





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


_A					:				int				=			logging.get_logger(__name__)

_A					:				Tuple				=			{"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_A					:				Any				=			{
    """vocab_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"""
        ),
        """distilbert-base-german-cased""": """https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt""",
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """distilbert-base-uncased""": """https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json""",
        """distilbert-base-uncased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-cased""": """https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json""",
        """distilbert-base-cased-distilled-squad""": (
            """https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-german-cased""": (
            """https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"""
        ),
        """distilbert-base-multilingual-cased""": (
            """https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"""
        ),
    },
}

_A					:				Optional[int]				=			{
    """distilbert-base-uncased""": 5_12,
    """distilbert-base-uncased-distilled-squad""": 5_12,
    """distilbert-base-cased""": 5_12,
    """distilbert-base-cased-distilled-squad""": 5_12,
    """distilbert-base-german-cased""": 5_12,
    """distilbert-base-multilingual-cased""": 5_12,
}


_A					:				Optional[Any]				=			{
    """distilbert-base-uncased""": {"""do_lower_case""": True},
    """distilbert-base-uncased-distilled-squad""": {"""do_lower_case""": True},
    """distilbert-base-cased""": {"""do_lower_case""": False},
    """distilbert-base-cased-distilled-squad""": {"""do_lower_case""": False},
    """distilbert-base-german-cased""": {"""do_lower_case""": False},
    """distilbert-base-multilingual-cased""": {"""do_lower_case""": False},
}



class 					__snake_case	(  __SCREAMING_SNAKE_CASE    ):


    '''simple docstring'''







    lowerCamelCase__    :		Dict				=	VOCAB_FILES_NAMES
    lowerCamelCase__    :		Union[str, Any]				=	PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase__    :		Tuple				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase__    :		Optional[Any]				=	PRETRAINED_INIT_CONFIGURATION
    lowerCamelCase__    :		Dict				=	["""input_ids""", """attention_mask"""]
    lowerCamelCase__    :		str				=	DistilBertTokenizer



    def __init__(       self   ,				A_=None   ,				A_=None   ,				A_=True   ,				A_="[UNK]"   ,				A_="[SEP]"   ,				A_="[PAD]"   ,				A_="[CLS]"   ,				A_="[MASK]"   ,				A_=True   ,				A_=None   ,				**A_   ,				):





        '''simple docstring'''

        super().__init__(
            A_   ,				tokenizer_file=A_   ,				do_lower_case=A_   ,				unk_token=A_   ,				sep_token=A_   ,				pad_token=A_   ,				cls_token=A_   ,				mask_token=A_   ,				tokenize_chinese_chars=A_   ,				strip_accents=A_   ,				**A_   ,				)

        SCREAMING_SNAKE_CASE__											=			json.loads(self.backend_tokenizer.normalizer.__getstate__()     )
        if (
            normalizer_state.get('''lowercase'''   ,				A_     ) != do_lower_case
            or normalizer_state.get('''strip_accents'''   ,				A_     ) != strip_accents
            or normalizer_state.get('''handle_chinese_chars'''   ,				A_     ) != tokenize_chinese_chars
        ):
            SCREAMING_SNAKE_CASE__											=			getattr(A_   ,				normalizer_state.pop('''type'''     )     )
            SCREAMING_SNAKE_CASE__											=			do_lower_case
            SCREAMING_SNAKE_CASE__											=			strip_accents
            SCREAMING_SNAKE_CASE__											=			tokenize_chinese_chars
            SCREAMING_SNAKE_CASE__											=			normalizer_class(**A_     )

        SCREAMING_SNAKE_CASE__											=			do_lower_case



    def  lowercase_					(       self   ,				A_   ,				A_=None     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			[self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
            output += token_ids_a + [self.sep_token_id]

        return output



    def  lowercase_					(       self   ,				A_   ,				A_ = None     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			[self.sep_token_id]
        SCREAMING_SNAKE_CASE__											=			[self.cls_token_id]
        if token_ids_a is None:
            return len(cls + token_ids_a + sep     ) * [0]
        return len(cls + token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1]




    def  lowercase_					(       self   ,				A_   ,				A_ = None     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			self._tokenizer.model.save(A_   ,				name=A_     )
        return tuple(A_     )







import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin



@skip_mps
class 					__snake_case	(  __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     unittest.TestCase    ):


    '''simple docstring'''







    lowerCamelCase__    :		Any				=	IFInpaintingPipeline
    lowerCamelCase__    :		str				=	TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
    lowerCamelCase__    :		Optional[Any]				=	TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
    lowerCamelCase__    :		Tuple				=	PipelineTesterMixin.required_optional_params - {"""latents"""}



    def  lowercase_					(       self     ):





        '''simple docstring'''

        return self._get_dummy_components()



    def  lowercase_					(       self   ,				A_   ,				A_=0     ):





        '''simple docstring'''

        if str(A_     ).startswith('''mps'''     ):
            SCREAMING_SNAKE_CASE__											=			torch.manual_seed(A_     )
        else:
            SCREAMING_SNAKE_CASE__											=			torch.Generator(device=A_     ).manual_seed(A_     )

        SCREAMING_SNAKE_CASE__											=			floats_tensor((1, 3, 32, 32)   ,				rng=random.Random(A_     )     ).to(A_     )
        SCREAMING_SNAKE_CASE__											=			floats_tensor((1, 3, 32, 32)   ,				rng=random.Random(A_     )     ).to(A_     )

        SCREAMING_SNAKE_CASE__											=			{
            '''prompt''': '''A painting of a squirrel eating a burger''',
            '''image''': image,
            '''mask_image''': mask_image,
            '''generator''': generator,
            '''num_inference_steps''': 2,
            '''output_type''': '''numpy''',
        }

        return inputs



    @unittest.skipIf(
        torch_device != '''cuda''' or not is_xformers_available()   ,				reason='''XFormers attention is only available with CUDA and `xformers` installed'''   ,				)
    def  lowercase_					(       self     ):





        '''simple docstring'''

        self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3     )



    def  lowercase_					(       self     ):





        '''simple docstring'''

        self._test_save_load_optional_components()



    @unittest.skipIf(torch_device != '''cuda'''   ,				reason='''float16 requires CUDA'''     )
    def  lowercase_					(       self     ):





        '''simple docstring'''

        super().test_save_load_floataa(expected_max_diff=1E-1     )



    def  lowercase_					(       self     ):





        '''simple docstring'''

        self._test_attention_slicing_forward_pass(expected_max_diff=1E-2     )



    def  lowercase_					(       self     ):





        '''simple docstring'''

        self._test_save_load_local()




    def  lowercase_					(       self     ):





        '''simple docstring'''

        self._test_inference_batch_single_identical(
            expected_max_diff=1E-2   ,				)
