from dataclasses import dataclass
from enum import Enum
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
class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						List[str]					     =			{
     'sld_warmup_steps': 15,
     'sld_guidance_scale': 20,
     'sld_threshold': 0.0,
     'sld_momentum_scale': 0.0,
     'sld_mom_beta': 0.0,
 }
 _lowerCamelCase    :						List[Any]					     =			{
     'sld_warmup_steps': 10,
     'sld_guidance_scale': 1_000,
     'sld_threshold': 0.01,
     'sld_momentum_scale': 0.3,
     'sld_mom_beta': 0.4,
 }
 _lowerCamelCase    :						Tuple					     =			{
     'sld_warmup_steps': 7,
     'sld_guidance_scale': 2_000,
     'sld_threshold': 0.025,
     'sld_momentum_scale': 0.5,
     'sld_mom_beta': 0.7,
 }
 _lowerCamelCase    :						List[str]					     =			{
     'sld_warmup_steps': 0,
     'sld_guidance_scale': 5_000,
     'sld_threshold': 1.0,
     'sld_momentum_scale': 0.5,
     'sld_mom_beta': 0.7,
 }







@dataclass
class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						Union[List[PIL.Image.Image], np.ndarray]
 _lowerCamelCase    :						Optional[List[bool]]
 _lowerCamelCase    :						Optional[Union[List[PIL.Image.Image], np.ndarray]]
 _lowerCamelCase    :						Optional[str]


if is_transformers_available() and is_torch_available():
 from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
 from .safety_checker import SafeStableDiffusionSafetyChecker











import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 		lowerCAmelCase_				(  UpperCamelCase				,     unittest.TestCase ):
     __lowerCamelCase       :    List[str] 	=     HerbertTokenizer
     __lowerCamelCase       :    Union[str, Any] 	=     HerbertTokenizerFast
     __lowerCamelCase       :    Union[str, Any] 	=     True





     def 						lowerCamelCase							(	self  )		->				int:
        super().setUp()

        # Use a simpler test file without japanese/chinese characters
        with open(F'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''							, encoding="""utf-8"""  ) as f_data:
           lowerCamelCase									=f_data.read().replace("""\n\n"""							, """\n"""  ).strip()

        lowerCamelCase									=[
            """<s>""",
            """</s>""",
            """l""",
            """o""",
            """w""",
            """e""",
            """r""",
            """s""",
            """t""",
            """i""",
            """d""",
            """n""",
            """w</w>""",
            """r</w>""",
            """t</w>""",
            """lo""",
            """low""",
            """er</w>""",
            """low</w>""",
            """lowest</w>""",
            """newer</w>""",
            """wider</w>""",
            """,</w>""",
            """<unk>""",
        ]
        lowerCamelCase									=dict(zip(_UpperCAmelCase							, range(len(_UpperCAmelCase  )  )  )  )
        lowerCamelCase									=["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

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





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				Optional[Any]:
        lowerCamelCase									="""lower newer"""
        lowerCamelCase									="""lower newer"""
        return input_text, output_text





     def 						lowerCamelCase							(	self  )		->				Any:
        lowerCamelCase									=self.tokenizer_class(vocab_file=self.vocab_file							, merges_file=self.merges_file  )

        lowerCamelCase									="""lower"""
        lowerCamelCase									=["""low""", """er</w>"""]
        lowerCamelCase									=tokenizer.tokenize(_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase							, _UpperCAmelCase  )

        lowerCamelCase									=tokens + ["""<unk>"""]
        lowerCamelCase									=[16, 17, 23]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase  )							, _UpperCAmelCase  )





     def 						lowerCamelCase							(	self  )		->				Union[str, Any]:
        if not self.test_rust_tokenizer:
           return

        lowerCamelCase									=self.get_tokenizer()
        lowerCamelCase									=self.get_rust_tokenizer()

        lowerCamelCase									="""lower,newer"""

        lowerCamelCase									=tokenizer.tokenize(_UpperCAmelCase  )
        lowerCamelCase									=rust_tokenizer.tokenize(_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase							, _UpperCAmelCase  )

        lowerCamelCase									=tokenizer.encode(_UpperCAmelCase							, add_special_tokens=_UpperCAmelCase  )
        lowerCamelCase									=rust_tokenizer.encode(_UpperCAmelCase							, add_special_tokens=_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase							, _UpperCAmelCase  )

        lowerCamelCase									=self.get_rust_tokenizer()
        lowerCamelCase									=tokenizer.encode(_UpperCAmelCase  )
        lowerCamelCase									=rust_tokenizer.encode(_UpperCAmelCase  )
        self.assertListEqual(_UpperCAmelCase							, _UpperCAmelCase  )





     @slow
     def 						lowerCamelCase							(	self  )		->				Any:
        lowerCamelCase									=self.tokenizer_class.from_pretrained("""allegro/herbert-base-cased"""  )

        lowerCamelCase									=tokenizer.encode("""konstruowanie sekwencji"""							, add_special_tokens=_UpperCAmelCase  )
        lowerCamelCase									=tokenizer.encode("""konstruowanie wielu sekwencji"""							, add_special_tokens=_UpperCAmelCase  )

        lowerCamelCase									=tokenizer.build_inputs_with_special_tokens(_UpperCAmelCase  )
        lowerCamelCase									=tokenizer.build_inputs_with_special_tokens(_UpperCAmelCase							, _UpperCAmelCase  )

        assert encoded_sentence == [0] + text + [2]
        assert encoded_pair == [0] + text + [2] + text_a + [2]