





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


__lowercase  :   Tuple						      =get_tests_dir("""fixtures/test_sentencepiece.model""")

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

if is_torch_available():
     __lowercase  :   int						      ="""pt"""
elif is_tf_available():
     __lowercase  :   Tuple						      ="""tf"""
else:
     __lowercase  :   List[Any]						      ="""jax"""


@require_sentencepiece
class      A       (	__lowercase		,      unittest.TestCase						):
      _snake_case							     =MarianTokenizer
      _snake_case							     =False
      _snake_case							     =True



      def 	lowerCAmelCase__    (	self:						Optional[Any]       )						->    Optional[Any]:
         '''simple docstring'''

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

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



      def 	lowerCAmelCase__    (	self:						Optional[Any]		,  **_lowerCAmelCase:						Union[str, Any]       )						->    MarianTokenizer:
         '''simple docstring'''

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



      def 	lowerCAmelCase__    (	self:						int		,  _lowerCAmelCase:						str       )						->    int:
         '''simple docstring'''

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



      def 	lowerCAmelCase__    (	self:						List[str]       )						->    Dict:
         '''simple docstring'''

         UpperCAmelCase_											="</s>"
         UpperCAmelCase_											=0

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



      def 	lowerCAmelCase__    (	self:						Any       )						->    int:
         '''simple docstring'''

         UpperCAmelCase_											=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(_lowerCAmelCase       )		,  9       )



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

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



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

         UpperCAmelCase_											=MarianTokenizer.from_pretrained(F'{ORG_NAME}opus-mt-en-de'       )
         UpperCAmelCase_											=en_de_tokenizer(["I am a small frog"]		,  return_tensors=_lowerCAmelCase       )
         self.assertIsInstance(_lowerCAmelCase		,  _lowerCAmelCase       )
         UpperCAmelCase_											=[38, 121, 14, 697, 3_8848, 0]
         self.assertListEqual(_lowerCAmelCase		,  batch.input_ids[0]       )

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



      def 	lowerCAmelCase__    (	self:						str       )						->    int:
         '''simple docstring'''

         UpperCAmelCase_											=self.get_tokenizer()

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



      def 	lowerCAmelCase__    (	self:						Any       )						->    Dict:
         '''simple docstring'''

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



      @slow
      def 	lowerCAmelCase__    (	self:						Optional[int]       )						->    Any:
         '''simple docstring'''

         UpperCAmelCase_											={"input_ids": [[4_3495, 462, 20, 4_2164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 3_8999, 6, 8, 464, 132, 1703, 492, 13, 4669, 3_7867, 13, 7525, 27, 1593, 988, 13, 3_3972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 1_2338, 2, 1_3958, 387, 2, 3629, 6953, 188, 2900, 2, 1_3958, 8011, 1_1501, 23, 8460, 4073, 3_4009, 20, 435, 1_1439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 3_7867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 2_6453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 1_0767, 6, 316, 304, 4239, 3, 0], [148, 1_5722, 19, 1839, 12, 1350, 13, 2_2327, 5082, 5418, 4_7567, 3_5938, 59, 318, 1_9552, 108, 2183, 54, 1_4976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 1_9088, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100], [36, 6395, 1_2570, 3_9147, 1_1597, 6, 266, 4, 4_5405, 7296, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100]], "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=_lowerCAmelCase		,  model_name="Helsinki-NLP/opus-mt-en-de"		,  revision="1a8c2263da11e68e50938f97e10cd57820bd504c"		,  decode_kwargs={"use_source_tokenizer": True}		,  )






      def 	lowerCAmelCase__    (	self:						List[str]       )						->    int:
         '''simple docstring'''

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

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

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

         UpperCAmelCase_											=tokenizer(_lowerCAmelCase       ).input_ids
         self.assertListEqual(_lowerCAmelCase		,  _lowerCAmelCase       )

         UpperCAmelCase_											=tokenizer(text_target=_lowerCAmelCase       ).input_ids
         self.assertListEqual(_lowerCAmelCase		,  _lowerCAmelCase       )

         UpperCAmelCase_											=tokenizer.decode(_lowerCAmelCase		,  skip_special_tokens=_lowerCAmelCase       )
         self.assertEqual(_lowerCAmelCase		,  _lowerCAmelCase       )











from __future__ import annotations




def     a__ (					lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_						,       UpperCAmelCase_											=set(lowercase__  ), [start]

   while stack:
      UpperCAmelCase_											=stack.pop()
      explored.add(lowercase__  )
      # Differences from BFS:
      # 1) pop last element instead of first one
      # 2) add adjacent elements to stack without exploring them
      for adj in reversed(graph[v]  ):
         if adj not in explored:
            stack.append(lowercase__  )
   return explored


__lowercase  :   Dict						      ={
    """A""": ["""B""", """C""", """D"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B""", """D"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E""", """G"""],
    """G""": ["""F"""],
}

if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(depth_first_search(G, """A"""))




