


import argparse
from pathlib import Path

import torch

from transformers import OPTConfig, OPTModel
from transformers.utils import logging


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


def 		lowercase_  (     _UpperCamelCase  ):
			__lowercase 					=   torch.load(_UpperCamelCase       ,			map_location='''cpu'''  )
			if "model" in sd.keys():
						__lowercase 					=   torch.load(_UpperCamelCase       ,			map_location='''cpu'''  )['''model''']

			# pop unnecessary weights
			__lowercase 					=   [
			    '''decoder.version''',
			    '''decoder.output_projection.weight''',
			]
			for key in keys_to_delete:
						if key in sd:
									sd.pop(_UpperCamelCase  )

			__lowercase 					=   {
			    '''decoder.project_in_dim.weight''': '''decoder.project_in.weight''',
			    '''decoder.project_out_dim.weight''': '''decoder.project_out.weight''',
			    '''decoder.layer_norm.weight''': '''decoder.final_layer_norm.weight''',
			    '''decoder.layer_norm.bias''': '''decoder.final_layer_norm.bias''',
			}
			for old_key, new_key in keys_to_rename.items():
						if old_key in sd:
									__lowercase 					=   sd.pop(_UpperCamelCase  )

			__lowercase 					=   list(sd.keys()  )
			for key in keys:
						if ".qkv_proj." in key:
									__lowercase 					=   sd[key]
									# We split QKV in separate Q,K,V

									__lowercase 					=   key.replace('''.qkv_proj.'''       ,			'''.q_proj.'''  )
									__lowercase 					=   key.replace('''.qkv_proj.'''       ,			'''.k_proj.'''  )
									__lowercase 					=   key.replace('''.qkv_proj.'''       ,			'''.v_proj.'''  )

									__lowercase 					=   value.shape[0]
									assert depth % 3 == 0
									# `SequeuceParallelTransformerBlock` has QKV weight is separated in K,V,Q despite the naming:
									# https://cs.github.com/facebookresearch/metaseq/blob/51871bd73cd04c038f239ea2a26db1d7f6b37927/metaseq/modules/sequence_parallel_transformer_layer.py#L97
									__lowercase					, __lowercase					, __lowercase 					=   torch.split(_UpperCamelCase       ,			depth // 3       ,			dim=0  )

									__lowercase 					=   q
									__lowercase 					=   k
									__lowercase 					=   v
									del sd[key]

			return sd


@torch.no_grad()
def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase=None  ):
			__lowercase 					=   load_checkpoint(_UpperCamelCase  )

			if config is not None:
						__lowercase 					=   OPTConfig.from_pretrained(_UpperCamelCase  )
			else:
						__lowercase 					=   OPTConfig()

			__lowercase 					=   OPTModel(_UpperCamelCase  ).half().eval()
			model.load_state_dict(_UpperCamelCase  )

			# Check results
			Path(_UpperCamelCase  ).mkdir(exist_ok=_UpperCamelCase  )
			model.save_pretrained(_UpperCamelCase  )


if __name__ == "__main__":
	a : Union[str, Any]		=				argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    '''--fairseq_path''',
	    type=str,
	    help=(
	        '''path to fairseq checkpoint in correct format. You can find all checkpoints in the correct format here:'''
	        ''' https://huggingface.co/models?other=opt_metasq'''
	    ),
	)
	parser.add_argument('''--pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model.''')
	parser.add_argument('''--hf_config''', default=None, type=str, help='''Define HF config.''')
	a : Union[str, Any]		=				parser.parse_args()
	convert_opt_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, config=args.hf_config)






a : Any		=				'''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

a : Union[str, Any]		=				[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
a : Union[str, Any]		=				{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}


