"""simple docstring"""


import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase_:					List[str]     =					get_tests_dir("fixtures/test_sentencepiece.model")






@require_sentencepiece
@require_tokenizers
class    a__    (   _a					,					unittest.TestCase	):
   snake_case_							=      XLMRobertaTokenizer
   snake_case_							=      XLMRobertaTokenizerFast
   snake_case_							=      True
   snake_case_							=      True


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase__				 =							XLMRobertaTokenizer(_UpperCAmelCase,				keep_accents=_UpperCAmelCase  )
        tokenizer.save_pretrained(self.tmpdirname  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							"<pad>"
        lowercase__				 =							1

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


   def 	snake_case__	(     self  ):
        '''simple docstring'''



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

        self.assertEqual(vocab_keys[0],				"<s>"  )
        self.assertEqual(vocab_keys[1],				"<pad>"  )
        self.assertEqual(vocab_keys[-1],				"<mask>"  )
        self.assertEqual(len(_UpperCAmelCase  ),				1002  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        self.assertEqual(self.get_tokenizer().vocab_size,				1002  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							XLMRobertaTokenizer(_UpperCAmelCase,				keep_accents=_UpperCAmelCase  )

        lowercase__				 =							tokenizer.tokenize("This is a test"  )
        self.assertListEqual(_UpperCAmelCase,				["▁This", "▁is", "▁a", "▁t", "est"]  )

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(_UpperCAmelCase  ),				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]],				)

        lowercase__				 =							tokenizer.tokenize("I was born in 92000, and this is falsé."  )
        self.assertListEqual(
            _UpperCAmelCase,				[
                SPIECE_UNDERLINE + "I",
                SPIECE_UNDERLINE + "was",
                SPIECE_UNDERLINE + "b",
                "or",
                "n",
                SPIECE_UNDERLINE + "in",
                SPIECE_UNDERLINE + "",
                "9",
                "2",
                "0",
                "0",
                "0",
                ",",
                SPIECE_UNDERLINE + "and",
                SPIECE_UNDERLINE + "this",
                SPIECE_UNDERLINE + "is",
                SPIECE_UNDERLINE + "f",
                "al",
                "s",
                "é",
                ".",
            ],				)
        lowercase__				 =							tokenizer.convert_tokens_to_ids(_UpperCAmelCase  )
        self.assertListEqual(
            _UpperCAmelCase,				[
                value + tokenizer.fairseq_offset
                for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
                #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
            ],				)

        lowercase__				 =							tokenizer.convert_ids_to_tokens(_UpperCAmelCase  )
        self.assertListEqual(
            _UpperCAmelCase,				[
                SPIECE_UNDERLINE + "I",
                SPIECE_UNDERLINE + "was",
                SPIECE_UNDERLINE + "b",
                "or",
                "n",
                SPIECE_UNDERLINE + "in",
                SPIECE_UNDERLINE + "",
                "<unk>",
                "2",
                "0",
                "0",
                "0",
                ",",
                SPIECE_UNDERLINE + "and",
                SPIECE_UNDERLINE + "this",
                SPIECE_UNDERLINE + "is",
                SPIECE_UNDERLINE + "f",
                "al",
                "s",
                "<unk>",
                ".",
            ],				)


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        if not self.test_slow_tokenizer:
             # as we don't have a slow version, we can't compare the outputs between slow and fast versions
             return

        lowercase__				 =							(self.rust_tokenizer_class, "hf-internal-testing/tiny-xlm-roberta", {})
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
                  lowercase__				 =							self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase,				**_UpperCAmelCase  )
                  lowercase__				 =							self.tokenizer_class.from_pretrained(_UpperCAmelCase,				**_UpperCAmelCase  )

                  lowercase__				 =							tempfile.mkdtemp()

                  lowercase__				 =							tokenizer_r.save_pretrained(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer_p.save_pretrained(_UpperCAmelCase  )

                  # Checks it save with the same files + the tokenizer.json file for the fast one
                  self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files  )  )
                  lowercase__				 =							tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f  )
                  self.assertSequenceEqual(_UpperCAmelCase,				_UpperCAmelCase  )

                  # Checks everything loads correctly in the same way
                  lowercase__				 =							tokenizer_r.from_pretrained(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer_p.from_pretrained(_UpperCAmelCase  )

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                       self.assertTrue(hasattr(_UpperCAmelCase,				_UpperCAmelCase  )  )
                       # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
                       # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

                  shutil.rmtree(_UpperCAmelCase  )

                  # Save tokenizer rust, legacy_format=True
                  lowercase__				 =							tempfile.mkdtemp()

                  lowercase__				 =							tokenizer_r.save_pretrained(_UpperCAmelCase,				legacy_format=_UpperCAmelCase  )
                  lowercase__				 =							tokenizer_p.save_pretrained(_UpperCAmelCase  )

                  # Checks it save with the same files
                  self.assertSequenceEqual(_UpperCAmelCase,				_UpperCAmelCase  )

                  # Checks everything loads correctly in the same way
                  lowercase__				 =							tokenizer_r.from_pretrained(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer_p.from_pretrained(_UpperCAmelCase  )

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                       self.assertTrue(hasattr(_UpperCAmelCase,				_UpperCAmelCase  )  )

                  shutil.rmtree(_UpperCAmelCase  )

                  # Save tokenizer rust, legacy_format=False
                  lowercase__				 =							tempfile.mkdtemp()

                  lowercase__				 =							tokenizer_r.save_pretrained(_UpperCAmelCase,				legacy_format=_UpperCAmelCase  )
                  lowercase__				 =							tokenizer_p.save_pretrained(_UpperCAmelCase  )

                  # Checks it saved the tokenizer.json file
                  self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files  )  )

                  # Checks everything loads correctly in the same way
                  lowercase__				 =							tokenizer_r.from_pretrained(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer_p.from_pretrained(_UpperCAmelCase  )

                  # Check special tokens are set accordingly on Rust and Python
                  for key in tokenizer_pp.special_tokens_map:
                       self.assertTrue(hasattr(_UpperCAmelCase,				_UpperCAmelCase  )  )

                  shutil.rmtree(_UpperCAmelCase  )


   @cached_property
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        return XLMRobertaTokenizer.from_pretrained("xlm-roberta-base"  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        with tempfile.NamedTemporaryFile() as f:
             shutil.copyfile(_UpperCAmelCase,				f.name  )
             lowercase__				 =							XLMRobertaTokenizer(f.name,				keep_accents=_UpperCAmelCase  )
             lowercase__				 =							pickle.dumps(_UpperCAmelCase  )
        pickle.loads(_UpperCAmelCase  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        if not self.test_rust_tokenizer:
             return

        lowercase__				 =							self.get_tokenizer()
        lowercase__				 =							self.get_rust_tokenizer()

        lowercase__				 =							"I was born in 92000, and this is falsé."

        lowercase__				 =							tokenizer.tokenize(_UpperCAmelCase  )
        lowercase__				 =							rust_tokenizer.tokenize(_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

        lowercase__				 =							tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
        lowercase__				 =							rust_tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

        lowercase__				 =							self.get_rust_tokenizer()
        lowercase__				 =							tokenizer.encode(_UpperCAmelCase  )
        lowercase__				 =							rust_tokenizer.encode(_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )


   @slow
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							"Hello World!"
        lowercase__				 =							[0, 3_5378, 6661, 38, 2]
        # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
        # xlmr.eval()
        # xlmr.encode(symbols)

        self.assertListEqual(_UpperCAmelCase,				self.big_tokenizer.encode(_UpperCAmelCase  )  )


   @slow
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							(
            "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
            " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
        )
        lowercase__				 =							[
            0,
            3293,
            83,
            10,
            4552,
            4989,
            7986,
            678,
            10,
            5915,
            111,
            17_9459,
            12_4850,
            4,
            6044,
            237,
            12,
            6,
            5,
            6,
            4,
            6780,
            705,
            15,
            1388,
            44,
            378,
            1_0114,
            711,
            152,
            20,
            6,
            5,
            2_2376,
            642,
            1221,
            1_5190,
            3_4153,
            450,
            5608,
            959,
            1119,
            5_7702,
            136,
            186,
            47,
            1098,
            2_9367,
            47,
            # 4426, # What fairseq tokenizes from "<unk>": "_<"
            # 3678, # What fairseq tokenizes from "<unk>": "unk"
            # 2740, # What fairseq tokenizes from "<unk>": ">"
            3,  # What we tokenize from "<unk>": "<unk>"
            6,  # Residue from the tokenization: an extra sentencepiece underline
            4,
            6044,
            237,
            6284,
            5_0901,
            528,
            31,
            90,
            34,
            927,
            2,
        ]
        # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
        # xlmr.eval()
        # xlmr.encode(symbols)

        self.assertListEqual(_UpperCAmelCase,				self.big_tokenizer.encode(_UpperCAmelCase  )  )


   @slow
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							{"input_ids": [[0, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [0, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], "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, 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], [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, 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=_UpperCAmelCase,				model_name="xlm-roberta-base",				revision="d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3",				)





"""simple docstring"""


from typing import Any

import numpy as np







def 					__a   (		A      ):






     '''simple docstring'''



     return np.array_equal(A    ,				matrix.conjugate().T      )







def 					__a   (		A    ,				A      ):






     '''simple docstring'''



     lowercase__				 =							v.conjugate().T
     lowercase__				 =							v_star.dot(A      )
     assert isinstance(A    ,				np.ndarray      )
     return (v_star_dot.dot(A      )) / (v_star.dot(A      ))







def 					__a   (		):






     '''simple docstring'''



     lowercase__				 =							np.array([[2, 2 + 1j, 4], [2 - 1j, 3, 1j], [4, -1j, 1]]      )
     lowercase__				 =							np.array([[1], [2], [3]]      )
     assert is_hermitian(A      ), f'''{a} is not hermitian.'''
     print(rayleigh_quotient(A    ,				A      )      )

     lowercase__				 =							np.array([[1, 2, 4], [2, 3, -1], [4, -1, 1]]      )
     assert is_hermitian(A      ), f'''{a} is not hermitian.'''
     assert rayleigh_quotient(A    ,				A      ) == float(3      )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 tests()




