
"""simple docstring"""



import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM
def 					lowerCamelCase   (     _snake_case ):
    if "model" in orig_key:
        UpperCAmelCase__	:      Union[str, Any]     							=					orig_key.replace('model.'    ,'' )
    if "norm1" in orig_key:
        UpperCAmelCase__	:      str     							=					orig_key.replace('norm1'    ,'attention.output.LayerNorm' )
    if "norm2" in orig_key:
        UpperCAmelCase__	:      Optional[int]     							=					orig_key.replace('norm2'    ,'output.LayerNorm' )
    if "norm" in orig_key:
        UpperCAmelCase__	:      Optional[int]     							=					orig_key.replace('norm'    ,'LayerNorm' )
    if "transformer" in orig_key:
        UpperCAmelCase__	:      Tuple     							=					orig_key.split('.' )[0].split('_' )[-1]
        UpperCAmelCase__	:      Optional[int]     							=					orig_key.replace(F'''transformer_{layer_num}'''    ,F'''encoder.layer.{layer_num}''' )
    if "mha.attn" in orig_key:
        UpperCAmelCase__	:      List[Any]     							=					orig_key.replace('mha.attn'    ,'attention.self' )
    if "mha" in orig_key:
        UpperCAmelCase__	:      int     							=					orig_key.replace('mha'    ,'attention' )
    if "W_q" in orig_key:
        UpperCAmelCase__	:      Dict     							=					orig_key.replace('W_q'    ,'self.query' )
    if "W_k" in orig_key:
        UpperCAmelCase__	:      Dict     							=					orig_key.replace('W_k'    ,'self.key' )
    if "W_v" in orig_key:
        UpperCAmelCase__	:      int     							=					orig_key.replace('W_v'    ,'self.value' )
    if "ff1" in orig_key:
        UpperCAmelCase__	:      int     							=					orig_key.replace('ff1'    ,'intermediate.dense' )
    if "ff2" in orig_key:
        UpperCAmelCase__	:      str     							=					orig_key.replace('ff2'    ,'output.dense' )
    if "ff" in orig_key:
        UpperCAmelCase__	:      Tuple     							=					orig_key.replace('ff'    ,'output.dense' )
    if "mlm_class" in orig_key:
        UpperCAmelCase__	:      Dict     							=					orig_key.replace('mlm.mlm_class'    ,'cls.predictions.decoder' )
    if "mlm" in orig_key:
        UpperCAmelCase__	:      Union[str, Any]     							=					orig_key.replace('mlm'    ,'cls.predictions.transform' )
    if "cls" not in orig_key:
        UpperCAmelCase__	:      Dict     							=					'yoso.' + orig_key

    return orig_key
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    for key in orig_state_dict.copy().keys():
        UpperCAmelCase__	:      Optional[int]     							=					orig_state_dict.pop(_snake_case )

        if ("pooler" in key) or ("sen_class" in key):
            continue
        else:
            UpperCAmelCase__	:      Union[str, Any]     							=					val

    UpperCAmelCase__	:      Dict     							=					orig_state_dict['cls.predictions.decoder.bias']
    UpperCAmelCase__	:      int     							=					torch.arange(_snake_case ).expand((1, -1) ) + 2

    return orig_state_dict
def 					lowerCamelCase   (     _snake_case    ,_snake_case    ,_snake_case ):
    UpperCAmelCase__	:      Tuple     							=					torch.load(_snake_case    ,map_location='cpu' )['model_state_dict']
    UpperCAmelCase__	:      Union[str, Any]     							=					YosoConfig.from_json_file(_snake_case )
    UpperCAmelCase__	:      int     							=					YosoForMaskedLM(_snake_case )

    UpperCAmelCase__	:      Union[str, Any]     							=					convert_checkpoint_helper(config.max_position_embeddings    ,_snake_case )

    print(model.load_state_dict(_snake_case ) )
    model.eval()
    model.save_pretrained(_snake_case )

    print(F'''Checkpoint successfuly converted. Model saved at {pytorch_dump_path}''' )


if __name__ == "__main__":
    UpperCamelCase__          =	argparse.ArgumentParser()
    # Required parameters
    parser.add_argument(
        '--pytorch_model_path', default=None, type=str, required=True, help='Path to YOSO pytorch checkpoint.'
    )
    parser.add_argument(
        '--config_file',
        default=None,
        type=str,
        required=True,
        help='The json file for YOSO model config.',
    )
    parser.add_argument(
        '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
    )
    UpperCamelCase__          =	parser.parse_args()
    convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)



"""simple docstring"""



UpperCamelCase__          =	{
    'meter': 'm',
    'kilometer': 'km',
    'megametre': 'Mm',
    'gigametre': 'Gm',
    'terametre': 'Tm',
    'petametre': 'Pm',
    'exametre': 'Em',
    'zettametre': 'Zm',
    'yottametre': 'Ym',
}
# Exponent of the factor(meter)
UpperCamelCase__          =	{
    'm': 0,
    'km': 3,
    'Mm': 6,
    'Gm': 9,
    'Tm': 12,
    'Pm': 15,
    'Em': 18,
    'Zm': 21,
    'Ym': 24,
}
def 					lowerCamelCase   (     _snake_case    ,_snake_case    ,_snake_case ):
    UpperCAmelCase__	:      int     							=					from_type.lower().strip('s' )
    UpperCAmelCase__	:      List[Any]     							=					to_type.lower().strip('s' )

    UpperCAmelCase__	:      Optional[int]     							=					UNIT_SYMBOL.get(_snake_case    ,_snake_case )
    UpperCAmelCase__	:      Optional[Any]     							=					UNIT_SYMBOL.get(_snake_case    ,_snake_case )

    if from_sanitized not in METRIC_CONVERSION:
        UpperCAmelCase__	:      Optional[int]     							=					(
            F'''Invalid \'from_type\' value: {from_type!r}.\n'''
            F'''Conversion abbreviations are: {', '.join(_snake_case )}'''
        )
        raise ValueError(_snake_case )
    if to_sanitized not in METRIC_CONVERSION:
        UpperCAmelCase__	:      int     							=					(
            F'''Invalid \'to_type\' value: {to_type!r}.\n'''
            F'''Conversion abbreviations are: {', '.join(_snake_case )}'''
        )
        raise ValueError(_snake_case )
    UpperCAmelCase__	:      str     							=					METRIC_CONVERSION[from_sanitized]
    UpperCAmelCase__	:      Optional[int]     							=					METRIC_CONVERSION[to_sanitized]
    UpperCAmelCase__	:      int     							=					1

    if from_exponent > to_exponent:
        UpperCAmelCase__	:      List[str]     							=					from_exponent - to_exponent
    else:
        UpperCAmelCase__	:      int     							=					-(to_exponent - from_exponent)

    return value * pow(10    ,_snake_case )


if __name__ == "__main__":
    from doctest import testmod

    testmod()

