key in orig_state_dict.copy().keys():
														lowerCamelCase_							  =					orig_state_dict.pop(lowercase_       )

														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(lowercase_       )
																					if new_key_name in ["visual_projection.weight", "text_projection.weight"]:
																												lowerCamelCase_							  =					val.T
																					lowerCamelCase_							  =					val

							return orig_state_dict



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Optional[int]       )  ->    List[str]:
							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=lowercase_			,				repo_type="""dataset"""			,				)
							lowerCamelCase_							  =					np.load(lowercase_       )
							return list(lowercase_       )



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Union[str, Any]			,				UpperCAmelCase__				:      Dict=None			,				UpperCAmelCase__				:      Optional[Any]=False       )  ->    Union[str, Any]:
							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(lowercase_			,				lowercase_       )
							lowerCamelCase_							  =					XCLIPModel(lowercase_       )
							model.eval()

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

							lowerCamelCase_							  =					convert_state_dict(lowercase_			,				lowercase_       )

							lowerCamelCase_							  =					XCLIPModel(lowercase_       )
							lowerCamelCase_							  =					model.load_state_dict(lowercase_			,				strict=lowercase_       )
							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=lowercase_       )
							lowerCamelCase_							  =					CLIPTokenizer.from_pretrained("""openai/clip-vit-base-patch32"""       )
							lowerCamelCase_							  =					CLIPTokenizerFast.from_pretrained("""openai/clip-vit-base-patch32"""       )
							lowerCamelCase_							  =					XCLIPProcessor(image_processor=lowercase_			,				tokenizer=lowercase_       )

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

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

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

							# Verify outputs
							lowerCamelCase_							  =					outputs.logits_per_video
							lowerCamelCase_							  =					logits_per_video.softmax(dim=1       )
							print("""Probs:"""			,				lowercase_       )
							# 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(lowercase_			,				lowercase_			,				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(lowercase_       )

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







from ..utils import DummyObject, requires_backends





class       __A(				metaclass=UpperCAmelCase       ):
					SCREAMING_SNAKE_CASE			    =    ['''torch''', '''scipy''']

					def __init__(	self					:     Any   ,					*__UpperCamelCase					:     str   ,					**__UpperCamelCase					:     Any   ):
												requires_backends(self   ,					["""torch""", """scipy"""]   )

					@classmethod
					def    lowercase__      (	cls					:     Dict   ,					*__UpperCamelCase					:     str   ,					**__UpperCamelCase					:     Dict   ):
												requires_backends(cls   ,					["""torch""", """scipy"""]   )



					@classmethod
					def    lowercase__      (	cls					:     str   ,					*__UpperCamelCase					:     Optional[int]   ,					**__UpperCamelCase					:     Optional[int]   ):
												requires_backends(cls   ,					["""torch""", """scipy"""]   )





