
import argparse
from argparse import Namespace

import torch
from torch import nn

from transformers import XGLMConfig, XGLMForCausalLM


def      UpperCamelCase   (       __lowerCamelCase	:					Union[str, Any]       ):
       snake_case			:  int     							= [
           "decoder.version",
           "decoder.output_projection.weight",
           "_float_tensor",
           "decoder.embed_positions._float_tensor",
       ]
       for k in ignore_keys:
              state_dict.pop(__lowerCamelCase							,   __lowerCamelCase       )


def      UpperCamelCase   (       __lowerCamelCase	:					str       ):
       snake_case							,   snake_case			:  List[str]     							= emb.weight.shape
       snake_case			:  List[str]     							= nn.Linear(__lowerCamelCase							,   __lowerCamelCase							,   bias=__lowerCamelCase       )
       snake_case			:  Optional[int]     							= emb.weight.data
       return lin_layer


def      UpperCamelCase   (       __lowerCamelCase	:					Optional[Any]       ):
       snake_case			:  Optional[Any]     							= torch.load(__lowerCamelCase							,   map_location="cpu"       )
       snake_case			:  Dict     							= Namespace(**checkpoint["cfg"]["model"]       )
       snake_case			:  Tuple     							= checkpoint["model"]
       remove_ignore_keys_(__lowerCamelCase       )
       snake_case			:  Optional[int]     							= state_dict["decoder.embed_tokens.weight"].shape[0]

       snake_case			:  List[Any]     							= {key.replace("decoder"							,   "model"       ): val for key, val in state_dict.items()}

       snake_case			:  int     							= XGLMConfig(
           vocab_size=__lowerCamelCase							,   max_position_embeddings=args.max_target_positions							,   num_layers=args.decoder_layers							,   attention_heads=args.decoder_attention_heads							,   ffn_dim=args.decoder_ffn_embed_dim							,   d_model=args.decoder_embed_dim							,   layerdrop=args.decoder_layerdrop							,   dropout=args.dropout							,   attention_dropout=args.attention_dropout							,   activation_dropout=args.activation_dropout							,   activation_function="gelu"							,   scale_embedding=not args.no_scale_embedding							,   tie_word_embeddings=args.share_decoder_input_output_embed							,   )

       snake_case			:  Union[str, Any]     							= XGLMForCausalLM(__lowerCamelCase       )
       snake_case			:  Any     							= model.load_state_dict(__lowerCamelCase							,   strict=__lowerCamelCase       )
       print(__lowerCamelCase       )
       snake_case			:  Optional[Any]     							= make_linear_from_emb(model.model.embed_tokens       )

       return model


if __name__ == "__main__":
   __lowerCamelCase				=			argparse.ArgumentParser()
   # Required parameters
   parser.add_argument("""fairseq_path""", type=str, help="""path to a model.pt on local filesystem.""")
   parser.add_argument("""pytorch_dump_folder_path""", default=None, type=str, help="""Path to the output PyTorch model.""")
   __lowerCamelCase				=			parser.parse_args()
   __lowerCamelCase				=			convert_fairseq_xglm_checkpoint_from_disk(args.fairseq_path)
   model.save_pretrained(args.pytorch_dump_folder_path)







import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation


def      UpperCamelCase   (       __lowerCamelCase	:					int = 8       ):
       snake_case			:  int     							= ascii_letters + digits + punctuation
       return "".join(secrets.choice(__lowerCamelCase       ) for _ in range(__lowerCamelCase       )       )


def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					int       ):
       # Password Generator = full boot with random_number, random_letters, and
       # random_character FUNCTIONS
       # Put your code here...
       i -= len(__lowerCamelCase       )
       snake_case			:  Any     							= i // 3
       snake_case			:  Optional[int]     							= i % 3
       # chars = chars_incl + random_letters(ascii_letters, i / 3 + remainder) +
       #     random_number(digits, i / 3) + random_characters(punctuation, i / 3)
       snake_case			:  Tuple     							= (
           chars_incl
           + random(__lowerCamelCase							,   quotient + remainder       )
           + random(__lowerCamelCase							,   __lowerCamelCase       )
           + random(__lowerCamelCase							,   __lowerCamelCase       )
       )
       snake_case			:  Optional[Any]     							= list(__lowerCamelCase       )
       shuffle(__lowerCamelCase       )
       return "".join(__lowerCamelCase       )

       # random is a generalised function for letters, characters and numbers


def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					int       ):
       return "".join(secrets.choice(__lowerCamelCase       ) for _ in range(__lowerCamelCase       )       )


def      UpperCamelCase   (       __lowerCamelCase	:					List[str]							,   __lowerCamelCase	:					str       ):
       pass  # Put your code here...


def      UpperCamelCase   (       __lowerCamelCase	:					Optional[int]							,   __lowerCamelCase	:					List[str]       ):
       pass  # Put your code here...


def      UpperCamelCase   (       __lowerCamelCase	:					Any							,   __lowerCamelCase	:					List[Any]       ):
       pass  # Put your code here...


def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					int = 8       ):

       if len(__lowerCamelCase       ) < min_length:
              # Your Password must be at least 8 characters long
              return False

       snake_case			:  Dict     							= any(char in ascii_uppercase for char in password       )
       snake_case			:  Optional[int]     							= any(char in ascii_lowercase for char in password       )
       snake_case			:  str     							= any(char in digits for char in password       )
       snake_case			:  str     							= any(char in punctuation for char in password       )

       return upper and lower and num and spec_char
       # Passwords should contain UPPERCASE, lowerase
       # numbers, and special characters


def      UpperCamelCase   (       ):
       snake_case			:  int     							= int(input("Please indicate the max length of your password: "       ).strip()       )
       snake_case			:  Union[str, Any]     							= input(
           "Please indicate the characters that must be in your password: "       ).strip()
       print("Password generated:"							,   password_generator(__lowerCamelCase       )       )
       print(
           "Alternative Password generated:"							,   alternative_password_generator(__lowerCamelCase							,   __lowerCamelCase       )							,   )
       print("[If you are thinking of using this passsword, You better save it.]"       )


if __name__ == "__main__":
   main()





