



'''simple docstring'''






import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


lowerCAmelCase:					int						       =						['small', 'medium', 'large']

lowerCAmelCase:					int						       =						'lm_head.decoder.weight'
lowerCAmelCase:					Dict						       =						'lm_head.weight'
def       lowerCamelCase__       (						_A ,			_A				):
  a						:					List[Any]        =     torch.load(UpperCamelCase__				)
  a						:					List[str]        =     d.pop(UpperCamelCase__				)
  os.makedirs(UpperCamelCase__ ,			exist_ok=UpperCamelCase__				)
  torch.save(UpperCamelCase__ ,			os.path.join(UpperCamelCase__ ,			UpperCamelCase__				)				)


if __name__ == "__main__":
     lowerCAmelCase:					Dict						       =						argparse.ArgumentParser()
     parser.add_argument('--dialogpt_path', default='.', type=str)
     lowerCAmelCase:					str						       =						parser.parse_args()
     for MODEL in DIALOGPT_MODELS:
          lowerCAmelCase:					Tuple						       =						os.path.join(args.dialogpt_path, F"{MODEL}_ft.pkl")
          lowerCAmelCase:					int						       =						F"./DialoGPT-{MODEL}"
          convert_dialogpt_checkpoint(
              checkpoint_path,
              pytorch_dump_folder_path,
          )




"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCAmelCase    :int     =					logging.get_logger(__name__)

_lowerCAmelCase    :Union[str, Any]     =					{
    'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json',
}
class 							_UpperCAmelCase							( a      ):





     '''simple docstring'''



     a__									='''mgp-str'''





     def __init__(					self       ,	A=[3_2, 1_2_8]       ,	A=4       ,	A=3       ,	A=2_7       ,	A=3_8       ,	A=5_0_2_5_7       ,	A=3_0_5_2_2       ,	A=7_6_8       ,	A=1_2       ,	A=1_2       ,	A=4.0       ,	A=True       ,	A=False       ,	A=1E-5       ,	A=0.0       ,	A=0.0       ,	A=0.0       ,	A=False       ,	A=0.02       ,	**A       ,	)							->					Union[str, Any]:
         super().__init__(**A		)

         _UpperCAmelCase							:  Any											=    image_size
         _UpperCAmelCase							:  str											=    patch_size
         _UpperCAmelCase							:  Dict											=    num_channels
         _UpperCAmelCase							:  Dict											=    max_token_length
         _UpperCAmelCase							:  Optional[Any]											=    num_character_labels
         _UpperCAmelCase							:  int											=    num_bpe_labels
         _UpperCAmelCase							:  List[str]											=    num_wordpiece_labels
         _UpperCAmelCase							:  Optional[int]											=    hidden_size
         _UpperCAmelCase							:  Any											=    num_hidden_layers
         _UpperCAmelCase							:  List[Any]											=    num_attention_heads
         _UpperCAmelCase							:  List[Any]											=    mlp_ratio
         _UpperCAmelCase							:  List[str]											=    distilled
         _UpperCAmelCase							:  Optional[int]											=    layer_norm_eps
         _UpperCAmelCase							:  str											=    drop_rate
         _UpperCAmelCase							:  List[Any]											=    qkv_bias
         _UpperCAmelCase							:  List[str]											=    attn_drop_rate
         _UpperCAmelCase							:  Dict											=    drop_path_rate
         _UpperCAmelCase							:  Union[str, Any]											=    output_aa_attentions
         _UpperCAmelCase							:  List[str]											=    initializer_range


