

import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
	from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase__		      =       get_tests_dir("""fixtures/test_sentencepiece.model""")

lowerCAmelCase__		      =       {"""target_lang""": """fi""", """source_lang""": """en"""}
lowerCAmelCase__		      =       """>>zh<<"""
lowerCAmelCase__		      =       """Helsinki-NLP/"""

if is_torch_available():
	lowerCAmelCase__		      =       """pt"""
elif is_tf_available():
	lowerCAmelCase__		      =       """tf"""
else:
	lowerCAmelCase__		      =       """jax"""

@require_sentencepiece
class     a__  (    snake_case							,		unittest.TestCase	):
			"""simple docstring"""







			__lowerCamelCase       				=				MarianTokenizer
			__lowerCamelCase       				=				False
			__lowerCamelCase       				=				True


			def    UpperCamelCase						(			self				)     ->  int:
							'''simple docstring'''






							super().setUp()
							A__						=	["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
							A__						=	dict(zip(lowercase					,					range(len(lowercase				)				)				)				)
							A__						=	Path(self.tmpdirname				)
							save_json(lowercase					,					save_dir / VOCAB_FILES_NAMES["vocab"]				)
							save_json(lowercase					,					save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"]				)
							if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
											copyfile(lowercase					,					save_dir / VOCAB_FILES_NAMES["source_spm"]				)
											copyfile(lowercase					,					save_dir / VOCAB_FILES_NAMES["target_spm"]				)

							A__						=	MarianTokenizer.from_pretrained(self.tmpdirname				)
							tokenizer.save_pretrained(self.tmpdirname				)


			def    UpperCamelCase						(			self					,					**lowercase				)     ->  MarianTokenizer:
							'''simple docstring'''






							return MarianTokenizer.from_pretrained(self.tmpdirname					,					**lowercase				)


			def    UpperCamelCase						(			self					,					lowercase				)     ->  str:
							'''simple docstring'''






							return (
							    "This is a test",
							    "This is a test",
							)


			def    UpperCamelCase						(			self				)     ->  Tuple:
							'''simple docstring'''






							A__						=	"</s>"
							A__						=	0

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase				)					,					lowercase				)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase				)					,					lowercase				)


			def    UpperCamelCase						(			self				)     ->  Optional[int]:
							'''simple docstring'''






							A__						=	list(self.get_tokenizer().get_vocab().keys()				)

							self.assertEqual(vocab_keys[0]					,					"</s>"				)
							self.assertEqual(vocab_keys[1]					,					"<unk>"				)
							self.assertEqual(vocab_keys[-1]					,					"<pad>"				)
							self.assertEqual(len(lowercase				)					,					9				)


			def    UpperCamelCase						(			self				)     ->  List[Any]:
							'''simple docstring'''






							self.assertEqual(self.get_tokenizer().vocab_size					,					9				)


			def    UpperCamelCase						(			self				)     ->  Optional[int]:
							'''simple docstring'''






							A__						=	MarianTokenizer.from_pretrained(F'{ORG_NAME}opus-mt-en-de'				)
							A__						=	en_de_tokenizer(["I am a small frog"]					,					return_tensors=lowercase				)
							self.assertIsInstance(lowercase					,					lowercase				)
							A__						=	[38, 121, 14, 697, 38848, 0]
							self.assertListEqual(lowercase					,					batch.input_ids[0]				)

							A__						=	tempfile.mkdtemp()
							en_de_tokenizer.save_pretrained(lowercase				)
							A__						=	[x.name for x in Path(lowercase				).glob("*"				)]
							self.assertIn("source.spm"					,					lowercase				)
							MarianTokenizer.from_pretrained(lowercase				)


			def    UpperCamelCase						(			self				)     ->  Union[str, Any]:
							'''simple docstring'''






							A__						=	self.get_tokenizer()

							A__						=	tok(
							    ["I am a small frog" * 1000, "I am a small frog"]					,					padding=lowercase					,					truncation=lowercase					,					return_tensors=lowercase				)
							self.assertIsInstance(lowercase					,					lowercase				)
							self.assertEqual(batch.input_ids.shape					,					(2, 512)				)


			def    UpperCamelCase						(			self				)     ->  List[Any]:
							'''simple docstring'''






							A__						=	self.get_tokenizer()
							A__						=	tok(["I am a tiny frog", "I am a small frog"]					,					padding=lowercase					,					return_tensors=lowercase				)
							self.assertIsInstance(lowercase					,					lowercase				)
							self.assertEqual(batch_smaller.input_ids.shape					,					(2, 10)				)


			@slow
			def    UpperCamelCase						(			self				)     ->  List[str]:
							'''simple docstring'''






							A__						=	{"input_ids": [[43495, 462, 20, 42164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 38999, 6, 8, 464, 132, 1703, 492, 13, 4669, 37867, 13, 7525, 27, 1593, 988, 13, 33972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 12338, 2, 13958, 387, 2, 3629, 6953, 188, 2900, 2, 13958, 8011, 11501, 23, 8460, 4073, 34009, 20, 435, 11439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 37867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 26453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10767, 6, 316, 304, 4239, 3, 0], [148, 15722, 19, 1839, 12, 1350, 13, 22327, 5082, 5418, 47567, 35938, 59, 318, 19552, 108, 2183, 54, 14976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 19088, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100], [36, 6395, 12570, 39147, 11597, 6, 266, 4, 45405, 7296, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=lowercase					,					model_name="Helsinki-NLP/opus-mt-en-de"					,					revision="1a8c2263da11e68e50938f97e10cd57820bd504c"					,					decode_kwargs={"use_source_tokenizer": True}					,					)


			def    UpperCamelCase						(			self				)     ->  str:
							'''simple docstring'''






							A__						=	MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs"				)

							A__						=	"Tämä on testi"
							A__						=	"This is a test"

							A__						=	[76, 7, 2047, 2]
							A__						=	[69, 12, 11, 940, 2]

							A__						=	tokenizer(lowercase				).input_ids
							self.assertListEqual(lowercase					,					lowercase				)

							A__						=	tokenizer(text_target=lowercase				).input_ids
							self.assertListEqual(lowercase					,					lowercase				)

							A__						=	tokenizer.decode(lowercase					,					skip_special_tokens=lowercase				)
							self.assertEqual(lowercase					,					lowercase				)


'''simple docstring'''





import os
from math import logaa





def 	lowerCAmelCase_				(					snake_case_       : str = "base_exp.txt"			)    ->      int:


     '''simple docstring'''




     UpperCAmelCase_           =   0
     UpperCAmelCase_           =   0
     for i, line in enumerate(open(os.path.join(os.path.dirname(snake_case_			)					,    snake_case_			)			)			):
          UpperCAmelCase_    , UpperCAmelCase_           =   list(map(snake_case_					,    line.split(","			)			)			)
          if x * logaa(snake_case_			) > largest:
               UpperCAmelCase_           =   x * logaa(snake_case_			)
               UpperCAmelCase_           =   i + 1
     return result


if __name__ == "__main__":
    print(solution())




