





'''simple docstring'''







import json
import os
import unittest

from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES, FSMTTokenizer
from transformers.testing_utils import slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


# using a different tiny model than the one used for default params defined in init to ensure proper testing
_a      :				Optional[int]											=					"""stas/tiny-wmt19-en-ru"""





class 					_UpperCAmelCase							(		lowerCAmelCase_			,      unittest.TestCase     ):
		a     :     int     						=FSMTTokenizer
		a     :     str     						=False
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					__lowerCAmelCase      		=       [
					    """l""",
					    """o""",
					    """w""",
					    """e""",
					    """r""",
					    """s""",
					    """t""",
					    """i""",
					    """d""",
					    """n""",
					    """w</w>""",
					    """r</w>""",
					    """t</w>""",
					    """lo""",
					    """low""",
					    """er</w>""",
					    """low</w>""",
					    """lowest</w>""",
					    """newer</w>""",
					    """wider</w>""",
					    """<unk>""",
					]
					__lowerCAmelCase      		=       dict(zip(__SCREAMING_SNAKE_CASE,range(len(__SCREAMING_SNAKE_CASE    )    )    )    )
					__lowerCAmelCase      		=       ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

					__lowerCAmelCase      		=       ["""en""", """ru"""]
					__lowerCAmelCase      		=       {
					    """langs""": self.langs,
					    """src_vocab_size""": 10,
					    """tgt_vocab_size""": 20,
					}

					__lowerCAmelCase      		=       os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["""src_vocab_file"""]    )
					__lowerCAmelCase      		=       os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["""tgt_vocab_file"""]    )
					__lowerCAmelCase      		=       os.path.join(self.tmpdirname,"""tokenizer_config.json"""    )
					__lowerCAmelCase      		=       os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["""merges_file"""]    )
					with open(self.src_vocab_file,"""w"""    ) as fp:
								fp.write(json.dumps(__SCREAMING_SNAKE_CASE    )    )
					with open(self.tgt_vocab_file,"""w"""    ) as fp:
								fp.write(json.dumps(__SCREAMING_SNAKE_CASE    )    )
					with open(self.merges_file,"""w"""    ) as fp:
								fp.write("""\n""".join(__SCREAMING_SNAKE_CASE    )    )
					with open(__SCREAMING_SNAKE_CASE,"""w"""    ) as fp:
								fp.write(json.dumps(__SCREAMING_SNAKE_CASE    )    )
		@cached_property
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					return FSMTTokenizer.from_pretrained("""facebook/wmt19-ru-en"""    )
		@cached_property
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					return FSMTTokenizer.from_pretrained("""facebook/wmt19-en-ru"""    )
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       FSMTTokenizer.from_pretrained(__SCREAMING_SNAKE_CASE    )
					self.assertListEqual([tokenizer.src_lang, tokenizer.tgt_lang],["""en""", """ru"""]    )
					self.assertEqual(tokenizer.src_vocab_size,21    )
					self.assertEqual(tokenizer.tgt_vocab_size,21    )
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       FSMTTokenizer(self.langs,self.src_vocab_file,self.tgt_vocab_file,self.merges_file    )

					__lowerCAmelCase      		=       """lower"""
					__lowerCAmelCase      		=       ["""low""", """er</w>"""]
					__lowerCAmelCase      		=       tokenizer.tokenize(__SCREAMING_SNAKE_CASE    )
					self.assertListEqual(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    )

					__lowerCAmelCase      		=       tokens + ["""<unk>"""]
					__lowerCAmelCase      		=       [14, 15, 20]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE    ),__SCREAMING_SNAKE_CASE    )
		@slow
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       self.tokenizer_ru_en

					__lowerCAmelCase      		=       tokenizer.encode("""sequence builders""",add_special_tokens=__SCREAMING_SNAKE_CASE    )
					__lowerCAmelCase      		=       tokenizer.encode("""multi-sequence build""",add_special_tokens=__SCREAMING_SNAKE_CASE    )

					__lowerCAmelCase      		=       tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE    )
					__lowerCAmelCase      		=       tokenizer.build_inputs_with_special_tokens(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    )

					assert encoded_sentence == text + [2]
					assert encoded_pair == text + [2] + text_a + [2]
		@slow
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       self.tokenizer_en_ru
					__lowerCAmelCase      		=       self.tokenizer_ru_en

					__lowerCAmelCase      		=       [
					    [
					        """Here's a little song I wrote. Don't worry, be happy.""",
					        [24_70, 39, 11, 23_49, 72_22, 70, 59_79, 7, 84_50, 10_50, 1_31_60, 5, 26, 64_45, 7, 2],
					    ],
					    ["""This is it. No more. I'm done!""", [1_32, 21, 37, 7, 14_34, 86, 7, 70, 64_76, 13_05, 4_27, 2]],
					]

					# if data needs to be recreated or added, run:
					# import torch
					# model = torch.hub.load("pytorch/fairseq", "transformer.wmt19.en-ru", checkpoint_file="model4.pt", tokenizer="moses", bpe="fastbpe")
					# for src_text, _ in targets: print(f"""[\n"{src_text}",\n {model.encode(src_text).tolist()}\n],""")

					for src_text, tgt_input_ids in targets:
								__lowerCAmelCase      		=       tokenizer_enc.encode(__SCREAMING_SNAKE_CASE,return_tensors=__SCREAMING_SNAKE_CASE    )
								self.assertListEqual(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    )

								# and decode backward, using the reversed languages model
								__lowerCAmelCase      		=       tokenizer_dec.decode(__SCREAMING_SNAKE_CASE,skip_special_tokens=__SCREAMING_SNAKE_CASE    )
								self.assertEqual(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    )
		@slow
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       FSMTTokenizer.from_pretrained("""facebook/wmt19-ru-en""",do_lower_case=__SCREAMING_SNAKE_CASE    )
					__lowerCAmelCase      		=       tokenizer.tokenize("""USA is United States of America"""    )
					__lowerCAmelCase      		=       ["""us""", """a</w>""", """is</w>""", """un""", """i""", """ted</w>""", """st""", """ates</w>""", """of</w>""", """am""", """er""", """ica</w>"""]
					self.assertListEqual(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    )
		@unittest.skip("""FSMTConfig.__init__  requires non-optional args"""    )
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					pass







		@unittest.skip("""FSMTConfig.__init__  requires non-optional args"""    )
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					pass









'''simple docstring'''







def      _lowerCAmelCase		(		lowercase = 1000			)      ->      int:
			__lowerCAmelCase      		=       []
			__lowerCAmelCase      		=       []
			__lowerCAmelCase      		=       3
			__lowerCAmelCase      		=       5
			__lowerCAmelCase      		=       1
			while True:
						__lowerCAmelCase      		=       z * temp
						if result < n:
									zmulti.append(lowercase			)
									temp += 1
						else:
									__lowerCAmelCase      		=       1
									break
			while True:
						__lowerCAmelCase      		=       x * temp
						if result < n:
									xmulti.append(lowercase			)
									temp += 1
						else:
									break
			__lowerCAmelCase      		=       list(set(xmulti + zmulti			)			)
			return sum(lowercase			)


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

