

'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


a   :			List[Any]         = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

a   :			List[str]         = {
    "vocab_file": {
        "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt",
    },
    "tokenizer_file": {
        "unc-nlp/lxmert-base-uncased": (
            "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json"
        ),
    },
}

a   :			List[Any]         = {
    "unc-nlp/lxmert-base-uncased": 5_12,
}

a   :			Tuple         = {
    "unc-nlp/lxmert-base-uncased": {"do_lower_case": True},
}







class   UpperCamelCase__    (   _UpperCamelCase   ):


		"""simple docstring"""

		SCREAMING_SNAKE_CASE__  :	Optional[Any]   =							VOCAB_FILES_NAMES
		SCREAMING_SNAKE_CASE__  :	Union[str, Any]   =							PRETRAINED_VOCAB_FILES_MAP
		SCREAMING_SNAKE_CASE__  :	List[Any]   =							PRETRAINED_INIT_CONFIGURATION
		SCREAMING_SNAKE_CASE__  :	Any   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		SCREAMING_SNAKE_CASE__  :	Any   =							LxmertTokenizer







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


							'''simple docstring'''

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

							UpperCAmelCase		:							Optional[Any]   					=   json.loads(self.backend_tokenizer.normalizer.__getstate__()			)
							if (
							    normalizer_state.get("lowercase"    ,			_UpperCAmelCase			) != do_lower_case
							    or normalizer_state.get("strip_accents"    ,			_UpperCAmelCase			) != strip_accents
							    or normalizer_state.get("handle_chinese_chars"    ,			_UpperCAmelCase			) != tokenize_chinese_chars
							):
												UpperCAmelCase		:							Optional[Any]   					=   getattr(_UpperCAmelCase    ,			normalizer_state.pop("type"			)			)
												UpperCAmelCase		:							Tuple   					=   do_lower_case
												UpperCAmelCase		:							Union[str, Any]   					=   strip_accents
												UpperCAmelCase		:							Union[str, Any]   					=   tokenize_chinese_chars
												UpperCAmelCase		:							Dict   					=   normalizer_class(**_UpperCAmelCase			)

							UpperCAmelCase		:							Tuple   					=   do_lower_case







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


							'''simple docstring'''

							UpperCAmelCase		:							List[Any]   					=   [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       A_       ( self    ,			snake_case    ,			snake_case = None			):


							'''simple docstring'''

							UpperCAmelCase		:							List[str]   					=   [self.sep_token_id]
							UpperCAmelCase		:							List[Any]   					=   [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       A_       ( self    ,			snake_case    ,			snake_case = None			):


							'''simple docstring'''

							UpperCAmelCase		:							List[Any]   					=   self._tokenizer.model.save(_UpperCAmelCase    ,			name=_UpperCAmelCase			)
							return tuple(_UpperCAmelCase			)





'''simple docstring'''

from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_  )			->      np.ndarray:
		_a     :      Union[str, Any]        =							cva.getAffineTransform(lowerCAmelCase_						,			lowerCAmelCase_  )
		return cva.warpAffine(lowerCAmelCase_						,			lowerCAmelCase_						,			(rows, cols)  )


if __name__ == "__main__":
							# read original image
							__lowerCAmelCase									=   cva.imread(
							    str(Path(__file__).resolve().parent.parent / '''image_data''' / '''lena.jpg''')
							)
							# turn image in gray scale value
							__lowerCAmelCase									=   cva.cvtColor(image, cva.COLOR_BGR2GRAY)
							# get image shape
							__lowerCAmelCase			,					__lowerCAmelCase									=   gray_img.shape

							# set different points to rotate image
							__lowerCAmelCase									=   np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
							__lowerCAmelCase									=   np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
							__lowerCAmelCase									=   np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
							__lowerCAmelCase									=   np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

							# add all rotated images in a list
							__lowerCAmelCase									=   [
							    gray_img,
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							]

							# plot different image rotations
							__lowerCAmelCase									=   plt.figure(1)
							__lowerCAmelCase									=   ['''Original''', '''Rotation 1''', '''Rotation 2''', '''Rotation 3''']
							for i, image in enumerate(images):
														plt.subplot(2, 2, i + 1), plt.imshow(image, '''gray''')
														plt.title(titles[i])
														plt.axis('''off''')
														plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
							plt.show()




