import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


_SCREAMING_SNAKE_CASE										=						["""small""", """medium""", """large"""]

_SCREAMING_SNAKE_CASE										=						"""lm_head.decoder.weight"""
_SCREAMING_SNAKE_CASE										=						"""lm_head.weight"""






def  snake_case  (       snake_case__			:List[str]   ,	snake_case__			:Tuple)						->   Tuple:
       _A        =  torch.load(snake_case__)
       _A        =  d.pop(snake_case__)
       os.makedirs(snake_case__   ,	exist_ok=snake_case__)
       torch.save(snake_case__   ,	os.path.join(snake_case__   ,	snake_case__))


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





from ...configuration_utils import PretrainedConfig
from ...utils import logging


__a  :     str       =  logging.get_logger(__name__)

__a  :     Optional[int]       =  {
    """google/vivit-b-16x2-kinetics400""": (
        """https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}




class    _UpperCamelCase      (						_UpperCAmelCase ):


			"""simple docstring"""






			__a  : Tuple			 =						'''vivit'''





			def __init__(   self      ,   lowerCAmelCase__=2_24      ,   lowerCAmelCase__=32      ,   lowerCAmelCase__=[2, 16, 16]      ,   lowerCAmelCase__=3      ,   lowerCAmelCase__=7_68      ,   lowerCAmelCase__=12      ,   lowerCAmelCase__=12      ,   lowerCAmelCase__=30_72      ,   lowerCAmelCase__="gelu_fast"      ,   lowerCAmelCase__=0.0      ,   lowerCAmelCase__=0.0      ,   lowerCAmelCase__=0.02      ,   lowerCAmelCase__=1E-06      ,   lowerCAmelCase__=True      ,   **lowerCAmelCase__      ,   )     ->					int:

							'''simple docstring'''


							__lowercase 			=							hidden_size
							__lowercase 			=							num_hidden_layers
							__lowercase 			=							num_attention_heads
							__lowercase 			=							intermediate_size
							__lowercase 			=							hidden_act
							__lowercase 			=							hidden_dropout_prob
							__lowercase 			=							attention_probs_dropout_prob
							__lowercase 			=							initializer_range
							__lowercase 			=							layer_norm_eps

							__lowercase 			=							image_size
							__lowercase 			=							num_frames
							__lowercase 			=							tubelet_size
							__lowercase 			=							num_channels
							__lowercase 			=							qkv_bias

							super().__init__(**lowerCAmelCase__						)