



import argparse
from argparse import Namespace

import torch
from torch import nn

from transformers import XGLMConfig, XGLMForCausalLM



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			[
	    "decoder.version",
	    "decoder.output_projection.weight",
	    "_float_tensor",
	    "decoder.embed_positions._float_tensor",
	]
	for k in ignore_keys:
		state_dict.pop(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	__lowercase       ,    __lowercase		       =			emb.weight.shape
	__lowercase		       =			nn.Linear(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	bias=_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			emb.weight.data
	return lin_layer



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			torch.load(_SCREAMING_SNAKE_CASE  ,	map_location="cpu"   )
	__lowercase		       =			Namespace(**checkpoint["cfg"]["model"]   )
	__lowercase		       =			checkpoint["model"]
	remove_ignore_keys_(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			state_dict["decoder.embed_tokens.weight"].shape[0]

	__lowercase		       =			{key.replace("decoder"  ,	"model"   ): val for key, val in state_dict.items()}

	__lowercase		       =			XGLMConfig(
	    vocab_size=_SCREAMING_SNAKE_CASE  ,	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  ,	)

	__lowercase		       =			XGLMForCausalLM(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			model.load_state_dict(_SCREAMING_SNAKE_CASE  ,	strict=_SCREAMING_SNAKE_CASE   )
	print(_SCREAMING_SNAKE_CASE   )
	__lowercase		       =			make_linear_from_emb(model.model.embed_tokens   )

	return model


if __name__ == "__main__":
	snake_case__					:     List[Any]    		=   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.""")
	snake_case__					:     int    		=   parser.parse_args()
	snake_case__					:     str    		=   convert_fairseq_xglm_checkpoint_from_disk(args.fairseq_path)
	model.save_pretrained(args.pytorch_dump_folder_path)








import os
import sys
from contextlib import contextmanager


# Windows only
if os.name == "nt":
	import ctypes
	import msvcrt  # noqa

	class   _A   ( ctypes.Structure	):


							'''simple docstring'''





							_snake_case			:     Optional[Any]      							=      [("""size""", ctypes.c_int), ("""visible""", ctypes.c_byte)]



def    snake_case_				(    ):
	if os.name == "nt":
		__lowercase		       =			CursorInfo()
		__lowercase		       =			ctypes.windll.kernelaa.GetStdHandle(-1_1   )
		ctypes.windll.kernelaa.GetConsoleCursorInfo(_SCREAMING_SNAKE_CASE  ,	ctypes.byref(_SCREAMING_SNAKE_CASE   )   )
		__lowercase		       =			False
		ctypes.windll.kernelaa.SetConsoleCursorInfo(_SCREAMING_SNAKE_CASE  ,	ctypes.byref(_SCREAMING_SNAKE_CASE   )   )
	elif os.name == "posix":
		sys.stdout.write("\033[?25l"   )
		sys.stdout.flush()



def    snake_case_				(    ):
	if os.name == "nt":
		__lowercase		       =			CursorInfo()
		__lowercase		       =			ctypes.windll.kernelaa.GetStdHandle(-1_1   )
		ctypes.windll.kernelaa.GetConsoleCursorInfo(_SCREAMING_SNAKE_CASE  ,	ctypes.byref(_SCREAMING_SNAKE_CASE   )   )
		__lowercase		       =			True
		ctypes.windll.kernelaa.SetConsoleCursorInfo(_SCREAMING_SNAKE_CASE  ,	ctypes.byref(_SCREAMING_SNAKE_CASE   )   )
	elif os.name == "posix":
		sys.stdout.write("\033[?25h"   )
		sys.stdout.flush()



@contextmanager
def    snake_case_				(    ):
	try:
		hide_cursor()
		yield
	finally:
		show_cursor()



