




import argparse

from transformers import ConvBertConfig, ConvBertModel, TFConvBertModel, load_tf_weights_in_convbert
from transformers.utils import logging


logging.set_verbosity_info()





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Dict:







				'''simple docstring'''


				__lowerCAmelCase					=  ConvBertConfig.from_json_file(__UpperCamelCase   )
				__lowerCAmelCase					=  ConvBertModel(__UpperCamelCase   )

				__lowerCAmelCase					=  load_tf_weights_in_convbert(__UpperCamelCase						,			__UpperCamelCase						,			__UpperCamelCase   )
				model.save_pretrained(__UpperCamelCase   )

				__lowerCAmelCase					=  TFConvBertModel.from_pretrained(__UpperCamelCase						,			from_pt=__UpperCamelCase   )
				tf_model.save_pretrained(__UpperCamelCase   )


if __name__ == "__main__":
	__A						:		Tuple          =						argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    "--tf_checkpoint_path", default=None, type=str, required=True, help="Path to the TensorFlow checkpoint path."
	)
	parser.add_argument(
	    "--convbert_config_file",
	    default=None,
	    type=str,
	    required=True,
	    help=(
	        "The config json file corresponding to the pre-trained ConvBERT model. \n"
	        "This specifies the model architecture."
	    ),
	)
	parser.add_argument(
	    "--pytorch_dump_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
	)
	__A						:		Optional[Any]          =						parser.parse_args()
	convert_orig_tfa_checkpoint_to_pytorch(args.tf_checkpoint_path, args.convbert_config_file, args.pytorch_dump_path)







"""simple docstring"""


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


__A					=			logging.get_logger(__name__)

__A					=			{
    'uw-madison/nystromformer-512': 'https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}







class 						lowerCamelCase__   (   __magic_name__							):





			'''simple docstring'''
			lowerCamelCase       =						'''nystromformer'''



			def __init__(				self	,	__UpperCAmelCase=3_00_00	,	__UpperCAmelCase=7_68	,	__UpperCAmelCase=12	,	__UpperCAmelCase=12	,	__UpperCAmelCase=30_72	,	__UpperCAmelCase="gelu_new"	,	__UpperCAmelCase=0.1	,	__UpperCAmelCase=0.1	,	__UpperCAmelCase=5_10	,	__UpperCAmelCase=2	,	__UpperCAmelCase=64	,	__UpperCAmelCase=64	,	__UpperCAmelCase=65	,	__UpperCAmelCase=False	,	__UpperCAmelCase=0.0_2	,	__UpperCAmelCase=1e-5	,	__UpperCAmelCase=1	,	__UpperCAmelCase=0	,	__UpperCAmelCase=2	,	**__UpperCAmelCase	,	)					->	Union[str, Any]:
				_lowerCAmelCase								=vocab_size
				_lowerCAmelCase								=max_position_embeddings
				_lowerCAmelCase								=hidden_size
				_lowerCAmelCase								=num_hidden_layers
				_lowerCAmelCase								=num_attention_heads
				_lowerCAmelCase								=intermediate_size
				_lowerCAmelCase								=hidden_act
				_lowerCAmelCase								=hidden_dropout_prob
				_lowerCAmelCase								=attention_probs_dropout_prob
				_lowerCAmelCase								=initializer_range
				_lowerCAmelCase								=type_vocab_size
				_lowerCAmelCase								=segment_means_seq_len
				_lowerCAmelCase								=num_landmarks
				_lowerCAmelCase								=conv_kernel_size
				_lowerCAmelCase								=inv_coeff_init_option
				_lowerCAmelCase								=layer_norm_eps
				super().__init__(pad_token_id=__UpperCAmelCase	,	bos_token_id=__UpperCAmelCase	,	eos_token_id=__UpperCAmelCase	,	**__UpperCAmelCase    )



