
import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    # Initialise PyTorch model
    snake_case__    =					TaConfig.from_json_file(__lowerCAmelCase				)
    print(F"""Building PyTorch model from configuration: {config}"""				)
    snake_case__    =					TaForConditionalGeneration(__lowerCAmelCase				)

    # Load weights from tf checkpoint
    load_tf_weights_in_ta(__lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				)

    # Save pytorch-model
    print(F"""Save PyTorch model to {pytorch_dump_path}"""				)
    model.save_pretrained(__lowerCAmelCase				)


if __name__ == "__main__":
     __magic_name__  							=	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(
         '''--config_file''',
         default=None,
         type=str,
         required=True,
         help=(
             '''The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture.'''
         ),
     )
     parser.add_argument(
         '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
     )
     __magic_name__  							=	parser.parse_args()
     convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)





import math





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase				):

    if initial_intensity < 0:
        raise ValueError("The value of intensity cannot be negative"				)
        # handling of negative values of initial intensity
    if angle < 0 or angle > 360:
        raise ValueError("In Malus Law, the angle is in the range 0-360 degrees"				)
        # handling of values out of allowed range
    return initial_intensity * (math.cos(math.radians(__lowerCAmelCase				)				) ** 2)


if __name__ == "__main__":
     import doctest

     doctest.testmod(name='''malus_law''')



