




'''simple docstring'''







import argparse

import torch

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


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

lowercase      :   Dict      =       [
    ["""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				):
     if k == "embeddings.weight":
          return "shared.weight"

     for parlai_name, hf_name in PATTERNS:
          snake_case			:      List[Any]        =			k.replace(__lowercase     ,   __lowercase				)

     if k.startswith("""encoder"""				):
          snake_case			:      Optional[int]        =			k.replace(""".attn"""     ,   """.self_attn"""				)
          snake_case			:      Optional[Any]        =			k.replace("""norm1"""     ,   """self_attn_layer_norm"""				)
          snake_case			:      str        =			k.replace("""norm2"""     ,   """final_layer_norm"""				)
     elif k.startswith("""decoder"""				):
          snake_case			:      Union[str, Any]        =			k.replace("""norm1"""     ,   """self_attn_layer_norm"""				)
          snake_case			:      int        =			k.replace("""norm2"""     ,   """encoder_attn_layer_norm"""				)
          snake_case			:      List[str]        =			k.replace("""norm3"""     ,   """final_layer_norm"""				)
     return k



def        lowerCamelCase__				(      __lowercase				):
     snake_case			:      Dict        =			[
         """model.encoder.layernorm_embedding.weight""",
         """model.encoder.layernorm_embedding.bias""",
         """model.decoder.layernorm_embedding.weight""",
         """model.decoder.layernorm_embedding.bias""",
     ]
     for k in keys:
          snake_case			:      Union[str, Any]        =			sd.pop(__lowercase				)
          snake_case			:      Tuple        =			k.replace("""layernorm_embedding"""     ,   """layer_norm"""				)
          assert new_k not in sd
          snake_case			:      Tuple        =			v


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



@torch.no_grad()
def        lowerCamelCase__				(      __lowercase     ,   __lowercase     ,   __lowercase				):
     snake_case			:      str        =			torch.load(__lowercase     ,   map_location="""cpu"""				)
     snake_case			:      Any        =			model["""model"""]
     snake_case			:      List[str]        =			BlenderbotConfig.from_json_file(__lowercase				)
     snake_case			:      List[Any]        =			BlenderbotForConditionalGeneration(__lowercase				)
     snake_case			:      Any        =			m.model.state_dict().keys()
     snake_case			:      Dict        =			[]
     snake_case			:      Optional[int]        =			{}
     for k, v in sd.items():
          if k in IGNORE_KEYS:
               continue

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


if __name__ == "__main__":
      lowercase      :   Optional[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"""
      )
      lowercase      :   List[Any]      =       parser.parse_args()
      convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)









'''simple docstring'''







def        lowerCamelCase__				(      __lowercase				):
     if not isinstance(__lowercase     ,   __lowercase				):
          snake_case			:      int        =			F'''Input value of [number={number}] must be an integer'''
          raise TypeError(__lowercase				)
     if number < 0:
          return False
     snake_case			:      Optional[int]        =			number * number
     while number > 0:
          if number % 10 != number_square % 10:
               return False
          number //= 10
          number_square //= 10
     return True


if __name__ == "__main__":
      import doctest

      doctest.testmod()



