'''simple docstring'''
import argparse

import torch
from torch import nn

from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration



def  __lowerCamelCase       (      _UpperCamelCase  :  Tuple					):


      '''simple docstring'''


      UpperCAmelCase_            =  [
          """encoder.version""",
          """decoder.version""",
          """model.encoder.version""",
          """model.decoder.version""",
          """decoder.output_projection.weight""",
          """_float_tensor""",
          """encoder.embed_positions._float_tensor""",
          """decoder.embed_positions._float_tensor""",
      ]
      for k in ignore_keys:
            state_dict.pop(UpperCAmelCase__							,    UpperCAmelCase__					)



def  __lowerCamelCase       (      _UpperCamelCase  :  Dict					):


      '''simple docstring'''


      UpperCAmelCase_            =  emb.weight.shape
      UpperCAmelCase_            =  nn.Linear(UpperCAmelCase__							,    UpperCAmelCase__							,    bias=UpperCAmelCase__					)
      UpperCAmelCase_            =  emb.weight.data
      return lin_layer



def  __lowerCamelCase       (      _UpperCamelCase  :  List[Any]					):


      '''simple docstring'''


      UpperCAmelCase_            =  torch.load(UpperCAmelCase__							,    map_location='''cpu'''					)
      UpperCAmelCase_            =  mam_aaa["""args"""] or mam_aaa["""cfg"""]["""model"""]
      UpperCAmelCase_            =  mam_aaa["""model"""]
      remove_ignore_keys_(UpperCAmelCase__					)
      UpperCAmelCase_            =  state_dict["""encoder.embed_tokens.weight"""].shape[0]

      UpperCAmelCase_            =  MaMaaaConfig(
          vocab_size=UpperCAmelCase__							,    max_position_embeddings=1024							,    encoder_layers=args.encoder_layers							,    decoder_layers=args.decoder_layers							,    encoder_attention_heads=args.encoder_attention_heads							,    decoder_attention_heads=args.decoder_attention_heads							,    encoder_ffn_dim=args.encoder_ffn_embed_dim							,    decoder_ffn_dim=args.decoder_ffn_embed_dim							,    d_model=args.encoder_embed_dim							,    encoder_layerdrop=args.encoder_layerdrop							,    decoder_layerdrop=args.decoder_layerdrop							,    dropout=args.dropout							,    attention_dropout=args.attention_dropout							,    activation_dropout=args.activation_dropout							,    activation_function='''relu'''							,    )

      UpperCAmelCase_            =  state_dict["""decoder.embed_tokens.weight"""]
      UpperCAmelCase_            =  MaMaaaForConditionalGeneration(UpperCAmelCase__					)
      model.model.load_state_dict(UpperCAmelCase__							,    strict=UpperCAmelCase__					)
      UpperCAmelCase_            =  make_linear_from_emb(model.model.shared					)

      return model


if __name__ == "__main__":
      lowercase__  :      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.")
      lowercase__  :      Any        =					parser.parse_args()
      lowercase__  :      Dict        =					convert_fairseq_mamaaa_checkpoint_from_disk(args.fairseq_pathß)
      model.save_pretrained(args.pytorch_dump_folder_path)






'''simple docstring'''
import re



def  __lowerCamelCase       (      _UpperCamelCase  :  str					):


      '''simple docstring'''


      return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]'''							,    str_					)]



def  __lowerCamelCase       (      _UpperCamelCase  :  str					):


      '''simple docstring'''


      UpperCAmelCase_            =  split_input(str_					)
      return "".join(
          [''''''.join([char.capitalize() for char in sub_str]					) for sub_str in string_split]					)



def  __lowerCamelCase       (      _UpperCamelCase  :  str							,    _UpperCamelCase  :  bool							,    _UpperCamelCase  :  str					):


      '''simple docstring'''


      try:
            UpperCAmelCase_            =  split_input(_UpperCamelCase					)
            if upper:
                  UpperCAmelCase_            =  ''''''.join(
                      [
                          separator.join([char.upper() for char in sub_str]					)
                          for sub_str in string_split
                      ]					)
            else:
                  UpperCAmelCase_            =  ''''''.join(
                      [
                          separator.join([char.lower() for char in sub_str]					)
                          for sub_str in string_split
                      ]					)
            return res_str
      except IndexError:
            return "not valid string"



def  __lowerCamelCase       (      _UpperCamelCase  :  str					):


      '''simple docstring'''


      return to_simple_case(_UpperCamelCase					)



def  __lowerCamelCase       (      _UpperCamelCase  :  str					):


      '''simple docstring'''


      try:
            UpperCAmelCase_            =  to_simple_case(_UpperCamelCase					)
            return res_str[0].lower() + res_str[1:]
      except IndexError:
            return "not valid string"



def  __lowerCamelCase       (      _UpperCamelCase  :  str							,    _UpperCamelCase  :  bool					):


      '''simple docstring'''


      return to_complex_case(_UpperCamelCase							,    _UpperCamelCase							,    '''_'''					)



def  __lowerCamelCase       (      _UpperCamelCase  :  str							,    _UpperCamelCase  :  bool					):


      '''simple docstring'''


      return to_complex_case(_UpperCamelCase							,    _UpperCamelCase							,    '''-'''					)


if __name__ == "__main__":
      __import__("doctest").testmod()





