



def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				if n_term == "":
								return []
				lowercase__					:   list													=					[]
				for temp in range(int(lowerCamelCase__						)						):
								series.append(F"""1/{temp + 1}""" if series else "1"						)
				return series


if __name__ == "__main__":
				lowerCAmelCase__					  =  input('''Enter the last number (nth term) of the Harmonic Series''')
				print('''Formula of Harmonic Series => 1+1/2+1/3 ..... 1/n''')
				print(harmonic_series(nth_term))









import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
				import optax
				from flax.training.common_utils import onehot

				from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
				from transformers.models.ta.modeling_flax_ta import shift_tokens_right

@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class 				snake_case__(unittest.TestCase      ):

					"""simple docstring"""






					@slow
					def 			snake_case					(							self :     Optional[int]					):
									lowercase__					:   Dict													=					FlaxMTaForConditionalGeneration.from_pretrained("google/mt5-small"					)
									lowercase__					:   Dict													=					AutoTokenizer.from_pretrained("google/mt5-small"					)

									lowercase__					:   Optional[Any]													=					tokenizer("Hello there"				,       return_tensors="np"					).input_ids
									lowercase__					:   Optional[Any]													=					tokenizer("Hi I am"				,       return_tensors="np"					).input_ids

									lowercase__					:   int													=					shift_tokens_right(SCREAMING_SNAKE_CASE				,       model.config.pad_token_id				,       model.config.decoder_start_token_id					)

									lowercase__					:   Tuple													=					model(SCREAMING_SNAKE_CASE				,       decoder_input_ids=SCREAMING_SNAKE_CASE					).logits
									lowercase__					:   Dict													=					optax.softmax_cross_entropy(SCREAMING_SNAKE_CASE				,       onehot(SCREAMING_SNAKE_CASE				,       logits.shape[-1]					)					).mean()

									lowercase__					:   Union[str, Any]													=					-(labels.shape[-1] * loss.item())

									lowercase__					:   Union[str, Any]													=					-84.9_127
									self.assertTrue(abs(mtf_score - EXPECTED_SCORE					) < 1E-4					)




