


import os
import sys

from . import rsa_key_generator as rkg

snake_case_  :     Union[str, Any]							  =							1_28
snake_case_  :     List[str]							  =							2_56







def   lowerCamelCase(				a__		,a__ = DEFAULT_BLOCK_SIZE):
    _SCREAMING_SNAKE_CASE     					=message.encode('''ascii''')

    _SCREAMING_SNAKE_CASE     					=[]
    for block_start in range(0		,len(a__)		,a__):
        _SCREAMING_SNAKE_CASE     					=0
        for i in range(a__		,min(block_start + block_size		,len(a__))):
            block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
        block_ints.append(a__)
    return block_ints







def   lowerCamelCase(				a__		,a__		,a__ = DEFAULT_BLOCK_SIZE):
    _SCREAMING_SNAKE_CASE     					=[]
    for block_int in block_ints:
        _SCREAMING_SNAKE_CASE     					=[]
        for i in range(block_size - 1		,-1		,-1):
            if len(a__) + i < message_length:
                _SCREAMING_SNAKE_CASE     					=block_int // (BYTE_SIZE**i)
                _SCREAMING_SNAKE_CASE     					=block_int % (BYTE_SIZE**i)
                block_message.insert(0		,chr(a__))
        message.extend(a__)
    return "".join(a__)







def   lowerCamelCase(				a__		,a__		,a__ = DEFAULT_BLOCK_SIZE):
    _SCREAMING_SNAKE_CASE     					=[]
    _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=key

    for block in get_blocks_from_text(a__		,a__):
        encrypted_blocks.append(pow(a__		,a__		,a__))
    return encrypted_blocks







def   lowerCamelCase(				a__		,a__		,a__		,a__ = DEFAULT_BLOCK_SIZE		,):
    _SCREAMING_SNAKE_CASE     					=[]
    _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=key
    for block in encrypted_blocks:
        decrypted_blocks.append(pow(a__		,a__		,a__))
    return get_text_from_blocks(a__		,a__		,a__)







def   lowerCamelCase(				a__):



    with open(a__) as fo:
        _SCREAMING_SNAKE_CASE     					=fo.read()
    _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=content.split(''',''')
    return (int(a__), int(a__), int(a__))







def   lowerCamelCase(				a__		,a__		,a__		,a__ = DEFAULT_BLOCK_SIZE		,):
    _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=read_key_file(a__)
    if key_size < block_size * 8:
        sys.exit(
            '''ERROR: Block size is {} bits and key size is {} bits. The RSA cipher '''
            '''requires the block size to be equal to or greater than the key size. '''
            '''Either decrease the block size or use different keys.'''.format(
                block_size * 8		,a__))

    _SCREAMING_SNAKE_CASE     					=[str(a__) for i in encrypt_message(a__		,(n, e)		,a__)]

    _SCREAMING_SNAKE_CASE     					=''','''.join(a__)
    _SCREAMING_SNAKE_CASE     					=f"{len(a__)}_{block_size}_{encrypted_content}"
    with open(a__		,'''w''') as fo:
        fo.write(a__)
    return encrypted_content







def   lowerCamelCase(				a__		,a__):
    _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=read_key_file(a__)
    with open(a__) as fo:
        _SCREAMING_SNAKE_CASE     					=fo.read()
    _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=content.split('''_''')
    _SCREAMING_SNAKE_CASE     					=int(a__)
    _SCREAMING_SNAKE_CASE     					=int(a__)

    if key_size < block_size * 8:
        sys.exit(
            '''ERROR: Block size is {} bits and key size is {} bits. The RSA cipher '''
            '''requires the block size to be equal to or greater than the key size. '''
            '''Did you specify the correct key file and encrypted file?'''.format(
                block_size * 8		,a__))

    _SCREAMING_SNAKE_CASE     					=[]
    for block in encrypted_message.split(''','''):
        encrypted_blocks.append(int(a__))

    return decrypt_message(a__		,a__		,(n, d)		,a__)







def   lowerCamelCase(				):
    _SCREAMING_SNAKE_CASE     					='''encrypted_file.txt'''
    _SCREAMING_SNAKE_CASE     					=input(R'''Encrypt\Decrypt [e\d]: ''')

    if response.lower().startswith('''e'''):
        _SCREAMING_SNAKE_CASE     					='''encrypt'''
    elif response.lower().startswith('''d'''):
        _SCREAMING_SNAKE_CASE     					='''decrypt'''

    if mode == "encrypt":
        if not os.path.exists('''rsa_pubkey.txt'''):
            rkg.make_key_files('''rsa'''		,1024)

        _SCREAMING_SNAKE_CASE     					=input('''\nEnter message: ''')
        _SCREAMING_SNAKE_CASE     					='''rsa_pubkey.txt'''
        print(f"Encrypting and writing to {filename}...")
        _SCREAMING_SNAKE_CASE     					=encrypt_and_write_to_file(a__		,a__		,a__)

        print('''\nEncrypted text:''')
        print(a__)

    elif mode == "decrypt":
        _SCREAMING_SNAKE_CASE     					='''rsa_privkey.txt'''
        print(f"Reading from {filename} and decrypting...")
        _SCREAMING_SNAKE_CASE     					=read_from_file_and_decrypt(a__		,a__)
        print('''writing decryption to rsa_decryption.txt...''')
        with open('''rsa_decryption.txt'''		,'''w''') as dec:
            dec.write(a__)

        print('''\nDecryption:''')
        print(a__)


if __name__ == "__main__":
       main()



import argparse

import torch

from transformers import ChineseCLIPConfig, ChineseCLIPModel







def   lowerCamelCase(				a__		,a__		,a__):
				_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=pt_weights[f"{prefix}.in_proj_weight"].chunk(3		,dim=0)
				_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE     					=pt_weights[f"{prefix}.in_proj_bias"].chunk(3		,dim=0)

				_SCREAMING_SNAKE_CASE     					=pt_weights[f"{prefix}.out_proj.weight"]
				_SCREAMING_SNAKE_CASE     					=pt_weights[f"{prefix}.out_proj.bias"]

				_SCREAMING_SNAKE_CASE     					=q_proj
				_SCREAMING_SNAKE_CASE     					=q_proj_bias

				_SCREAMING_SNAKE_CASE     					=k_proj
				_SCREAMING_SNAKE_CASE     					=k_proj_bias

				_SCREAMING_SNAKE_CASE     					=v_proj
				_SCREAMING_SNAKE_CASE     					=v_proj_bias

				_SCREAMING_SNAKE_CASE     					=out_proj_weights
				_SCREAMING_SNAKE_CASE     					=out_proj_bias







def   lowerCamelCase(				a__		,a__		,a__):
				copy_linear(hf_mlp.fca		,a__		,f"{prefix}.c_fc")
				copy_linear(hf_mlp.fca		,a__		,f"{prefix}.c_proj")







def   lowerCamelCase(				a__		,a__		,a__):
				_SCREAMING_SNAKE_CASE     					=pt_weights[f"{prefix}.weight"].data
				_SCREAMING_SNAKE_CASE     					=pt_weights[f"{prefix}.bias"].data







def   lowerCamelCase(				a__		,a__		,a__):
				# copy layer norms
				copy_linear(hf_layer.layer_norma		,a__		,f"{prefix}.ln_1")
				copy_linear(hf_layer.layer_norma		,a__		,f"{prefix}.ln_2")

				# copy MLP
				copy_mlp(hf_layer.mlp		,a__		,f"{prefix}.mlp")

				# copy attn
				copy_attn_layer(hf_layer.self_attn		,a__		,f"{prefix}.attn")







def   lowerCamelCase(				a__		,a__		,a__):
				for layer_id, hf_layer in enumerate(a__):
								copy_layer(a__		,a__		,f"{prefix}.{layer_id}")







def   lowerCamelCase(				a__		,a__):
				# copy projection
				_SCREAMING_SNAKE_CASE     					=pt_weights['''text_projection'''].data.T

				# copy text encoder
				for name, param in hf_model.text_model.named_parameters():
								_SCREAMING_SNAKE_CASE     					=pt_weights[f"bert.{name}"].data







def   lowerCamelCase(				a__		,a__):
				# copy projection
				_SCREAMING_SNAKE_CASE     					=pt_weights['''visual.proj'''].data.T

				# copy layer norms
				copy_linear(hf_model.vision_model.pre_layrnorm		,a__		,'''visual.ln_pre''')
				copy_linear(hf_model.vision_model.post_layernorm		,a__		,'''visual.ln_post''')

				# copy embeddings
				_SCREAMING_SNAKE_CASE     					=pt_weights['''visual.conv1.weight'''].data
				_SCREAMING_SNAKE_CASE     					=pt_weights['''visual.class_embedding'''].data
				_SCREAMING_SNAKE_CASE     					=pt_weights['''visual.positional_embedding'''].data

				# copy encoder
				copy_layers(hf_model.vision_model.encoder.layers		,a__		,'''visual.transformer.resblocks''')







@torch.no_grad()
def   lowerCamelCase(				a__		,a__		,a__=None):
				assert config_path is not None, "Please specify the ChineseCLIP model config of the corresponding model size."
				_SCREAMING_SNAKE_CASE     					=ChineseCLIPConfig.from_pretrained(a__)

				_SCREAMING_SNAKE_CASE     					=ChineseCLIPModel(a__).eval()

				_SCREAMING_SNAKE_CASE     					=torch.load(a__		,map_location='''cpu''')['''state_dict''']
				_SCREAMING_SNAKE_CASE     					={(name[7:] if name.startswith('''module.''') else name): value for name, value in pt_weights.items()}

				copy_text_model_and_projection(a__		,a__)
				copy_vision_model_and_projection(a__		,a__)
				_SCREAMING_SNAKE_CASE     					=pt_weights['''logit_scale'''].data

				hf_model.save_pretrained(a__)


if __name__ == "__main__":
							snake_case_  :     Tuple							  =							argparse.ArgumentParser()
							parser.add_argument(
							    '''--pytorch_dump_folder_path''',
							    default=None,
							    type=str,
							    help='''Path to the output folder storing converted hf PyTorch model.''',
							)
							parser.add_argument(
							    '''--checkpoint_path''', default=None, type=str, help='''Path to original github format ChineseCLIP checkpoint.'''
							)
							parser.add_argument(
							    '''--config_path''', default=None, required=True, type=str, help='''Path to hf config.json of model to convert.'''
							)
							snake_case_  :     List[str]							  =							parser.parse_args()

							convert_chinese_clip_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path)
							print('''The conversion is finished!''')