



import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a_								=       get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")



@require_sentencepiece
@require_tokenizers
class 			__lowerCAmelCase  (						lowerCAmelCase__	,						unittest.TestCase ):
 lowerCAmelCase__							       =	PegasusTokenizer
 lowerCAmelCase__							       =	PegasusTokenizerFast
 lowerCAmelCase__							       =	True
 lowerCAmelCase__							       =	True




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    super().setUp()

    # We have a SentencePiece fixture for testing
    __lowerCamelCase    				=     PegasusTokenizer(__UpperCAmelCase					)
    tokenizer.save_pretrained(self.tmpdirname					)




 @cached_property
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    return PegasusTokenizer.from_pretrained('''google/pegasus-large'''					)




 def 							lowerCamelCase   (    self						,					**__UpperCAmelCase					):



    '''simple docstring'''
    return PegasusTokenizer.from_pretrained(self.tmpdirname						,					**__UpperCAmelCase					)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    return ("This is a test", "This is a test")




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     '''</s>'''
    __lowerCamelCase    				=     1

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




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     list(self.get_tokenizer().get_vocab().keys()					)

    self.assertEqual(vocab_keys[0]						,					'''<pad>'''					)
    self.assertEqual(vocab_keys[1]						,					'''</s>'''					)
    self.assertEqual(vocab_keys[-1]						,					'''v'''					)
    self.assertEqual(len(__UpperCAmelCase					)						,					1103					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    self.assertEqual(self.get_tokenizer().vocab_size						,					1103					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     self.rust_tokenizer_class.from_pretrained(self.tmpdirname					)
    __lowerCamelCase    				=     self.tokenizer_class.from_pretrained(self.tmpdirname					)
    __lowerCamelCase    				=     (
        '''Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'''
        ''' </s> <pad> <pad> <pad>'''
    )
    __lowerCamelCase    				=     rust_tokenizer([raw_input_str]						,					return_tensors=__UpperCAmelCase						,					add_special_tokens=__UpperCAmelCase					).input_ids[0]
    __lowerCamelCase    				=     py_tokenizer([raw_input_str]						,					return_tensors=__UpperCAmelCase						,					add_special_tokens=__UpperCAmelCase					).input_ids[0]
    self.assertListEqual(__UpperCAmelCase						,					__UpperCAmelCase					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     self._large_tokenizer
    # <mask_1> masks whole sentence while <mask_2> masks single word
    __lowerCamelCase    				=     '''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
    __lowerCamelCase    				=     [2, 413, 615, 114, 3, 1971, 113, 1679, 10710, 107, 1]
    __lowerCamelCase    				=     tokenizer([raw_input_str]						,					return_tensors=__UpperCAmelCase					).input_ids[0]
    self.assertListEqual(__UpperCAmelCase						,					__UpperCAmelCase					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     self._large_tokenizer
    # The tracebacks for the following asserts are **better** without messages or self.assertEqual
    assert tokenizer.vocab_size == 96103
    assert tokenizer.pad_token_id == 0
    assert tokenizer.eos_token_id == 1
    assert tokenizer.offset == 103
    assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
    assert tokenizer.unk_token == "<unk>"
    assert tokenizer.model_max_length == 1024
    __lowerCamelCase    				=     '''To ensure a smooth flow of bank resolutions.'''
    __lowerCamelCase    				=     [413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
    __lowerCamelCase    				=     tokenizer([raw_input_str]						,					return_tensors=__UpperCAmelCase					).input_ids[0]
    self.assertListEqual(__UpperCAmelCase						,					__UpperCAmelCase					)
    assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]					) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]




 @require_torch
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     ['''This is going to be way too long.''' * 150, '''short example''']
    __lowerCamelCase    				=     ['''not super long but more than 5 tokens''', '''tiny''']
    __lowerCamelCase    				=     self._large_tokenizer(__UpperCAmelCase						,					padding=__UpperCAmelCase						,					truncation=__UpperCAmelCase						,					return_tensors='''pt'''					)
    __lowerCamelCase    				=     self._large_tokenizer(
        text_target=__UpperCAmelCase						,					max_length=5						,					padding=__UpperCAmelCase						,					truncation=__UpperCAmelCase						,					return_tensors='''pt'''					)

    assert batch.input_ids.shape == (2, 1024)
    assert batch.attention_mask.shape == (2, 1024)
    assert targets["input_ids"].shape == (2, 5)
    assert len(__UpperCAmelCase					) == 2  # input_ids, attention_mask.




 @slow
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    # fmt: off
    __lowerCamelCase    				=     {'''input_ids''': [[38979, 143, 18485, 606, 130, 26669, 87686, 121, 54189, 1129, 111, 26669, 87686, 121, 9114, 14787, 121, 13249, 158, 592, 956, 121, 14621, 31576, 143, 62613, 108, 9688, 930, 43430, 11562, 62613, 304, 108, 11443, 897, 108, 9314, 17415, 63399, 108, 11443, 7614, 18316, 118, 4284, 7148, 12430, 143, 1400, 25703, 158, 111, 4284, 7148, 11772, 143, 21297, 1064, 158, 122, 204, 3506, 1754, 1133, 14787, 1581, 115, 33224, 4482, 111, 1355, 110, 29173, 317, 50833, 108, 20147, 94665, 111, 77198, 107, 1], [110, 62613, 117, 638, 112, 1133, 121, 20098, 1355, 79050, 13872, 135, 1596, 53541, 1352, 141, 13039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 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], [139, 1235, 2799, 18289, 17780, 204, 109, 9474, 1296, 107, 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]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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='''google/bigbird-pegasus-large-arxiv'''						,					revision='''ba85d0851d708441f91440d509690f1ab6353415'''						,					)



@require_sentencepiece
@require_tokenizers
class 			__lowerCAmelCase  (						lowerCAmelCase__	,						unittest.TestCase ):
 lowerCAmelCase__							       =	PegasusTokenizer
 lowerCAmelCase__							       =	PegasusTokenizerFast
 lowerCAmelCase__							       =	True
 lowerCAmelCase__							       =	True




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    super().setUp()

    # We have a SentencePiece fixture for testing
    __lowerCamelCase    				=     PegasusTokenizer(__UpperCAmelCase						,					offset=0						,					mask_token_sent=__UpperCAmelCase						,					mask_token='''[MASK]'''					)
    tokenizer.save_pretrained(self.tmpdirname					)




 @cached_property
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    return PegasusTokenizer.from_pretrained('''google/bigbird-pegasus-large-arxiv'''					)




 def 							lowerCamelCase   (    self						,					**__UpperCAmelCase					):



    '''simple docstring'''
    return PegasusTokenizer.from_pretrained(self.tmpdirname						,					**__UpperCAmelCase					)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    return ("This is a test", "This is a test")




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     self.rust_tokenizer_class.from_pretrained(self.tmpdirname					)
    __lowerCamelCase    				=     self.tokenizer_class.from_pretrained(self.tmpdirname					)
    __lowerCamelCase    				=     (
        '''Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'''
        ''' <pad> <pad> <pad>'''
    )
    __lowerCamelCase    				=     rust_tokenizer([raw_input_str]						,					return_tensors=__UpperCAmelCase						,					add_special_tokens=__UpperCAmelCase					).input_ids[0]
    __lowerCamelCase    				=     py_tokenizer([raw_input_str]						,					return_tensors=__UpperCAmelCase						,					add_special_tokens=__UpperCAmelCase					).input_ids[0]
    self.assertListEqual(__UpperCAmelCase						,					__UpperCAmelCase					)




 @require_torch
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     ['''This is going to be way too long.''' * 1000, '''short example''']
    __lowerCamelCase    				=     ['''not super long but more than 5 tokens''', '''tiny''']
    __lowerCamelCase    				=     self._large_tokenizer(__UpperCAmelCase						,					padding=__UpperCAmelCase						,					truncation=__UpperCAmelCase						,					return_tensors='''pt'''					)
    __lowerCamelCase    				=     self._large_tokenizer(
        text_target=__UpperCAmelCase						,					max_length=5						,					padding=__UpperCAmelCase						,					truncation=__UpperCAmelCase						,					return_tensors='''pt'''					)

    assert batch.input_ids.shape == (2, 4096)
    assert batch.attention_mask.shape == (2, 4096)
    assert targets["input_ids"].shape == (2, 5)
    assert len(__UpperCAmelCase					) == 2  # input_ids, attention_mask.




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     (
        '''This is an example string that is used to test the original TF implementation against the HF'''
        ''' implementation'''
    )

    __lowerCamelCase    				=     self._large_tokenizer(__UpperCAmelCase					).input_ids

    self.assertListEqual(
        __UpperCAmelCase						,					[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 25016, 3137, 464, 109, 26955, 3137, 1]						,					)











import os
import sys
import unittest


a_								=       os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
a_								=       os.path.join(git_repo_path, """src""", """transformers""")

a_								=       """
{0} = None
"""

a_								=       """
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


a_								=       """
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""



class 			__lowerCAmelCase  (						unittest.TestCase ):




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     find_backend('''    _import_structure["models.albert"].append("AlbertTokenizerFast")'''					)
    self.assertIsNone(__UpperCAmelCase					)

    __lowerCamelCase    				=     find_backend('''    if not is_tokenizers_available():'''					)
    self.assertEqual(__UpperCAmelCase						,					'''tokenizers'''					)

    __lowerCamelCase    				=     find_backend('''    if not is_tensorflow_text_available():'''					)
    self.assertEqual(__UpperCAmelCase						,					'''tensorflow_text'''					)

    __lowerCamelCase    				=     find_backend('''    if not (is_sentencepiece_available() and is_tokenizers_available()):'''					)
    self.assertEqual(__UpperCAmelCase						,					'''sentencepiece_and_tokenizers'''					)

    __lowerCamelCase    				=     find_backend(
        '''    if not (is_sentencepiece_available() and is_tensorflow_text_available()):'''					)
    self.assertEqual(__UpperCAmelCase						,					'''sentencepiece_and_tensorflow_text'''					)

    __lowerCamelCase    				=     find_backend(
        '''    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):'''					)
    self.assertEqual(__UpperCAmelCase						,					'''sentencepiece_and_tokenizers_and_vision'''					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     read_init()
    # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
    self.assertIn('''torch'''						,					__UpperCAmelCase					)
    self.assertIn('''tensorflow_text'''						,					__UpperCAmelCase					)
    self.assertIn('''sentencepiece_and_tokenizers'''						,					__UpperCAmelCase					)

    # Likewise, we can't assert on the exact content of a key
    self.assertIn('''BertModel'''						,					objects['''torch''']					)
    self.assertIn('''TFBertModel'''						,					objects['''tf''']					)
    self.assertIn('''FlaxBertModel'''						,					objects['''flax''']					)
    self.assertIn('''BertModel'''						,					objects['''torch''']					)
    self.assertIn('''TFBertTokenizer'''						,					objects['''tensorflow_text''']					)
    self.assertIn('''convert_slow_tokenizer'''						,					objects['''sentencepiece_and_tokenizers''']					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     create_dummy_object('''CONSTANT'''						,					'''\'torch\''''					)
    self.assertEqual(__UpperCAmelCase						,					'''\nCONSTANT = None\n'''					)

    __lowerCamelCase    				=     create_dummy_object('''function'''						,					'''\'torch\''''					)
    self.assertEqual(
        __UpperCAmelCase						,					'''\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'''					)

    __lowerCamelCase    				=     '''
class FakeClass(metaclass=DummyObject):
    _backends = \'torch\'

    def __init__(self, *args, **kwargs):
        requires_backends(self, \'torch\')
'''
    __lowerCamelCase    				=     create_dummy_object('''FakeClass'''						,					'''\'torch\''''					)
    self.assertEqual(__UpperCAmelCase						,					__UpperCAmelCase					)




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     '''# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, ["torch"])


class FakeClass(metaclass=DummyObject):
    _backends = ["torch"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch"])
'''
    __lowerCamelCase    				=     create_dummy_files({'''torch''': ['''CONSTANT''', '''function''', '''FakeClass''']}					)
    self.assertEqual(dummy_files['''torch''']						,					__UpperCAmelCase					)






