




import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin

class 		lowercase_       (	lowerCAmelCase__						,							unittest.TestCase				):
					__UpperCamelCase     	= SpeechaTextaTokenizer
					__UpperCamelCase     	= False




					def     _lowercase						(   self:		str):


									'''simple docstring'''


									super().setUp()

									__lowerCAmelCase					=  """<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab""".split(""" """)
									__lowerCAmelCase					=  ["""he re</w> 123""", """here a 1456"""]
									__lowerCAmelCase					=  dict(zip(_lowercase,     range(len(_lowercase))))

									__lowerCAmelCase					=  {"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}

									__lowerCAmelCase					=  tempfile.mkdtemp()
									__lowerCAmelCase					=  os.path.join(self.tmpdirname,     VOCAB_FILES_NAMES["""vocab_file"""])
									__lowerCAmelCase					=  os.path.join(self.tmpdirname,     VOCAB_FILES_NAMES["""merges_file"""])

									with open(self.vocab_file,     """w""",     encoding="""utf-8""") as fp:
													fp.write(json.dumps(_lowercase) + """\n""")

									with open(self.merges_file,     """w""") as fp:
													fp.write("""\n""".join(_lowercase))




					def     _lowercase						(   self:		Any):


									'''simple docstring'''


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

									self.assertEqual(vocab_keys[0],     """<s>""")
									self.assertEqual(vocab_keys[1],     """<pad>""")
									self.assertEqual(vocab_keys[-1],     """vocab""")
									self.assertEqual(len(_lowercase),     14)




					def     _lowercase						(   self:		List[Any]):


									'''simple docstring'''


									self.assertEqual(self.get_tokenizer().vocab_size,     14)




					def     _lowercase						(   self:		str):


									'''simple docstring'''


									__lowerCAmelCase					=  SpeechaTextaTokenizer.from_pretrained(self.tmpdirname)

									# make sure @@ is correctly concatenated
									__lowerCAmelCase					=  [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
									__lowerCAmelCase					=  tokenizer.decode(_lowercase)

									self.assertTrue(output_string == """herecouple words ofthe""")




					def     _lowercase						(   self:		Tuple):


									'''simple docstring'''


									__lowerCAmelCase					=  SpeechaTextaTokenizer.from_pretrained(self.tmpdirname)

									with tempfile.TemporaryDirectory() as tmp_dirname:
													tokenizer.save_pretrained(_lowercase)
													os.remove(os.path.join(_lowercase,     """merges.txt"""))

													# load tokenizer without merges file should not throw an error
													__lowerCAmelCase					=  SpeechaTextaTokenizer.from_pretrained(_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dirname:
													# save tokenizer and load again
													tokenizer.save_pretrained(_lowercase)
													__lowerCAmelCase					=  SpeechaTextaTokenizer.from_pretrained(_lowercase)

									self.assertIsNotNone(_lowercase)







					def     _lowercase						(   self:		Tuple):


									'''simple docstring'''


									if not self.test_slow_tokenizer:
													return

									__lowerCAmelCase					=  inspect.signature(self.tokenizer_class.__init__)
									__lowerCAmelCase					=  self.get_tokenizer()

									for parameter_name, parameter in signature.parameters.items():
													if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
																	self.assertIn(_lowercase,     tokenizer.init_kwargs)











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_lowerCamelCase							=      {'''configuration_cvt''': ['''CVT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CvtConfig''']}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase							=      [
        '''CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''CvtForImageClassification''',
        '''CvtModel''',
        '''CvtPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase							=      [
        '''TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFCvtForImageClassification''',
        '''TFCvtModel''',
        '''TFCvtPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_cvt import (
            CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
            CvtForImageClassification,
            CvtModel,
            CvtPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_cvt import (
            TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFCvtForImageClassification,
            TFCvtModel,
            TFCvtPreTrainedModel,
        )


else:
    import sys

    _lowerCamelCase							=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
