




'''simple docstring'''





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 CLIPImageProcessor, CLIPProcessor




@require_vision
class  _snake_case		(	unittest.TestCase							):




			def    lowerCAmelCase__				(					self							)				->				List[Any]:

										'''simple docstring'''




										snake_case_						=      tempfile.mkdtemp()

										# fmt: off
										snake_case_						=      ["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
										snake_case_						=      dict(zip(a__				,							range(len(a__							)							)							)							)
										snake_case_						=      ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
										snake_case_						=      {"unk_token": "<unk>"}

										snake_case_						=      os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES["vocab_file"]							)
										snake_case_						=      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(a__							) + "\n"							)
										with open(self.merges_file				,							"w"				,							encoding="utf-8"							) as fp:
																	fp.write("\n".join(a__							)							)

										snake_case_						=      {
										    "do_resize": True,
										    "size": 20,
										    "do_center_crop": True,
										    "crop_size": 18,
										    "do_normalize": True,
										    "image_mean": [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
										    "image_std": [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
										}
										snake_case_						=      os.path.join(self.tmpdirname				,							a__							)
										with open(self.image_processor_file				,							"w"				,							encoding="utf-8"							) as fp:
																	json.dump(a__				,							a__							)




			def    lowerCAmelCase__				(					self				,							**a__							)				->				Dict:

										'''simple docstring'''




										return CLIPTokenizer.from_pretrained(self.tmpdirname				,							**a__							)




			def    lowerCAmelCase__				(					self				,							**a__							)				->				List[str]:

										'''simple docstring'''




										return CLIPTokenizerFast.from_pretrained(self.tmpdirname				,							**a__							)




			def    lowerCAmelCase__				(					self				,							**a__							)				->				Tuple:

										'''simple docstring'''




										return CLIPImageProcessor.from_pretrained(self.tmpdirname				,							**a__							)




			def    lowerCAmelCase__				(					self							)				->				List[str]:

										'''simple docstring'''




										shutil.rmtree(self.tmpdirname							)




			def    lowerCAmelCase__				(					self							)				->				Dict:

										'''simple docstring'''




										snake_case_						=      [np.random.randint(255				,							size=(3, 30, 400)				,							dtype=np.uinta							)]

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

										return image_inputs




			def    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										snake_case_						=      self.get_tokenizer()
										snake_case_						=      self.get_rust_tokenizer()
										snake_case_						=      self.get_image_processor()

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)
										processor_slow.save_pretrained(self.tmpdirname							)
										snake_case_						=      CLIPProcessor.from_pretrained(self.tmpdirname				,							use_fast=a__							)

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)
										processor_fast.save_pretrained(self.tmpdirname							)
										snake_case_						=      CLIPProcessor.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				,							a__							)
										self.assertIsInstance(processor_fast.tokenizer				,							a__							)

										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				,							a__							)
										self.assertIsInstance(processor_fast.image_processor				,							a__							)




			def    lowerCAmelCase__				(					self							)				->				Tuple:

										'''simple docstring'''




										snake_case_						=      CLIPProcessor(tokenizer=self.get_tokenizer()				,							image_processor=self.get_image_processor()							)
										processor.save_pretrained(self.tmpdirname							)

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

										snake_case_						=      CLIPProcessor.from_pretrained(
										    self.tmpdirname				,							bos_token="(BOS)"				,							eos_token="(EOS)"				,							do_normalize=a__				,							padding_value=1.0							)

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

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




			def    lowerCAmelCase__				(					self							)				->				Dict:

										'''simple docstring'''




										snake_case_						=      self.get_image_processor()
										snake_case_						=      self.get_tokenizer()

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)

										snake_case_						=      self.prepare_image_inputs()

										snake_case_						=      image_processor(a__				,							return_tensors="np"							)
										snake_case_						=      processor(images=a__				,							return_tensors="np"							)

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




			def    lowerCAmelCase__				(					self							)				->				Dict:

										'''simple docstring'''




										snake_case_						=      self.get_image_processor()
										snake_case_						=      self.get_tokenizer()

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)

										snake_case_						=      "lower newer"

										snake_case_						=      processor(text=a__							)

										snake_case_						=      tokenizer(a__							)

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




			def    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										snake_case_						=      self.get_image_processor()
										snake_case_						=      self.get_tokenizer()

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)

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

										snake_case_						=      processor(text=a__				,							images=a__							)

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

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




			def    lowerCAmelCase__				(					self							)				->				Any:

										'''simple docstring'''




										snake_case_						=      self.get_image_processor()
										snake_case_						=      self.get_tokenizer()

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)

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

										snake_case_						=      processor.batch_decode(a__							)
										snake_case_						=      tokenizer.batch_decode(a__							)

										self.assertListEqual(a__				,							a__							)




			def    lowerCAmelCase__				(					self							)				->				str:

										'''simple docstring'''




										snake_case_						=      self.get_image_processor()
										snake_case_						=      self.get_tokenizer()

										snake_case_						=      CLIPProcessor(tokenizer=a__				,							image_processor=a__							)

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

										snake_case_						=      processor(text=a__				,							images=a__							)

										self.assertListEqual(list(inputs.keys()							)				,							processor.model_input_names							)










import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
__A        =    {
    "E": 1_2.7_0,
    "T": 9.0_6,
    "A": 8.1_7,
    "O": 7.5_1,
    "I": 6.9_7,
    "N": 6.7_5,
    "S": 6.3_3,
    "H": 6.0_9,
    "R": 5.9_9,
    "D": 4.2_5,
    "L": 4.0_3,
    "C": 2.7_8,
    "U": 2.7_6,
    "M": 2.4_1,
    "W": 2.3_6,
    "F": 2.2_3,
    "G": 2.0_2,
    "Y": 1.9_7,
    "P": 1.9_3,
    "B": 1.2_9,
    "V": 0.9_8,
    "K": 0.7_7,
    "J": 0.1_5,
    "X": 0.1_5,
    "Q": 0.1_0,
    "Z": 0.0_7,
}
__A        =    "ETAOINSHRDLCUMWFGYPBVKJXQZ"
__A        =    "ABCDEFGHIJKLMNOPQRSTUVWXYZ"







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       dict[str, int]:





				"""simple docstring"""


				__lowerCamelCase		       =    {letter: 0 for letter in string.ascii_uppercase}
				for letter in message.upper():
								if letter in LETTERS:
												letter_count[letter] += 1

				return letter_count







def 			lowerCamelCase_		(       UpperCamelCase__				:      tuple      )     ->       str:





				"""simple docstring"""


				return x[0]







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       str:





				"""simple docstring"""


				__lowerCamelCase		       =    get_letter_count(UpperCamelCase__      )
				__lowerCamelCase		       =    {
				    freq: [] for letter, freq in letter_to_freq.items()
				}
				for letter in LETTERS:
								freq_to_letter[letter_to_freq[letter]].append(UpperCamelCase__      )

				__lowerCamelCase		       =    {}

				for freq in freq_to_letter:
								freq_to_letter[freq].sort(key=ETAOIN.find ,     reverse=UpperCamelCase__      )
								__lowerCamelCase		       =    ''.join(freq_to_letter[freq]      )

				__lowerCamelCase		       =    list(freq_to_letter_str.items()      )
				freq_pairs.sort(key=UpperCamelCase__ ,     reverse=UpperCamelCase__      )

				__lowerCamelCase		       =    [freq_pair[1] for freq_pair in freq_pairs]

				return "".join(UpperCamelCase__      )







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       int:





				"""simple docstring"""


				__lowerCamelCase		       =    get_frequency_order(UpperCamelCase__      )
				__lowerCamelCase		       =    0
				for common_letter in ETAOIN[:6]:
								if common_letter in freq_order[:6]:
												match_score += 1

				for uncommon_letter in ETAOIN[-6:]:
								if uncommon_letter in freq_order[-6:]:
												match_score += 1

				return match_score


if __name__ == "__main__":
					import doctest

					doctest.testmod()


