





'''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 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = XCLIPTextConfig()

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

				if "large" in model_name:
								lowercase         = 768
								lowercase         = 3072
								lowercase         = 12

								lowercase         = 1024
								lowercase         = 4096
								lowercase         = 16
								lowercase         = 24
								lowercase         = 768
								lowercase         = 3072

				if model_name == "xclip-large-patch14-16-frames":
								lowercase         = 336

				lowercase         = XCLIPConfig.from_text_vision_configs(lowerCAmelCase_		,							lowerCAmelCase_							)

				if "large" in model_name:
								lowercase         = 768

				return config







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






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

				return name







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				for key in orig_state_dict.copy().keys():
								lowercase         = orig_state_dict.pop(lowerCAmelCase_							)

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

				return orig_state_dict







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				if num_frames == 8:
								lowercase         = "eating_spaghetti_8_frames.npy"
				elif num_frames == 16:
								lowercase         = "eating_spaghetti.npy"
				elif num_frames == 32:
								lowercase         = "eating_spaghetti_32_frames.npy"
				lowercase         = hf_hub_download(
				    repo_id="hf-internal-testing/spaghetti-video"		,							filename=lowerCAmelCase_		,							repo_type="dataset"		,							)
				lowercase         = np.load(lowerCAmelCase_							)
				return list(lowerCAmelCase_							)







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_=None		,							lowerCAmelCase_=False							):

				"""simple docstring"""






				lowercase         = {
				    # 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",
				}

				lowercase         = model_to_url[model_name]
				lowercase         = 8
				if "16-frames" in model_name:
								lowercase         = 16
				elif "shot" in model_name:
								lowercase         = 32

				lowercase         = get_xclip_config(lowerCAmelCase_		,							lowerCAmelCase_							)
				lowercase         = XCLIPModel(lowerCAmelCase_							)
				model.eval()

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

				lowercase         = convert_state_dict(lowerCAmelCase_		,							lowerCAmelCase_							)

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

				lowercase         = 336 if model_name == "xclip-large-patch14-16-frames" else 224
				lowercase         = VideoMAEImageProcessor(size=lowerCAmelCase_							)
				lowercase         = CLIPTokenizer.from_pretrained("openai/clip-vit-base-patch32"							)
				lowercase         = CLIPTokenizerFast.from_pretrained("openai/clip-vit-base-patch32"							)
				lowercase         = XCLIPProcessor(image_processor=lowerCAmelCase_		,							tokenizer=lowerCAmelCase_							)

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

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

				with torch.no_grad():
								lowercase         = model(**lowerCAmelCase_							)

				# Verify outputs
				lowercase         = outputs.logits_per_video
				lowercase         = logits_per_video.softmax(dim=1							)
				print("Probs:"		,							lowerCAmelCase_							)
				# kinetics-400
				if model_name == "xclip-base-patch32":
								lowercase         = torch.tensor([[0.00_19, 0.99_51, 0.00_30]]							)
				elif model_name == "xclip-base-patch32-16-frames":
								lowercase         = torch.tensor([[7.0_9_9_9E-0_4, 9.9_8_8_3E-0_1, 4.5_5_8_0E-0_4]]							)
				elif model_name == "xclip-base-patch16":
								lowercase         = torch.tensor([[0.00_83, 0.96_81, 0.02_36]]							)
				elif model_name == "xclip-base-patch16-16-frames":
								lowercase         = torch.tensor([[7.6_9_3_7E-0_4, 9.9_7_2_8E-0_1, 1.9_4_7_3E-0_3]]							)
				elif model_name == "xclip-large-patch14":
								lowercase         = torch.tensor([[0.00_62, 0.98_64, 0.00_75]]							)
				elif model_name == "xclip-large-patch14-16-frames":
								lowercase         = torch.tensor([[3.3_8_7_7E-0_4, 9.9_9_3_7E-0_1, 2.8_8_8_8E-0_4]]							)
				# kinetics-600
				elif model_name == "xclip-base-patch16-kinetics-600":
								lowercase         = torch.tensor([[0.05_55, 0.89_14, 0.05_31]]							)
				elif model_name == "xclip-base-patch16-kinetics-600-16-frames":
								lowercase         = torch.tensor([[3.8_5_5_4E-0_4, 9.9_9_2_9E-0_1, 3.2_7_5_4E-0_4]]							)
				elif model_name == "xclip-large-patch14-kinetics-600":
								lowercase         = torch.tensor([[0.00_36, 0.99_20, 0.00_45]]							)
				# few shot
				elif model_name == "xclip-base-patch16-hmdb-2-shot":
								lowercase         = torch.tensor([[7.1_8_9_0E-0_6, 9.9_9_9_4E-0_1, 5.6_5_5_9E-0_5]]							)
				elif model_name == "xclip-base-patch16-hmdb-4-shot":
								lowercase         = torch.tensor([[1.0_3_2_0E-0_5, 9.9_9_9_3E-0_1, 6.2_4_3_5E-0_5]]							)
				elif model_name == "xclip-base-patch16-hmdb-8-shot":
								lowercase         = torch.tensor([[4.1_3_7_7E-0_6, 9.9_9_9_0E-0_1, 9.8_3_8_6E-0_5]]							)
				elif model_name == "xclip-base-patch16-hmdb-16-shot":
								lowercase         = torch.tensor([[4.1_3_4_7E-0_5, 9.9_9_6_2E-0_1, 3.3_4_1_1E-0_4]]							)
				elif model_name == "xclip-base-patch16-ucf-2-shot":
								lowercase         = torch.tensor([[8.5_8_5_7E-0_5, 9.9_9_2_8E-0_1, 6.3_2_9_1E-0_4]]							)
				elif model_name == "xclip-base-patch16-ucf-4-shot":
								lowercase         = torch.tensor([[8.5_8_5_7E-0_5, 9.9_9_2_8E-0_1, 6.3_2_9_1E-0_4]]							)
				elif model_name == "xclip-base-patch16-ucf-8-shot":
								lowercase         = torch.tensor([[0.00_27, 0.99_04, 0.00_70]]							)
				elif model_name == "xclip-base-patch16-ucf-16-shot":
								lowercase         = torch.tensor([[9.8_2_1_9E-0_4, 9.9_5_9_3E-0_1, 3.0_8_6_3E-0_3]]							)
				# zero shot
				elif model_name == "xclip-base-patch16-zero-shot":
								lowercase         = torch.tensor([[3.5_0_8_2E-0_4, 9.9_7_8_5E-0_1, 1.7_9_6_6E-0_3]]							)
				else:
								raise ValueError(f'Model name {model_name} not supported'							)
				assert torch.allclose(lowerCAmelCase_		,							lowerCAmelCase_		,							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(lowerCAmelCase_							)

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


if __name__ == "__main__":
			__lowerCamelCase : Any											=			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."
			)

			__lowerCamelCase : Optional[Any]											=			parser.parse_args()
			convert_xclip_checkpoint(args.model_name, args.pytorch_dump_folder_path, args.push_to_hub)











'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


__lowerCamelCase : Union[str, Any]											=			logging.get_logger(__name__)

class       UpperCAmelCase (						_lowercase  ):




		def __init__(self      :	Tuple							,			*A__      :	Union[str, Any]							,			**A__      :	Optional[Any]				)					-> None:
						warnings.warn(
						    "The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
						    " use CLIPImageProcessor instead."							,			A__							,			)
						super().__init__(*A__							,			**A__				)




