





"""simple docstring"""


import unittest

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



class      lowercase_				(     unittest.TestCase							):

       @cached_property
       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B"     )

       @cached_property
       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B"     )

       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        snake_case__    							=				self.tokenizer_ab
        snake_case__    							=				" I am a small frog."
        snake_case__    							=				tok([src_text]   ,					padding=__SCREAMING_SNAKE_CASE   ,					truncation=__SCREAMING_SNAKE_CASE     )["input_ids"]
        snake_case__    							=				tok.batch_decode(__SCREAMING_SNAKE_CASE   ,					skip_special_tokens=__SCREAMING_SNAKE_CASE   ,					clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE     )[0]
        assert src_text == decoded

       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        snake_case__    							=				self.rust_tokenizer_ab
        snake_case__    							=				" I am a small frog."
        snake_case__    							=				tok([src_text]   ,					padding=__SCREAMING_SNAKE_CASE   ,					truncation=__SCREAMING_SNAKE_CASE     )["input_ids"]
        snake_case__    							=				tok.batch_decode(__SCREAMING_SNAKE_CASE   ,					skip_special_tokens=__SCREAMING_SNAKE_CASE   ,					clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE     )[0]
        assert src_text == decoded

       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        assert self.tokenizer_ab.add_prefix_space
        assert self.tokenizer_ab([" Sam", "Sam"]     ).input_ids == [[5502, 2], [5502, 2]]

       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        assert self.rust_tokenizer_ab.add_prefix_space
        assert self.rust_tokenizer_ab([" Sam", "Sam"]     ).input_ids == [[5502, 2], [5502, 2]]








"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__					:     Tuple							=				logging.get_logger(__name__)

a__					:     str							=				{
    """facebook/regnet-y-040""": """https://huggingface.co/facebook/regnet-y-040/blob/main/config.json""",
}



class      lowercase_				(     __lowerCAmelCase							):
       snake_case__				:							Tuple											=     """regnet"""
       snake_case__				:							List[Any]											=     ["""x""", """y"""]

       def __init__(			self   ,					__SCREAMING_SNAKE_CASE=3   ,					__SCREAMING_SNAKE_CASE=32   ,					__SCREAMING_SNAKE_CASE=[128, 192, 512, 1088]   ,					__SCREAMING_SNAKE_CASE=[2, 6, 12, 2]   ,					__SCREAMING_SNAKE_CASE=64   ,					__SCREAMING_SNAKE_CASE="y"   ,					__SCREAMING_SNAKE_CASE="relu"   ,					**__SCREAMING_SNAKE_CASE   ,					):






        '''simple docstring'''

        super().__init__(**__SCREAMING_SNAKE_CASE     )
        if layer_type not in self.layer_types:
         raise ValueError(F"layer_type={layer_type} is not one of {','.join(self.layer_types     )}"     )
        snake_case__    							=				num_channels
        snake_case__    							=				embedding_size
        snake_case__    							=				hidden_sizes
        snake_case__    							=				depths
        snake_case__    							=				groups_width
        snake_case__    							=				layer_type
        snake_case__    							=				hidden_act
        # always downsample in the first stage
        snake_case__    							=				True

