





from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available

@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class 		__a							(	_SCREAMING_SNAKE_CASE      ):
       __snake_case						:   Union[List[PIL.Image.Image], np.ndarray]
       __snake_case						:   Optional[List[bool]]


if is_transformers_available() and is_torch_available():
  from .modeling_roberta_series import RobertaSeriesModelWithTransformation
  from .pipeline_alt_diffusion import AltDiffusionPipeline
  from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline









import unittest

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

class 		__a							(	unittest.TestCase      ):



       @cached_property
       def  A							(     self	:   Optional[int]			):
           return BlenderbotTokenizer.from_pretrained("""facebook/blenderbot-3B"""			)



       @cached_property
       def  A							(     self	:   Optional[int]			):
           return BlenderbotTokenizerFast.from_pretrained("""facebook/blenderbot-3B"""			)



       def  A							(     self	:   Optional[Any]			):
           lowerCAmelCase_					:	List[str]						=   self.tokenizer_ab
           lowerCAmelCase_					:	Any						=   """ I am a small frog."""
           lowerCAmelCase_					:	Union[str, Any]						=   tok([src_text]					,			padding=UpperCAmelCase					,			truncation=UpperCAmelCase			)["""input_ids"""]
           lowerCAmelCase_					:	int						=   tok.batch_decode(UpperCAmelCase					,			skip_special_tokens=UpperCAmelCase					,			clean_up_tokenization_spaces=UpperCAmelCase			)[0]
           assert src_text == decoded



       def  A							(     self	:   List[Any]			):
           lowerCAmelCase_					:	Dict						=   self.rust_tokenizer_ab
           lowerCAmelCase_					:	str						=   """ I am a small frog."""
           lowerCAmelCase_					:	Tuple						=   tok([src_text]					,			padding=UpperCAmelCase					,			truncation=UpperCAmelCase			)["""input_ids"""]
           lowerCAmelCase_					:	int						=   tok.batch_decode(UpperCAmelCase					,			skip_special_tokens=UpperCAmelCase					,			clean_up_tokenization_spaces=UpperCAmelCase			)[0]
           assert src_text == decoded



       def  A							(     self	:   str			):
           assert self.tokenizer_ab.add_prefix_space
           assert self.tokenizer_ab([""" Sam""", """Sam"""]			).input_ids == [[55_02, 2], [55_02, 2]]



       def  A							(     self	:   List[str]			):
           assert self.rust_tokenizer_ab.add_prefix_space
           assert self.rust_tokenizer_ab([""" Sam""", """Sam"""]			).input_ids == [[55_02, 2], [55_02, 2]]


