



"""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				(       lowercase_		,     lowercase_						):
						UpperCAmelCase					=			XCLIPTextConfig()

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

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

												UpperCAmelCase					=			1024
												UpperCAmelCase					=			4096
												UpperCAmelCase					=			16
												UpperCAmelCase					=			24
												UpperCAmelCase					=			768
												UpperCAmelCase					=			3072

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

						UpperCAmelCase					=			XCLIPConfig.from_text_vision_configs(lowercase_		,     lowercase_						)

						if "large" in model_name:
												UpperCAmelCase					=			768

						return config

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

						return name

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_						):
						for key in orig_state_dict.copy().keys():
												UpperCAmelCase					=			orig_state_dict.pop(lowercase_						)

												if "attn.in_proj" in key:
																		UpperCAmelCase					=			key.split('.'						)
																		if key.startswith('visual'						):
																								UpperCAmelCase					=			key_split[3]
																								UpperCAmelCase					=			config.vision_config.hidden_size
																								if "message_attn" in key:
																														if "weight" in key:
																																				UpperCAmelCase					=			val[
																																				    :dim, :
																																				]
																																				UpperCAmelCase					=			val[
																																				    dim : dim * 2, :
																																				]
																																				UpperCAmelCase					=			val[
																																				    -dim:, :
																																				]
																														else:
																																				UpperCAmelCase					=			val[
																																				    :dim
																																				]
																																				UpperCAmelCase					=			val[
																																				    dim : dim * 2
																																				]
																																				UpperCAmelCase					=			val[
																																				    -dim:
																																				]
																								else:
																														if "weight" in key:
																																				UpperCAmelCase					=			val[
																																				    :dim, :
																																				]
																																				UpperCAmelCase					=			val[
																																				    dim : dim * 2, :
																																				]
																																				UpperCAmelCase					=			val[
																																				    -dim:, :
																																				]
																														else:
																																				UpperCAmelCase					=			val[:dim]
																																				UpperCAmelCase					=			val[
																																				    dim : dim * 2
																																				]
																																				UpperCAmelCase					=			val[-dim:]
																		elif key.startswith('mit'						):
																								UpperCAmelCase					=			key_split[2]
																								UpperCAmelCase					=			config.vision_config.mit_hidden_size
																								if "weight" in key:
																														UpperCAmelCase					=			val[:dim, :]
																														UpperCAmelCase					=			val[dim : dim * 2, :]
																														UpperCAmelCase					=			val[-dim:, :]
																								else:
																														UpperCAmelCase					=			val[:dim]
																														UpperCAmelCase					=			val[dim : dim * 2]
																														UpperCAmelCase					=			val[-dim:]
																		else:
																								UpperCAmelCase					=			key_split[2]
																								UpperCAmelCase					=			config.text_config.hidden_size
																								if "weight" in key:
																														UpperCAmelCase					=			val[:dim, :]
																														UpperCAmelCase					=			val[
																														    dim : dim * 2, :
																														]
																														UpperCAmelCase					=			val[-dim:, :]
																								else:
																														UpperCAmelCase					=			val[:dim]
																														UpperCAmelCase					=			val[
																														    dim : dim * 2
																														]
																														UpperCAmelCase					=			val[-dim:]
												else:
																		UpperCAmelCase					=			rename_key(lowercase_						)
																		if new_key_name in ["visual_projection.weight", "text_projection.weight"]:
																								UpperCAmelCase					=			val.T
																		UpperCAmelCase					=			val

						return orig_state_dict

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

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_=None		,     lowercase_=False						):
						UpperCAmelCase					=			{
						    # 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',
						}

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

						UpperCAmelCase					=			get_xclip_config(lowercase_		,     lowercase_						)
						UpperCAmelCase					=			XCLIPModel(lowercase_						)
						model.eval()

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

						UpperCAmelCase					=			convert_state_dict(lowercase_		,     lowercase_						)

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

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

						UpperCAmelCase					=			prepare_video(lowercase_						)
						UpperCAmelCase					=			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():
												UpperCAmelCase					=			model(**lowercase_						)

						# Verify outputs
						UpperCAmelCase					=			outputs.logits_per_video
						UpperCAmelCase					=			logits_per_video.softmax(dim=1						)
						print('Probs:'		,     lowercase_						)
						# kinetics-400
						if model_name == "xclip-base-patch32":
												UpperCAmelCase					=			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":
												UpperCAmelCase					=			torch.tensor([[7.09_99e-04, 9.98_83e-01, 4.55_80e-04]]						)
						elif model_name == "xclip-base-patch16":
												UpperCAmelCase					=			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":
												UpperCAmelCase					=			torch.tensor([[7.69_37e-04, 9.97_28e-01, 1.94_73e-03]]						)
						elif model_name == "xclip-large-patch14":
												UpperCAmelCase					=			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":
												UpperCAmelCase					=			torch.tensor([[3.38_77e-04, 9.99_37e-01, 2.88_88e-04]]						)
						# kinetics-600
						elif model_name == "xclip-base-patch16-kinetics-600":
												UpperCAmelCase					=			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":
												UpperCAmelCase					=			torch.tensor([[3.85_54e-04, 9.99_29e-01, 3.27_54e-04]]						)
						elif model_name == "xclip-large-patch14-kinetics-600":
												UpperCAmelCase					=			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":
												UpperCAmelCase					=			torch.tensor([[7.18_90e-06, 9.99_94e-01, 5.65_59e-05]]						)
						elif model_name == "xclip-base-patch16-hmdb-4-shot":
												UpperCAmelCase					=			torch.tensor([[1.03_20e-05, 9.99_93e-01, 6.24_35e-05]]						)
						elif model_name == "xclip-base-patch16-hmdb-8-shot":
												UpperCAmelCase					=			torch.tensor([[4.13_77e-06, 9.99_90e-01, 9.83_86e-05]]						)
						elif model_name == "xclip-base-patch16-hmdb-16-shot":
												UpperCAmelCase					=			torch.tensor([[4.13_47e-05, 9.99_62e-01, 3.34_11e-04]]						)
						elif model_name == "xclip-base-patch16-ucf-2-shot":
												UpperCAmelCase					=			torch.tensor([[8.58_57e-05, 9.99_28e-01, 6.32_91e-04]]						)
						elif model_name == "xclip-base-patch16-ucf-4-shot":
												UpperCAmelCase					=			torch.tensor([[8.58_57e-05, 9.99_28e-01, 6.32_91e-04]]						)
						elif model_name == "xclip-base-patch16-ucf-8-shot":
												UpperCAmelCase					=			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":
												UpperCAmelCase					=			torch.tensor([[9.82_19e-04, 9.95_93e-01, 3.08_63e-03]]						)
						# zero shot
						elif model_name == "xclip-base-patch16-zero-shot":
												UpperCAmelCase					=			torch.tensor([[3.50_82e-04, 9.97_85e-01, 1.79_66e-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__":
				snake_case_    					=	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."""
				)

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










"""simple docstring"""


import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

snake_case_    					=	3

def 			_lowerCAmelCase				(       lowercase_						):
						print('Generating primitive root of p'						)
						while True:
												UpperCAmelCase					=			random.randrange(3		,     lowercase_						)
												if pow(lowercase_		,     2		,     lowercase_						) == 1:
																		continue
												if pow(lowercase_		,     lowercase_		,     lowercase_						) == 1:
																		continue
												return g

def 			_lowerCAmelCase				(       lowercase_						):
						print('Generating prime p...'						)
						UpperCAmelCase					=			rabin_miller.generate_large_prime(lowercase_						)  # select large prime number.
						UpperCAmelCase					=			primitive_root(lowercase_						)  # one primitive root on modulo p.
						UpperCAmelCase					=			random.randrange(3		,     lowercase_						)  # private_key -> have to be greater than 2 for safety.
						UpperCAmelCase					=			cryptomath.find_mod_inverse(pow(lowercase_		,     lowercase_		,     lowercase_						)		,     lowercase_						)

						UpperCAmelCase					=			(key_size, e_a, e_a, p)
						UpperCAmelCase					=			(key_size, d)

						return public_key, private_key

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_						):
						if os.path.exists(F"""{name}_pubkey.txt"""						) or os.path.exists(F"""{name}_privkey.txt"""						):
												print('\nWARNING:'						)
												print(
												    F"""\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"""
												    'Use a different name or delete these files and re-run this program.'						)
												sys.exit()

						UpperCAmelCase				,   UpperCAmelCase					=			generate_key(lowercase_						)
						print(F"""\nWriting public key to file {name}_pubkey.txt..."""						)
						with open(F"""{name}_pubkey.txt"""		,     'w'						) as fo:
												fo.write(F"""{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}"""						)

						print(F"""Writing private key to file {name}_privkey.txt..."""						)
						with open(F"""{name}_privkey.txt"""		,     'w'						) as fo:
												fo.write(F"""{private_key[0]},{private_key[1]}"""						)

def 			_lowerCAmelCase				(       ):
						print('Making key files...'						)
						make_key_files('elgamal'		,     2048						)
						print('Key files generation successful'						)


if __name__ == "__main__":
				main()





