





'''simple docstring'''


import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin
class 				a_       (    __UpperCamelCase     ,						unittest.TestCase							):
     __A								=      ProphetNetTokenizer
     __A								=      False





     def 							lowercase__				(			self		: Union[str, Any]						):





        """simple docstring"""




        super().setUp()

        lowercase_      :Any         =			[
            """[UNK]""",
            """[CLS]""",
            """[SEP]""",
            """[PAD]""",
            """[MASK]""",
            """want""",
            """##want""",
            """##ed""",
            """wa""",
            """un""",
            """runn""",
            """##ing""",
            """,""",
            """low""",
            """lowest""",
        ]
        lowercase_      :int         =			os.path.join(self.tmpdirname     ,				VOCAB_FILES_NAMES["vocab_file"]						)
        with open(self.vocab_file     ,				"w"     ,				encoding="utf-8"						) as vocab_writer:
           vocab_writer.write("".join([x + "\n" for x in vocab_tokens]						)						)





     def 							lowercase__				(			self		: Optional[int]     ,				lowercase		: Optional[int]						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			"""UNwant\u00E9d,running"""
        lowercase_      :Optional[int]         =			"""unwanted, running"""
        return input_text, output_text





     def 							lowercase__				(			self		: List[Any]						):





        """simple docstring"""




        lowercase_      :Optional[Any]         =			self.tokenizer_class(self.vocab_file						)

        lowercase_      :int         =			tokenizer.tokenize("UNwant\u00E9d,running"						)
        self.assertListEqual(_lowerCAmelCase     ,				["un", "##want", "##ed", ",", "runn", "##ing"]						)
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase						)     ,				[9, 6, 7, 12, 10, 11]						)





     def 							lowercase__				(			self		: Tuple						):





        """simple docstring"""




        lowercase_      :str         =			BasicTokenizer()

        self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz"						)     ,				["ah", "\u535A", "\u63A8", "zz"]						)





     def 							lowercase__				(			self		: Optional[Any]						):





        """simple docstring"""




        lowercase_      :Optional[int]         =			BasicTokenizer(do_lower_case=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "						)     ,				["hello", "!", "how", "are", "you", "?"]						)
        self.assertListEqual(tokenizer.tokenize("H\u00E9llo"						)     ,				["hello"]						)





     def 							lowercase__				(			self		: Optional[int]						):





        """simple docstring"""




        lowercase_      :Optional[Any]         =			BasicTokenizer(do_lower_case=_lowerCAmelCase     ,				strip_accents=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "						)     ,				["hällo", "!", "how", "are", "you", "?"]						)
        self.assertListEqual(tokenizer.tokenize("H\u00E9llo"						)     ,				["h\u00E9llo"]						)





     def 							lowercase__				(			self		: Union[str, Any]						):





        """simple docstring"""




        lowercase_      :List[str]         =			BasicTokenizer(do_lower_case=_lowerCAmelCase     ,				strip_accents=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "						)     ,				["hallo", "!", "how", "are", "you", "?"]						)
        self.assertListEqual(tokenizer.tokenize("H\u00E9llo"						)     ,				["hello"]						)





     def 							lowercase__				(			self		: Optional[int]						):





        """simple docstring"""




        lowercase_      :Any         =			BasicTokenizer(do_lower_case=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "						)     ,				["hallo", "!", "how", "are", "you", "?"]						)
        self.assertListEqual(tokenizer.tokenize("H\u00E9llo"						)     ,				["hello"]						)





     def 							lowercase__				(			self		: Union[str, Any]						):





        """simple docstring"""




        lowercase_      :Any         =			BasicTokenizer(do_lower_case=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "						)     ,				["HeLLo", "!", "how", "Are", "yoU", "?"]						)





     def 							lowercase__				(			self		: int						):





        """simple docstring"""




        lowercase_      :Optional[Any]         =			BasicTokenizer(do_lower_case=_lowerCAmelCase     ,				strip_accents=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "						)     ,				["HäLLo", "!", "how", "Are", "yoU", "?"]						)





     def 							lowercase__				(			self		: int						):





        """simple docstring"""




        lowercase_      :Optional[Any]         =			BasicTokenizer(do_lower_case=_lowerCAmelCase     ,				strip_accents=_lowerCAmelCase						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "						)     ,				["HaLLo", "!", "how", "Are", "yoU", "?"]						)





     def 							lowercase__				(			self		: Any						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			BasicTokenizer(do_lower_case=_lowerCAmelCase     ,				never_split=["[UNK]"]						)

        self.assertListEqual(
            tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]"						)     ,				["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"]						)





     def 							lowercase__				(			self		: str						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

        lowercase_      :List[str]         =			{}
        for i, token in enumerate(_lowerCAmelCase						):
           lowercase_      :int         =			i
        lowercase_      :Any         =			WordpieceTokenizer(vocab=_lowerCAmelCase     ,				unk_token="[UNK]"						)

        self.assertListEqual(tokenizer.tokenize(""						)     ,				[]						)

        self.assertListEqual(tokenizer.tokenize("unwanted running"						)     ,				["un", "##want", "##ed", "runn", "##ing"]						)

        self.assertListEqual(tokenizer.tokenize("unwantedX running"						)     ,				["[UNK]", "runn", "##ing"]						)





     @require_torch
     def 							lowercase__				(			self		: List[str]						):





        """simple docstring"""




        lowercase_      :int         =			self.tokenizer_class.from_pretrained("microsoft/prophetnet-large-uncased"						)

        lowercase_      :Dict         =			["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
        lowercase_      :Optional[Any]         =			[1_037, 2_146, 20_423, 2_005, 7_680, 7_849, 3_989, 1_012, 102]
        lowercase_      :str         =			tokenizer(_lowerCAmelCase     ,				padding=_lowerCAmelCase     ,				return_tensors="pt"						)
        self.assertIsInstance(_lowerCAmelCase     ,				_lowerCAmelCase						)
        lowercase_      :int         =			list(batch.input_ids.numpy()[0]						)
        self.assertListEqual(_lowerCAmelCase     ,				_lowerCAmelCase						)

        self.assertEqual((2, 9)     ,				batch.input_ids.shape						)
        self.assertEqual((2, 9)     ,				batch.attention_mask.shape						)





     def 							lowercase__				(			self		: int						):





        """simple docstring"""




        self.assertTrue(_is_whitespace(" "						)						)
        self.assertTrue(_is_whitespace("\t"						)						)
        self.assertTrue(_is_whitespace("\r"						)						)
        self.assertTrue(_is_whitespace("\n"						)						)
        self.assertTrue(_is_whitespace("\u00A0"						)						)

        self.assertFalse(_is_whitespace("A"						)						)
        self.assertFalse(_is_whitespace("-"						)						)





     def 							lowercase__				(			self		: Any						):





        """simple docstring"""




        self.assertTrue(_is_control("\u0005"						)						)

        self.assertFalse(_is_control("A"						)						)
        self.assertFalse(_is_control(" "						)						)
        self.assertFalse(_is_control("\t"						)						)
        self.assertFalse(_is_control("\r"						)						)





     def 							lowercase__				(			self		: int						):





        """simple docstring"""




        self.assertTrue(_is_punctuation("-"						)						)
        self.assertTrue(_is_punctuation("$"						)						)
        self.assertTrue(_is_punctuation("`"						)						)
        self.assertTrue(_is_punctuation("."						)						)

        self.assertFalse(_is_punctuation("A"						)						)
        self.assertFalse(_is_punctuation(" "						)						)







     @slow
     def 							lowercase__				(			self		: Dict						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			self.tokenizer_class.from_pretrained("microsoft/prophetnet-large-uncased"						)

        lowercase_      :Union[str, Any]         =			tokenizer.encode("sequence builders"     ,				add_special_tokens=_lowerCAmelCase						)
        lowercase_      :Union[str, Any]         =			tokenizer.encode("multi-sequence build"     ,				add_special_tokens=_lowerCAmelCase						)

        lowercase_      :str         =			tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase						)
        lowercase_      :List[str]         =			tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase     ,				_lowerCAmelCase						)

        assert encoded_sentence == text + [102]
        assert encoded_pair == text + [102] + text_a + [102]







'''simple docstring'''


import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class 				a_       (    _lowerCAmelCase							):
     __A								=      ["image_processor", "tokenizer"]
     __A								=      "LayoutLMv3ImageProcessor"
     __A								=      ("LayoutLMv3Tokenizer", "LayoutLMv3TokenizerFast")





     def __init__(			self		: int     ,				lowercase		: Optional[Any]=None     ,				lowercase		: List[str]=None     ,				**lowercase		: Optional[int]						):





        """simple docstring"""




        lowercase_      :int         =			None
        if "feature_extractor" in kwargs:
           warnings.warn(
               "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
               " instead."     ,				lowercase     ,				)
           lowercase_      :Optional[int]         =			kwargs.pop("feature_extractor"						)

        lowercase_      :Union[str, Any]         =			image_processor if image_processor is not None else feature_extractor
        if image_processor is None:
           raise ValueError("You need to specify an `image_processor`."						)
        if tokenizer is None:
           raise ValueError("You need to specify a `tokenizer`."						)

        super().__init__(lowercase     ,				lowercase						)





     def __call__(			self		: Optional[Any]     ,				lowercase		: List[str]     ,				lowercase		: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None     ,				lowercase		: Optional[Union[PreTokenizedInput, List[PreTokenizedInput]]] = None     ,				lowercase		: Union[List[List[int]], List[List[List[int]]]] = None     ,				lowercase		: Optional[Union[List[int], List[List[int]]]] = None     ,				lowercase		: bool = True     ,				lowercase		: Union[bool, str, PaddingStrategy] = False     ,				lowercase		: Union[bool, str, TruncationStrategy] = None     ,				lowercase		: Optional[int] = None     ,				lowercase		: int = 0     ,				lowercase		: Optional[int] = None     ,				lowercase		: Optional[bool] = None     ,				lowercase		: Optional[bool] = None     ,				lowercase		: bool = False     ,				lowercase		: bool = False     ,				lowercase		: bool = False     ,				lowercase		: bool = False     ,				lowercase		: bool = True     ,				lowercase		: Optional[Union[str, TensorType]] = None     ,				**lowercase		: List[Any]     ,				):





        """simple docstring"""




        if self.image_processor.apply_ocr and (boxes is not None):
           raise ValueError(
               "You cannot provide bounding boxes if you initialized the image processor with apply_ocr set to True."						)

        if self.image_processor.apply_ocr and (word_labels is not None):
           raise ValueError(
               "You cannot provide word labels if you initialized the image processor with apply_ocr set to True."						)

        # first, apply the image processor
        lowercase_      :Dict         =			self.image_processor(images=lowercase     ,				return_tensors=lowercase						)

        # second, apply the tokenizer
        if text is not None and self.image_processor.apply_ocr and text_pair is None:
           if isinstance(lowercase     ,				lowercase						):
              lowercase_      :str         =			[text]  # add batch dimension (as the image processor always adds a batch dimension)
           lowercase_      :Union[str, Any]         =			features["words"]

        lowercase_      :Optional[Any]         =			self.tokenizer(
            text=text if text is not None else features["words"]     ,				text_pair=text_pair if text_pair is not None else None     ,				boxes=boxes if boxes is not None else features["boxes"]     ,				word_labels=lowercase     ,				add_special_tokens=lowercase     ,				padding=lowercase     ,				truncation=lowercase     ,				max_length=lowercase     ,				stride=lowercase     ,				pad_to_multiple_of=lowercase     ,				return_token_type_ids=lowercase     ,				return_attention_mask=lowercase     ,				return_overflowing_tokens=lowercase     ,				return_special_tokens_mask=lowercase     ,				return_offsets_mapping=lowercase     ,				return_length=lowercase     ,				verbose=lowercase     ,				return_tensors=lowercase     ,				**lowercase     ,				)

        # add pixel values
        lowercase_      :Any         =			features.pop("pixel_values"						)
        if return_overflowing_tokens is True:
           lowercase_      :Any         =			self.get_overflowing_images(lowercase     ,				encoded_inputs["overflow_to_sample_mapping"]						)
        lowercase_      :Any         =			images

        return encoded_inputs





     def 							lowercase__				(			self		: List[Any]     ,				lowercase		: Any     ,				lowercase		: Optional[Any]						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			[]
        for sample_idx in overflow_to_sample_mapping:
           images_with_overflow.append(images[sample_idx]						)

        if len(lowercase						) != len(lowercase						):
           raise ValueError(
               "Expected length of images to be the same as the length of `overflow_to_sample_mapping`, but got"
               F' {len(lowercase						)} and {len(lowercase						)}'						)

        return images_with_overflow





     def 							lowercase__				(			self		: Union[str, Any]     ,				*lowercase		: List[Any]     ,				**lowercase		: Optional[Any]						):





        """simple docstring"""




        return self.tokenizer.batch_decode(*lowercase     ,				**lowercase						)





     def 							lowercase__				(			self		: List[Any]     ,				*lowercase		: Any     ,				**lowercase		: str						):





        """simple docstring"""




        return self.tokenizer.decode(*lowercase     ,				**lowercase						)





     @property
     def 							lowercase__				(			self		: Optional[Any]						):





        """simple docstring"""




        return ["input_ids", "bbox", "attention_mask", "pixel_values"]





     @property
     def 							lowercase__				(			self		: str						):





        """simple docstring"""




        warnings.warn(
            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."     ,				lowercase     ,				)
        return self.image_processor_class







     @property
     def 							lowercase__				(			self		: Tuple						):





        """simple docstring"""




        warnings.warn(
            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."     ,				lowercase     ,				)
        return self.image_processor


