

def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ):





						def count_of_possible_combinations(SCREAMING_SNAKE_CASE__       ) -> int:
												if target < 0:
																		return 0
												if target == 0:
																		return 1
												return sum(count_of_possible_combinations(target - item       ) for item in array       )

						return count_of_possible_combinations(SCREAMING_SNAKE_CASE__       )


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ):





						def count_of_possible_combinations_with_dp_array(
						    SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ) -> int:
												if target < 0:
																		return 0
												if target == 0:
																		return 1
												if dp_array[target] != -1:
																		return dp_array[target]
												snake_case_   =	sum(
												    count_of_possible_combinations_with_dp_array(target - item  ,		SCREAMING_SNAKE_CASE__       )
												    for item in array       )
												snake_case_   =	answer
												return answer

						snake_case_   =	[-1] * (target + 1)
						return count_of_possible_combinations_with_dp_array(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	[0] * (target + 1)
						snake_case_   =	1

						for i in range(1  ,		target + 1       ):
												for j in range(SCREAMING_SNAKE_CASE__       ):
																		if i - array[j] >= 0:
																								dp_array[i] += dp_array[i - array[j]]

						return dp_array[target]


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					lowerCAmelCase_       	=	3
					lowerCAmelCase_       	=	5
					lowerCAmelCase_       	=	[1, 2, 5]
					print(combination_sum_iv(n, array, target))




import io
import json
import unittest

from parameterized import parameterized

from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu


_lowercase: Union[str, Any]      			=		get_tests_dir() + "/test_data/fsmt/fsmt_val_data.json"
with io.open(filename, "r", encoding="utf-8") as f:
				_lowercase: List[str]      			=		json.load(f)



@require_torch
class 	_lowercase							(   unittest.TestCase	):





	"""simple docstring"""




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						return FSMTTokenizer.from_pretrained(lowerCamelCase_		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						a					     =   FSMTForConditionalGeneration.from_pretrained(lowerCamelCase_		).to(lowerCamelCase_		)
						if torch_device == "cuda":
											model.half()
						return model




	@parameterized.expand(
	    [
	        ["en-ru", 26.0],
	        ["ru-en", 22.0],
	        ["en-de", 22.0],
	        ["de-en", 29.0],
	    ]		)
	@slow
	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_		):
						"""simple docstring"""

						a					     =   F'''facebook/wmt19-{pair}'''
						a					     =   self.get_tokenizer(lowerCamelCase_		)
						a					     =   self.get_model(lowerCamelCase_		)

						a					     =   bleu_data[pair]["src"]
						a					     =   bleu_data[pair]["tgt"]

						a					     =   tokenizer(lowerCamelCase_		,       return_tensors="pt"		,       truncation=lowerCamelCase_		,       padding="longest"		).to(lowerCamelCase_		)
						a					     =   model.generate(
						    input_ids=batch.input_ids		,       num_beams=8		,       )
						a					     =   tokenizer.batch_decode(
						    lowerCamelCase_		,       skip_special_tokens=lowerCamelCase_		,       clean_up_tokenization_spaces=lowerCamelCase_		)
						a					     =   calculate_bleu(lowerCamelCase_		,       lowerCamelCase_		)
						print(lowerCamelCase_		)
						self.assertGreaterEqual(scores["bleu"]		,       lowerCamelCase_		)
