


import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property







class   lowerCAmelCase__ (       unittest.TestCase):




     '''simple docstring'''


     @cached_property
     def 				_lowerCamelCase				(		self)    ->       Union[str, Any]:
            return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B")


     @cached_property
     def 				_lowerCamelCase				(		self)    ->       List[Any]:
            return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B")


     def 				_lowerCamelCase				(		self)    ->       Tuple:
            _A   : Tuple       					=				self.tokenizer_ab
            _A   : List[Any]       					=				" I am a small frog."
            _A   : Optional[int]       					=				tok([src_text]				,		padding=__lowerCamelCase				,		truncation=__lowerCamelCase)["input_ids"]
            _A   : Union[str, Any]       					=				tok.batch_decode(__lowerCamelCase				,		skip_special_tokens=__lowerCamelCase				,		clean_up_tokenization_spaces=__lowerCamelCase)[0]
            assert src_text == decoded


     def 				_lowerCamelCase				(		self)    ->       Tuple:
            _A   : Tuple       					=				self.rust_tokenizer_ab
            _A   : List[str]       					=				" I am a small frog."
            _A   : Dict       					=				tok([src_text]				,		padding=__lowerCamelCase				,		truncation=__lowerCamelCase)["input_ids"]
            _A   : int       					=				tok.batch_decode(__lowerCamelCase				,		skip_special_tokens=__lowerCamelCase				,		clean_up_tokenization_spaces=__lowerCamelCase)[0]
            assert src_text == decoded


     def 				_lowerCamelCase				(		self)    ->       str:
            assert self.tokenizer_ab.add_prefix_space
            assert self.tokenizer_ab([" Sam", "Sam"]).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]


     def 				_lowerCamelCase				(		self)    ->       Optional[Any]:
            assert self.rust_tokenizer_ab.add_prefix_space
            assert self.rust_tokenizer_ab([" Sam", "Sam"]).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]




from typing import TYPE_CHECKING

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


lowerCAmelCase__   	=				{
    'configuration_deta': ['DETA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DetaConfig'],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__   	=				['DetaImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__   	=				[
        'DETA_PRETRAINED_MODEL_ARCHIVE_LIST',
        'DetaForObjectDetection',
        'DetaModel',
        'DetaPreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .image_processing_deta import DetaImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_deta import (
            DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
            DetaForObjectDetection,
            DetaModel,
            DetaPreTrainedModel,
        )

else:
    import sys

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