





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


SCREAMING_SNAKE_CASE__							:      int         =    get_tests_dir("""fixtures/test_sentencepiece.model""")

SCREAMING_SNAKE_CASE__							:      Dict         =    {"""target_lang""": """fi""", """source_lang""": """en"""}
SCREAMING_SNAKE_CASE__							:      List[Any]         =    """>>zh<<"""
SCREAMING_SNAKE_CASE__							:      int         =    """Helsinki-NLP/"""

if is_torch_available():
  SCREAMING_SNAKE_CASE__							:      int         =    """pt"""
elif is_tf_available():
  SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    """tf"""
else:
  SCREAMING_SNAKE_CASE__							:      Any         =    """jax"""







@require_sentencepiece
class 	__lowerCAmelCase      (       _UpperCamelCase		,unittest.TestCase	):
   _UpperCamelCase			:    List[Any]  		=					MarianTokenizer
   _UpperCamelCase			:    List[Any]  		=					False
   _UpperCamelCase			:    Dict  		=					True





   def 						_snake_case			(			self   )					->	Optional[int]:
      """simple docstring"""





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

      a__						:    Dict   		=	MarianTokenizer.from_pretrained(self.tmpdirname   )
      tokenizer.save_pretrained(self.tmpdirname   )





   def 						_snake_case			(			self       ,      **snake_case   )					->	MarianTokenizer:
      """simple docstring"""





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





   def 						_snake_case			(			self       ,      snake_case   )					->	Dict:
      """simple docstring"""





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





   def 						_snake_case			(			self   )					->	List[Any]:
      """simple docstring"""





      a__						:    int   		=	"</s>"
      a__						:    Union[str, Any]   		=	0

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





   def 						_snake_case			(			self   )					->	Optional[int]:
      """simple docstring"""





      a__						:    Any   		=	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(snake_case   )       ,      9   )





   def 						_snake_case			(			self   )					->	List[str]:
      """simple docstring"""





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





   def 						_snake_case			(			self   )					->	int:
      """simple docstring"""





      a__						:    Optional[int]   		=	MarianTokenizer.from_pretrained(F"""{ORG_NAME}opus-mt-en-de"""   )
      a__						:    int   		=	en_de_tokenizer(["I am a small frog"]       ,      return_tensors=snake_case   )
      self.assertIsInstance(snake_case       ,      snake_case   )
      a__						:    List[str]   		=	[38, 121, 14, 697, 38_848, 0]
      self.assertListEqual(snake_case       ,      batch.input_ids[0]   )

      a__						:    List[str]   		=	tempfile.mkdtemp()
      en_de_tokenizer.save_pretrained(snake_case   )
      a__						:    Optional[Any]   		=	[x.name for x in Path(snake_case   ).glob("*"   )]
      self.assertIn("source.spm"       ,      snake_case   )
      MarianTokenizer.from_pretrained(snake_case   )





   def 						_snake_case			(			self   )					->	Union[str, Any]:
      """simple docstring"""





      a__						:    Union[str, Any]   		=	self.get_tokenizer()

      a__						:    Tuple   		=	tok(
          ["I am a small frog" * 1_000, "I am a small frog"]       ,      padding=snake_case       ,      truncation=snake_case       ,      return_tensors=snake_case   )
      self.assertIsInstance(snake_case       ,      snake_case   )
      self.assertEqual(batch.input_ids.shape       ,      (2, 512)   )





   def 						_snake_case			(			self   )					->	Tuple:
      """simple docstring"""





      a__						:    str   		=	self.get_tokenizer()
      a__						:    Dict   		=	tok(["I am a tiny frog", "I am a small frog"]       ,      padding=snake_case       ,      return_tensors=snake_case   )
      self.assertIsInstance(snake_case       ,      snake_case   )
      self.assertEqual(batch_smaller.input_ids.shape       ,      (2, 10)   )





   @slow
   def 						_snake_case			(			self   )					->	List[Any]:
      """simple docstring"""





      a__						:    Tuple   		=	{"input_ids": [[43_495, 462, 20, 42_164, 1_369, 52, 464, 132, 1_703, 492, 13, 7_491, 38_999, 6, 8, 464, 132, 1_703, 492, 13, 4_669, 37_867, 13, 7_525, 27, 1_593, 988, 13, 33_972, 7_029, 6, 20, 8_251, 383, 2, 270, 5_866, 3_788, 2, 2_353, 8_251, 12_338, 2, 13_958, 387, 2, 3_629, 6_953, 188, 2_900, 2, 13_958, 8_011, 11_501, 23, 8_460, 4_073, 34_009, 20, 435, 11_439, 27, 8, 8_460, 4_073, 6_004, 20, 9_988, 375, 27, 33, 266, 1_945, 1_076, 1_350, 37_867, 3_288, 5, 577, 1_076, 4_374, 8, 5_082, 5, 26_453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10_767, 6, 316, 304, 4_239, 3, 0], [148, 15_722, 19, 1_839, 12, 1_350, 13, 22_327, 5_082, 5_418, 47_567, 35_938, 59, 318, 19_552, 108, 2_183, 54, 14_976, 4_835, 32, 547, 1_114, 8, 315, 2_417, 5, 92, 19_088, 3, 0, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100], [36, 6_395, 12_570, 39_147, 11_597, 6, 266, 4, 45_405, 7_296, 3, 0, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100]], "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=snake_case       ,      model_name="Helsinki-NLP/opus-mt-en-de"       ,      revision="1a8c2263da11e68e50938f97e10cd57820bd504c"       ,      decode_kwargs={"use_source_tokenizer": True}       ,      )





   def 						_snake_case			(			self   )					->	List[Any]:
      """simple docstring"""





      a__						:    Optional[Any]   		=	MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs"   )

      a__						:    Union[str, Any]   		=	"Tämä on testi"
      a__						:    List[Any]   		=	"This is a test"

      a__						:    Dict   		=	[76, 7, 2_047, 2]
      a__						:    str   		=	[69, 12, 11, 940, 2]

      a__						:    List[Any]   		=	tokenizer(snake_case   ).input_ids
      self.assertListEqual(snake_case       ,      snake_case   )

      a__						:    Optional[Any]   		=	tokenizer(text_target=snake_case   ).input_ids
      self.assertListEqual(snake_case       ,      snake_case   )

      a__						:    Optional[Any]   		=	tokenizer.decode(snake_case       ,      skip_special_tokens=snake_case   )
      self.assertEqual(snake_case       ,      snake_case   )








def    _A	(   lowerCamelCase = 200 ):
   a__						:    List[str]   		=	[1, 2, 5, 10, 20, 50, 100, 200]
   a__						:    Dict   		=	[0] * (pence + 1)
   a__						:    int   		=	1  # base case: 1 way to make 0 pence

   for coin in coins:
      for i in range(lowerCamelCase				,			pence + 1				,			1 ):
         number_of_ways[i] += number_of_ways[i - coin]
   return number_of_ways[pence]


if __name__ == "__main__":
  assert solution(2_0_0) == 7_3_6_8_2

