
import argparse

from transformers import CanineConfig, CanineModel, CanineTokenizer, load_tf_weights_in_canine
from transformers.utils import logging


logging.set_verbosity_info()





def        lowerCAmelCase       (				snake_case__   :      List[Any]				,					snake_case__   :      List[str] )->			Any:
    # Initialize PyTorch model
    A_								=					CanineConfig()
    A_								=					CanineModel(snake_case__ )
    model.eval()

    print(f'Building PyTorch model from configuration: {config}' )

    # Load weights from tf checkpoint
    load_tf_weights_in_canine(snake_case__				,					snake_case__				,					snake_case__ )

    # Save pytorch-model (weights and configuration)
    print(f'Save PyTorch model to {pytorch_dump_path}' )
    model.save_pretrained(snake_case__ )

    # Save tokenizer files
    A_								=					CanineTokenizer()
    print(f'Save tokenizer files to {pytorch_dump_path}' )
    tokenizer.save_pretrained(snake_case__ )


if __name__ == "__main__":
     __magic_name__  :  Any     			=   argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         '--tf_checkpoint_path',
         default=None,
         type=str,
         required=True,
         help='Path to the TensorFlow checkpoint. Should end with model.ckpt',
     )
     parser.add_argument(
         '--pytorch_dump_path',
         default=None,
         type=str,
         required=True,
         help='Path to a folder where the PyTorch model will be placed.',
     )
     __magic_name__  :  Optional[Any]     			=   parser.parse_args()
     convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.pytorch_dump_path)








import sys

sys.set_int_max_str_digits(0)  # type: ignore





def        lowerCAmelCase       (				snake_case__   :      int )->			bool:
    A_								=					[0] * 11
    A_								=					[0] * 11

    # mark last 9 numbers
    for _ in range(9 ):
        A_								=					1
        A_								=					number // 10
    # flag
    A_								=					True

    # check last 9 numbers for pandigitality

    for x in range(9 ):
        if not check_last[x + 1]:
            A_								=					False
    if not f:
        return f

    # mark first 9 numbers
    A_								=					int(str(snake_case__ )[:9] )

    for _ in range(9 ):
        A_								=					1
        A_								=					number // 10

    # check first 9 numbers for pandigitality

    for x in range(9 ):
        if not check_front[x + 1]:
            A_								=					False
    return f





def        lowerCAmelCase       (				snake_case__   :      int )->			bool:
    A_								=					[0] * 11

    # mark last 9 numbers
    for _ in range(9 ):
        A_								=					1
        A_								=					number // 10
    # flag
    A_								=					True

    # check last 9 numbers for pandigitality

    for x in range(9 ):
        if not check_last[x + 1]:
            A_								=					False
    return f





def        lowerCAmelCase       (				)->			int:
    A_								=					1
    A_								=					1
    A_								=					2
    # temporary Fibonacci numbers

    A_								=					1
    A_								=					1
    A_								=					2
    # temporary Fibonacci numbers mod 1e9

    # mod m=1e9, done for fast optimisation
    A_								=					[0] * 1000000
    A_								=					1000000000

    for x in range(1000000 ):
        A_								=					(aa + ba) % m
        A_								=					ba % m
        A_								=					ca % m
        if checka(snake_case__ ):
            A_								=					1

    for x in range(1000000 ):
        A_								=					a + b
        A_								=					b
        A_								=					c
        # perform check only if in tocheck
        if tocheck[x + 3] and check(snake_case__ ):
            return x + 3  # first 2 already done
    return -1


if __name__ == "__main__":
     print(f"""{solution() = }""")






