"""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         =		"stas/tiny-wmt19-en-ru"
class 	__UpperCAmelCase						(__A       ,      unittest.TestCase    ):







			'''simple docstring'''
			_UpperCamelCase     :	List[Any]				    =							FSMTTokenizer
			_UpperCamelCase     :	Optional[Any]				    =							False





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										super().setUp()

										# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
										A__					:    Tuple														= [
										    """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>""",
										]
										A__					:    str														= dict(zip(snake_case_      ,			range(len(snake_case_       )       )       )       )
										A__					:    List[Any]														= ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

										A__					:    Union[str, Any]														= ["""en""", """ru"""]
										A__					:    Dict														= {
										    """langs""": self.langs,
										    """src_vocab_size""": 10,
										    """tgt_vocab_size""": 20,
										}

										A__					:    List[str]														= os.path.join(self.tmpdirname      ,			VOCAB_FILES_NAMES["""src_vocab_file"""]       )
										A__					:    Optional[Any]														= os.path.join(self.tmpdirname      ,			VOCAB_FILES_NAMES["""tgt_vocab_file"""]       )
										A__					:    Optional[Any]														= os.path.join(self.tmpdirname      ,			"""tokenizer_config.json"""       )
										A__					:    List[Any]														= os.path.join(self.tmpdirname      ,			VOCAB_FILES_NAMES["""merges_file"""]       )
										with open(self.src_vocab_file      ,			"""w"""       ) as fp:
																	fp.write(json.dumps(snake_case_       )       )
										with open(self.tgt_vocab_file      ,			"""w"""       ) as fp:
																	fp.write(json.dumps(snake_case_       )       )
										with open(self.merges_file      ,			"""w"""       ) as fp:
																	fp.write("""\n""".join(snake_case_       )       )
										with open(snake_case_      ,			"""w"""       ) as fp:
																	fp.write(json.dumps(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'''


										A__					:    Dict														= FSMTTokenizer.from_pretrained(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'''


										A__					:    Optional[Any]														= FSMTTokenizer(self.langs      ,			self.src_vocab_file      ,			self.tgt_vocab_file      ,			self.merges_file       )

										A__					:    Union[str, Any]														= """lower"""
										A__					:    List[str]														= ["""low""", """er</w>"""]
										A__					:    List[Any]														= tokenizer.tokenize(snake_case_       )
										self.assertListEqual(snake_case_      ,			snake_case_       )

										A__					:    int														= tokens + ["""<unk>"""]
										A__					:    List[Any]														= [14, 15, 20]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_       )      ,			snake_case_       )





			@slow
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    int														= self.tokenizer_ru_en

										A__					:    Union[str, Any]														= tokenizer.encode("""sequence builders"""      ,			add_special_tokens=snake_case_       )
										A__					:    str														= tokenizer.encode("""multi-sequence build"""      ,			add_special_tokens=snake_case_       )

										A__					:    Optional[int]														= tokenizer.build_inputs_with_special_tokens(snake_case_       )
										A__					:    int														= tokenizer.build_inputs_with_special_tokens(snake_case_      ,			snake_case_       )

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





			@slow
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Any														= self.tokenizer_en_ru
										A__					:    Tuple														= self.tokenizer_ru_en

										A__					:    List[Any]														= [
										    [
										        """Here's a little song I wrote. Don't worry, be happy.""",
										        [2_470, 39, 11, 2_349, 7_222, 70, 5_979, 7, 8_450, 1_050, 13_160, 5, 26, 6_445, 7, 2],
										    ],
										    ["""This is it. No more. I'm done!""", [132, 21, 37, 7, 1_434, 86, 7, 70, 6_476, 1_305, 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:
																	A__					:    Dict														= tokenizer_enc.encode(snake_case_      ,			return_tensors=snake_case_       )
																	self.assertListEqual(snake_case_      ,			snake_case_       )

																	# and decode backward, using the reversed languages model
																	A__					:    str														= tokenizer_dec.decode(snake_case_      ,			skip_special_tokens=snake_case_       )
																	self.assertEqual(snake_case_      ,			snake_case_       )





			@slow
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Dict														= FSMTTokenizer.from_pretrained("""facebook/wmt19-ru-en"""      ,			do_lower_case=snake_case_       )
										A__					:    Any														= tokenizer.tokenize("""USA is United States of America"""       )
										A__					:    int														= ["""us""", """a</w>""", """is</w>""", """un""", """i""", """ted</w>""", """st""", """ates</w>""", """of</w>""", """am""", """er""", """ica</w>"""]
										self.assertListEqual(snake_case_      ,			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    _A(		lowerCAmelCase       ):
							if not isinstance(lowerCAmelCase ,     lowerCAmelCase       ):
														A__					:    int														= F'''Input value of [number={number}] must be an integer'''
														raise TypeError(lowerCAmelCase       )
							if number < 0 or number % 2 == 1:
														return False
							A__					:    List[Any]														= int(number**0.5       )
							return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
				import doctest

				doctest.testmod()





