






from __future__ import annotations
def 					snake_case_						(   lowerCAmelCase_				:  Optional[int]					):
							__lowercase					:							Tuple			=   str(_lowercase					)
							return len(_lowercase					) == 9 and set(_lowercase					) == set("""123456789"""					)
def 					snake_case_						(   ):
							for base_num in range(9999				,				4999				,				-1					):
														__lowercase					:							List[Any]			=   100002 * base_num
														if is_9_pandigital(_lowercase					):
																					return candidate

							for base_num in range(333				,				99				,				-1					):
														__lowercase					:							Optional[int]			=   1002003 * base_num
														if is_9_pandigital(_lowercase					):
																					return candidate

							return None


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





