
'''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
UpperCAmelCase__				:	int					=						"stas/tiny-wmt19-en-ru"






class 				A       (		SCREAMING_SNAKE_CASE__					, unittest.TestCase      ):
	snake_case__ :Optional[int]				       =       FSMTTokenizer
	snake_case__ :Dict				       =       False





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""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(__magic_name__ ,							range(len(__magic_name__							)							)							)							)
				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(__magic_name__							)							)
				with open(self.tgt_vocab_file ,							"w"							) as fp:
							fp.write(json.dumps(__magic_name__							)							)
				with open(self.merges_file ,							"w"							) as fp:
							fp.write("\n".join(__magic_name__							)							)
				with open(__magic_name__ ,							"w"							) as fp:
							fp.write(json.dumps(__magic_name__							)							)





	@cached_property
	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				return FSMTTokenizer.from_pretrained("facebook/wmt19-ru-en"							)





	@cached_property
	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				return FSMTTokenizer.from_pretrained("facebook/wmt19-en-ru"							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""simple docstring"""

				lowerCAmelCase__									=							FSMTTokenizer.from_pretrained(__magic_name__							)
				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 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""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(__magic_name__							)
				self.assertListEqual(__magic_name__ ,							__magic_name__							)

				lowerCAmelCase__									=							tokens + ["<unk>"]
				lowerCAmelCase__									=							[14, 15, 20]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__							) ,							__magic_name__							)





	@slow
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.tokenizer_ru_en

				lowerCAmelCase__									=							tokenizer.encode("sequence builders" ,							add_special_tokens=__magic_name__							)
				lowerCAmelCase__									=							tokenizer.encode("multi-sequence build" ,							add_special_tokens=__magic_name__							)

				lowerCAmelCase__									=							tokenizer.build_inputs_with_special_tokens(__magic_name__							)
				lowerCAmelCase__									=							tokenizer.build_inputs_with_special_tokens(__magic_name__ ,							__magic_name__							)

				assert encoded_sentence == text + [2]
				assert encoded_pair == text + [2] + text_a + [2]





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


				"""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.",
				        [2470, 39, 11, 2349, 7222, 70, 5979, 7, 8450, 1050, 13160, 5, 26, 6445, 7, 2],
				    ],
				    ["This is it. No more. I'm done!", [132, 21, 37, 7, 1434, 86, 7, 70, 6476, 1305, 427, 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(__magic_name__ ,							return_tensors=__magic_name__							)
							self.assertListEqual(__magic_name__ ,							__magic_name__							)

							# and decode backward, using the reversed languages model
							lowerCAmelCase__									=							tokenizer_dec.decode(__magic_name__ ,							skip_special_tokens=__magic_name__							)
							self.assertEqual(__magic_name__ ,							__magic_name__							)





	@slow
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Dict							):


				"""simple docstring"""

				lowerCAmelCase__									=							FSMTTokenizer.from_pretrained("facebook/wmt19-ru-en" ,							do_lower_case=__magic_name__							)
				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(__magic_name__ ,							__magic_name__							)





	@unittest.skip("FSMTConfig.__init__  requires non-optional args"							)
	def 							__SCREAMING_SNAKE_CASE					(   self     :    Union[str, Any]							):


				"""simple docstring"""

				pass







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


				"""simple docstring"""

				pass








'''simple docstring'''

import math







def 					A       ( UpperCamelCase_   :       int )   ->    list:







			'''simple docstring'''



			if n <= 0:
						raise ValueError("Only positive integers have prime factors" )
			lowerCAmelCase__									=							[]
			while n % 2 == 0:
						pf.append(2 )
						lowerCAmelCase__									=							int(n / 2 )
			for i in range(3  ,		int(math.sqrt(UpperCamelCase_ ) ) + 1  ,		2 ):
						while n % i == 0:
									pf.append(UpperCamelCase_ )
									lowerCAmelCase__									=							int(n / i )
			if n > 2:
						pf.append(UpperCamelCase_ )
			return pf







def 					A       ( UpperCamelCase_   :       int )   ->    int:







			'''simple docstring'''



			if n <= 0:
						raise ValueError("Only positive numbers are accepted" )
			lowerCAmelCase__									=							1
			lowerCAmelCase__									=							1
			while n % 2 == 0:
						temp += 1
						lowerCAmelCase__									=							int(n / 2 )
			div *= temp
			for i in range(3  ,		int(math.sqrt(UpperCamelCase_ ) ) + 1  ,		2 ):
						lowerCAmelCase__									=							1
						while n % i == 0:
									temp += 1
									lowerCAmelCase__									=							int(n / i )
						div *= temp
			if n > 1:
						div *= 2
			return div







def 					A       ( UpperCamelCase_   :       int )   ->    int:







			'''simple docstring'''



			if n <= 0:
						raise ValueError("Only positive numbers are accepted" )
			lowerCAmelCase__									=							1
			lowerCAmelCase__									=							1
			while n % 2 == 0:
						temp += 1
						lowerCAmelCase__									=							int(n / 2 )
			if temp > 1:
						s *= (2**temp - 1) / (2 - 1)
			for i in range(3  ,		int(math.sqrt(UpperCamelCase_ ) ) + 1  ,		2 ):
						lowerCAmelCase__									=							1
						while n % i == 0:
									temp += 1
									lowerCAmelCase__									=							int(n / i )
						if temp > 1:
									s *= (i**temp - 1) / (i - 1)
			return int(UpperCamelCase_ )







def 					A       ( UpperCamelCase_   :       int )   ->    int:







			'''simple docstring'''



			lowerCAmelCase__									=							n
			for x in set(prime_factors(UpperCamelCase_ ) ):
						s *= (x - 1) / x
			return int(UpperCamelCase_ )


if __name__ == "__main__":
		import doctest

		doctest.testmod()





