





'''simple docstring'''







import argparse

import torch

from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging


logging.set_verbosity_info()
_a   :					Dict           =       logging.get_logger(__name__)

_a   :					Union[str, Any]           =       [
    ["""attention""", """attn"""],
    ["""encoder_attention""", """encoder_attn"""],
    ["""q_lin""", """q_proj"""],
    ["""k_lin""", """k_proj"""],
    ["""v_lin""", """v_proj"""],
    ["""out_lin""", """out_proj"""],
    ["""norm_embeddings""", """layernorm_embedding"""],
    ["""position_embeddings""", """embed_positions"""],
    ["""embeddings""", """embed_tokens"""],
    ["""ffn.lin""", """fc"""],
]





def   _lowerCAmelCase		(		lowercase      )   ->   List[Any]:


			if k == "embeddings.weight":
						return "shared.weight"

			for parlai_name, hf_name in PATTERNS:
						__lowerCAmelCase   		=							k.replace(_snake_case   ,      _snake_case      )

			if k.startswith("""encoder"""      ):
						__lowerCAmelCase   		=							k.replace(""".attn"""   ,      """.self_attn"""      )
						__lowerCAmelCase   		=							k.replace("""norm1"""   ,      """self_attn_layer_norm"""      )
						__lowerCAmelCase   		=							k.replace("""norm2"""   ,      """final_layer_norm"""      )
			elif k.startswith("""decoder"""      ):
						__lowerCAmelCase   		=							k.replace("""norm1"""   ,      """self_attn_layer_norm"""      )
						__lowerCAmelCase   		=							k.replace("""norm2"""   ,      """encoder_attn_layer_norm"""      )
						__lowerCAmelCase   		=							k.replace("""norm3"""   ,      """final_layer_norm"""      )
			return k





def   _lowerCAmelCase		(		lowercase      )   ->   int:
			__lowerCAmelCase   		=							[
			    """model.encoder.layernorm_embedding.weight""",
			    """model.encoder.layernorm_embedding.bias""",
			    """model.decoder.layernorm_embedding.weight""",
			    """model.decoder.layernorm_embedding.bias""",
			]
			for k in keys:
						__lowerCAmelCase   		=							sd.pop(_snake_case      )
						__lowerCAmelCase   		=							k.replace("""layernorm_embedding"""   ,      """layer_norm"""      )
						assert new_k not in sd
						__lowerCAmelCase   		=							v


_a   :					List[Any]           =       ["""START"""]





@torch.no_grad()
def   _lowerCAmelCase		(		lowercase   ,      lowercase   ,      lowercase      )   ->   Dict:
			__lowerCAmelCase   		=							torch.load(_snake_case   ,      map_location="""cpu"""      )
			__lowerCAmelCase   		=							model["""model"""]
			__lowerCAmelCase   		=							BlenderbotConfig.from_json_file(_snake_case      )
			__lowerCAmelCase   		=							BlenderbotForConditionalGeneration(_snake_case      )
			__lowerCAmelCase   		=							m.model.state_dict().keys()
			__lowerCAmelCase   		=							[]
			__lowerCAmelCase   		=							{}
			for k, v in sd.items():
						if k in IGNORE_KEYS:
									continue

						__lowerCAmelCase   		=							rename_state_dict_key(_snake_case      )
						if new_k not in valid_keys:
									failures.append([k, new_k]      )
						else:
									__lowerCAmelCase   		=							v
			if cfg.normalize_before:  # Blenderbot-3B checkpoints. Rename layernorm_embedding -> layer_norm
						rename_layernorm_keys(_snake_case      )
			m.model.load_state_dict(_snake_case   ,      strict=_snake_case      )
			m.half()
			m.save_pretrained(_snake_case      )


if __name__ == "__main__":
	_a   :					Union[str, Any]           =       argparse.ArgumentParser()
	# Required parameters
	parser.add_argument("""--src_path""", type=str, help="""like blenderbot-model.bin""")
	parser.add_argument("""--save_dir""", default="""hf_blenderbot""", type=str, help="""Where to save converted model.""")
	parser.add_argument(
	    """--hf_config_json""", default="""blenderbot-3b-config.json""", type=str, help="""Path to config to use"""
	)
	_a   :					Union[str, Any]           =       parser.parse_args()
	convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)






'''simple docstring'''





def 							lowerCamelCase	(					_snake_case	:    list							):





    '''simple docstring'''


    if not isinstance(_snake_case  ,_snake_case							):
        raise ValueError("Input series is not valid, valid series - [2, 4, 6]"							)
    if len(_snake_case							) == 0:
        raise ValueError("Input list must be a non empty list"							)
    if len(_snake_case							) == 1:
        return True
    lowercase__									=    series[1] - series[0]
    for index in range(len(_snake_case							) - 1							):
        if series[index + 1] - series[index] != common_diff:
            return False
    return True




def 							lowerCamelCase	(					_snake_case	:    list							):





    '''simple docstring'''


    if not isinstance(_snake_case  ,_snake_case							):
        raise ValueError("Input series is not valid, valid series - [2, 4, 6]"							)
    if len(_snake_case							) == 0:
        raise ValueError("Input list must be a non empty list"							)
    lowercase__									=    0
    for val in series:
        answer += val
    return answer / len(_snake_case							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()




