from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands
def       A	(    ):
						SCREAMING_SNAKE_CASE							:    Tuple							=							ArgumentParser('''Transformers CLI tool'''		,  usage='''transformers-cli <command> [<args>]'''						)
						SCREAMING_SNAKE_CASE							:    Dict							=							parser.add_subparsers(help='''transformers-cli command helpers'''						)

						# Register commands
						ConvertCommand.register_subcommand(_lowercase						)
						DownloadCommand.register_subcommand(_lowercase						)
						EnvironmentCommand.register_subcommand(_lowercase						)
						RunCommand.register_subcommand(_lowercase						)
						ServeCommand.register_subcommand(_lowercase						)
						UserCommands.register_subcommand(_lowercase						)
						AddNewModelCommand.register_subcommand(_lowercase						)
						AddNewModelLikeCommand.register_subcommand(_lowercase						)
						LfsCommands.register_subcommand(_lowercase						)
						PTtoTFCommand.register_subcommand(_lowercase						)

						# Let's go
						SCREAMING_SNAKE_CASE							:    int							=							parser.parse_args()

						if not hasattr(_lowercase		,  '''func'''						):
												parser.print_help()
												exit(1						)

						# Run
						SCREAMING_SNAKE_CASE							:    Dict							=							args.func(_lowercase						)
						service.run()


if __name__ == "__main__":
					main()






from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
					import tensorflow as tf

					from transformers import AutoTokenizer, TFAutoModelForSeqaSeqLM





@require_tf
@require_sentencepiece
@require_tokenizers
class 					lowercase__						(   unittest.TestCase):


						@slow
						def        __A       (       self	:				Union[str, Any]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Any							=							TFAutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''						)
												SCREAMING_SNAKE_CASE							:    List[str]							=							AutoTokenizer.from_pretrained('''google/mt5-small'''						)

												SCREAMING_SNAKE_CASE							:    Optional[int]							=							tokenizer('''Hello there'''    ,		return_tensors='''tf'''						).input_ids
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							tokenizer('''Hi I am'''    ,		return_tensors='''tf'''						).input_ids

												SCREAMING_SNAKE_CASE							:    List[Any]							=							model(UpperCamelCase__    ,		labels=UpperCamelCase__						).loss
												SCREAMING_SNAKE_CASE							:    int							=							-tf.math.reduce_mean(UpperCamelCase__						).numpy()

												SCREAMING_SNAKE_CASE							:    List[str]							=							-21.22_8168
												self.assertTrue(abs(mtf_score - EXPECTED_SCORE						) < 2E-4						)





