
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import CLIPSegProcessor, ViTImageProcessor





@require_vision
class 			_lowerCAmelCase      (			unittest.TestCase ):




    def   __a		(      self  )       ->   str:
       lowerCAmelCase_      			=			tempfile.mkdtemp()

       # fmt: off
       lowerCAmelCase_      			=			["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "lo", "l</w>", "w</w>", "r</w>", "t</w>", "low</w>", "er</w>", "lowest</w>", "newer</w>", "wider", "<unk>", "<|startoftext|>", "<|endoftext|>"]
       # fmt: on
       lowerCAmelCase_      			=			dict(zip(_UpperCamelCase       ,       range(len(_UpperCamelCase  )  )  )  )
       lowerCAmelCase_      			=			["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
       lowerCAmelCase_      			=			{"unk_token": "<unk>"}

       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"       ,       encoding="utf-8"  ) as fp:
          fp.write(json.dumps(_UpperCamelCase  ) + "\n"  )
       with open(self.merges_file       ,       "w"       ,       encoding="utf-8"  ) as fp:
          fp.write("\n".join(_UpperCamelCase  )  )

       lowerCAmelCase_      			=			{
           "do_resize": True,
           "size": 20,
           "do_center_crop": True,
           "crop_size": 18,
           "do_normalize": True,
           "image_mean": [0.48145466, 0.4578275, 0.40821073],
           "image_std": [0.26862954, 0.26130258, 0.27577711],
       }
       lowerCAmelCase_      			=			os.path.join(self.tmpdirname       ,       _UpperCamelCase  )
       with open(self.image_processor_file       ,       "w"       ,       encoding="utf-8"  ) as fp:
          json.dump(_UpperCamelCase       ,       _UpperCamelCase  )




    def   __a		(      self       ,       **_UpperCamelCase  )       ->   int:
       return CLIPTokenizer.from_pretrained(self.tmpdirname       ,       **_UpperCamelCase  )




    def   __a		(      self       ,       **_UpperCamelCase  )       ->   int:
       return CLIPTokenizerFast.from_pretrained(self.tmpdirname       ,       **_UpperCamelCase  )




    def   __a		(      self       ,       **_UpperCamelCase  )       ->   int:
       return ViTImageProcessor.from_pretrained(self.tmpdirname       ,       **_UpperCamelCase  )




    def   __a		(      self  )       ->   int:
       shutil.rmtree(self.tmpdirname  )




    def   __a		(      self  )       ->   Optional[Any]:
       lowerCAmelCase_      			=			[np.random.randint(255       ,       size=(3, 30, 400)       ,       dtype=np.uinta  )]

       lowerCAmelCase_      			=			[Image.fromarray(np.moveaxis(_UpperCamelCase       ,       0       ,       -1  )  ) for x in image_inputs]

       return image_inputs




    def   __a		(      self  )       ->   str:
       lowerCAmelCase_      			=			self.get_tokenizer()
       lowerCAmelCase_      			=			self.get_rust_tokenizer()
       lowerCAmelCase_      			=			self.get_image_processor()

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )
       processor_slow.save_pretrained(self.tmpdirname  )
       lowerCAmelCase_      			=			CLIPSegProcessor.from_pretrained(self.tmpdirname       ,       use_fast=_UpperCamelCase  )

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )
       processor_fast.save_pretrained(self.tmpdirname  )
       lowerCAmelCase_      			=			CLIPSegProcessor.from_pretrained(self.tmpdirname  )

       self.assertEqual(processor_slow.tokenizer.get_vocab()       ,       tokenizer_slow.get_vocab()  )
       self.assertEqual(processor_fast.tokenizer.get_vocab()       ,       tokenizer_fast.get_vocab()  )
       self.assertEqual(tokenizer_slow.get_vocab()       ,       tokenizer_fast.get_vocab()  )
       self.assertIsInstance(processor_slow.tokenizer       ,       _UpperCamelCase  )
       self.assertIsInstance(processor_fast.tokenizer       ,       _UpperCamelCase  )

       self.assertEqual(processor_slow.image_processor.to_json_string()       ,       image_processor.to_json_string()  )
       self.assertEqual(processor_fast.image_processor.to_json_string()       ,       image_processor.to_json_string()  )
       self.assertIsInstance(processor_slow.image_processor       ,       _UpperCamelCase  )
       self.assertIsInstance(processor_fast.image_processor       ,       _UpperCamelCase  )




    def   __a		(      self  )       ->   List[Any]:
       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=self.get_tokenizer()       ,       image_processor=self.get_image_processor()  )
       processor.save_pretrained(self.tmpdirname  )

       lowerCAmelCase_      			=			self.get_tokenizer(bos_token="(BOS)"       ,       eos_token="(EOS)"  )
       lowerCAmelCase_      			=			self.get_image_processor(do_normalize=_UpperCamelCase       ,       padding_value=1.0  )

       lowerCAmelCase_      			=			CLIPSegProcessor.from_pretrained(
           self.tmpdirname       ,       bos_token="(BOS)"       ,       eos_token="(EOS)"       ,       do_normalize=_UpperCamelCase       ,       padding_value=1.0  )

       self.assertEqual(processor.tokenizer.get_vocab()       ,       tokenizer_add_kwargs.get_vocab()  )
       self.assertIsInstance(processor.tokenizer       ,       _UpperCamelCase  )

       self.assertEqual(processor.image_processor.to_json_string()       ,       image_processor_add_kwargs.to_json_string()  )
       self.assertIsInstance(processor.image_processor       ,       _UpperCamelCase  )




    def   __a		(      self  )       ->   Tuple:
       lowerCAmelCase_      			=			self.get_image_processor()
       lowerCAmelCase_      			=			self.get_tokenizer()

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )

       lowerCAmelCase_      			=			self.prepare_image_inputs()

       lowerCAmelCase_      			=			image_processor(_UpperCamelCase       ,       return_tensors="np"  )
       lowerCAmelCase_      			=			processor(images=_UpperCamelCase       ,       return_tensors="np"  )

       for key in input_feat_extract.keys():
          self.assertAlmostEqual(input_feat_extract[key].sum()       ,       input_processor[key].sum()       ,       delta=1e-2  )




    def   __a		(      self  )       ->   Any:
       lowerCAmelCase_      			=			self.get_image_processor()
       lowerCAmelCase_      			=			self.get_tokenizer()

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )

       lowerCAmelCase_      			=			"lower newer"

       lowerCAmelCase_      			=			processor(text=_UpperCamelCase  )

       lowerCAmelCase_      			=			tokenizer(_UpperCamelCase  )

       for key in encoded_tok.keys():
          self.assertListEqual(encoded_tok[key]       ,       encoded_processor[key]  )




    def   __a		(      self  )       ->   Union[str, Any]:
       lowerCAmelCase_      			=			self.get_image_processor()
       lowerCAmelCase_      			=			self.get_tokenizer()

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )

       lowerCAmelCase_      			=			"lower newer"
       lowerCAmelCase_      			=			self.prepare_image_inputs()

       lowerCAmelCase_      			=			processor(text=_UpperCamelCase       ,       images=_UpperCamelCase  )

       self.assertListEqual(list(inputs.keys()  )       ,       ["input_ids", "attention_mask", "pixel_values"]  )

       # test if it raises when no input is passed
       with pytest.raises(_UpperCamelCase  ):
          processor()




    def   __a		(      self  )       ->   str:
       lowerCAmelCase_      			=			self.get_image_processor()
       lowerCAmelCase_      			=			self.get_tokenizer()

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )

       lowerCAmelCase_      			=			self.prepare_image_inputs()
       lowerCAmelCase_      			=			self.prepare_image_inputs()

       lowerCAmelCase_      			=			processor(images=_UpperCamelCase       ,       visual_prompt=_UpperCamelCase  )

       self.assertListEqual(list(inputs.keys()  )       ,       ["pixel_values", "conditional_pixel_values"]  )

       # test if it raises when no input is passed
       with pytest.raises(_UpperCamelCase  ):
          processor()




    def   __a		(      self  )       ->   Union[str, Any]:
       lowerCAmelCase_      			=			self.get_image_processor()
       lowerCAmelCase_      			=			self.get_tokenizer()

       lowerCAmelCase_      			=			CLIPSegProcessor(tokenizer=_UpperCamelCase       ,       image_processor=_UpperCamelCase  )

       lowerCAmelCase_      			=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       lowerCAmelCase_      			=			processor.batch_decode(_UpperCamelCase  )
       lowerCAmelCase_      			=			tokenizer.batch_decode(_UpperCamelCase  )

       self.assertListEqual(_UpperCamelCase       ,       _UpperCamelCase  )





import itertools
import string
from collections.abc import Generator, Iterable






def      lowerCamelCase__       (       __lowerCAmelCase						:						Iterable[str]					,							__lowerCAmelCase						:						int       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			iter(__lowerCAmelCase       )
			while True:
						lowerCAmelCase_      			=			tuple(itertools.islice(__lowerCAmelCase					,							__lowerCAmelCase       )       )
						if not chunk:
									return
						yield chunk






def      lowerCamelCase__       (       __lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			"".join([c.upper() for c in dirty if c in string.ascii_letters]       )
			lowerCAmelCase_      			=			""

			if len(__lowerCAmelCase       ) < 2:
						return dirty

			for i in range(len(__lowerCAmelCase       ) - 1       ):
						clean += dirty[i]

						if dirty[i] == dirty[i + 1]:
									clean += "X"

			clean += dirty[-1]

			if len(__lowerCAmelCase       ) & 1:
						clean += "X"

			return clean






def      lowerCamelCase__       (       __lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			"ABCDEFGHIKLMNOPQRSTUVWXYZ"
			# we're using a list instead of a '2d' array because it makes the math
			# for setting up the table and doing the actual encoding/decoding simpler
			lowerCAmelCase_      			=			[]

			# copy key chars into the table if they are in `alphabet` ignoring duplicates
			for char in key.upper():
						if char not in table and char in alphabet:
									table.append(__lowerCAmelCase       )

    # fill the rest of the table in with the remaining alphabet chars
			for char in alphabet:
						if char not in table:
									table.append(__lowerCAmelCase       )

			return table






def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			generate_table(__lowerCAmelCase       )
			lowerCAmelCase_      			=			prepare_input(__lowerCAmelCase       )
			lowerCAmelCase_      			=			""

			# https://en.wikipedia.org/wiki/Playfair_cipher#Description
			for chara, chara in chunker(__lowerCAmelCase					,							2       ):
						lowerCAmelCase_			,						lowerCAmelCase_      			=			divmod(table.index(__lowerCAmelCase       )					,							5       )
						lowerCAmelCase_			,						lowerCAmelCase_      			=			divmod(table.index(__lowerCAmelCase       )					,							5       )

						if rowa == rowa:
									ciphertext += table[rowa * 5 + (cola + 1) % 5]
									ciphertext += table[rowa * 5 + (cola + 1) % 5]
						elif cola == cola:
									ciphertext += table[((rowa + 1) % 5) * 5 + cola]
									ciphertext += table[((rowa + 1) % 5) * 5 + cola]
						else:  # rectangle
									ciphertext += table[rowa * 5 + cola]
									ciphertext += table[rowa * 5 + cola]

			return ciphertext






def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			generate_table(__lowerCAmelCase       )
			lowerCAmelCase_      			=			""

			# https://en.wikipedia.org/wiki/Playfair_cipher#Description
			for chara, chara in chunker(__lowerCAmelCase					,							2       ):
						lowerCAmelCase_			,						lowerCAmelCase_      			=			divmod(table.index(__lowerCAmelCase       )					,							5       )
						lowerCAmelCase_			,						lowerCAmelCase_      			=			divmod(table.index(__lowerCAmelCase       )					,							5       )

						if rowa == rowa:
									plaintext += table[rowa * 5 + (cola - 1) % 5]
									plaintext += table[rowa * 5 + (cola - 1) % 5]
						elif cola == cola:
									plaintext += table[((rowa - 1) % 5) * 5 + cola]
									plaintext += table[((rowa - 1) % 5) * 5 + cola]
						else:  # rectangle
									plaintext += table[rowa * 5 + cola]
									plaintext += table[rowa * 5 + cola]

			return plaintext



