"""simple docstring"""



import os

# Precomputes a list of the 100 first triangular numbers
__lowercase		:		int														=							[int(0.5 * n * (n + 1)) for n in range(1, 101)]





def    SCREAMING_SNAKE_CASE       (     ):
     __snake_case				=							os.path.dirname(os.path.realpath(snake_case))
     __snake_case				=							os.path.join(snake_case,      '''words.txt''')

     __snake_case				=							''''''
     with open(snake_case) as f:
          __snake_case				=							f.readline()

     __snake_case				=							[word.strip('''"''') for word in words.strip('''\r\n''').split(''',''')]
     __snake_case				=							[
         word
         for word in [sum(ord(snake_case) - 64 for x in word) for word in words]
         if word in TRIANGULAR_NUMBERS
     ]
     return len(snake_case)


if __name__ == "__main__":
       print(solution())
"""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 CLIPSegProcessor, ViTImageProcessor



@require_vision
class      _A	(						unittest.TestCase					):




    """simple docstring"""




    def  lowercase					(		self							:     Optional[int]    )    ->       List[str]:
         __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''': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
             '''image_std''': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
         }
         __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  lowercase					(		self							:     Optional[Any]	,      **A_							:     Dict    )    ->       Any:
         return CLIPTokenizer.from_pretrained(self.tmpdirname	,      **A_    )
    def  lowercase					(		self							:     Optional[int]	,      **A_							:     str    )    ->       str:
         return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,      **A_    )
    def  lowercase					(		self							:     Any	,      **A_							:     Tuple    )    ->       Tuple:
         return ViTImageProcessor.from_pretrained(self.tmpdirname	,      **A_    )
    def  lowercase					(		self							:     Optional[int]    )    ->       Optional[Any]:
         shutil.rmtree(self.tmpdirname    )
    def  lowercase					(		self							:     int    )    ->       Optional[Any]:
         __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  lowercase					(		self							:     Optional[Any]    )    ->       Optional[Any]:
         __snake_case				=							self.get_tokenizer()
         __snake_case				=							self.get_rust_tokenizer()
         __snake_case				=							self.get_image_processor()

         __snake_case				=							CLIPSegProcessor(tokenizer=A_	,      image_processor=A_    )
         processor_slow.save_pretrained(self.tmpdirname    )
         __snake_case				=							CLIPSegProcessor.from_pretrained(self.tmpdirname	,      use_fast=A_    )

         __snake_case				=							CLIPSegProcessor(tokenizer=A_	,      image_processor=A_    )
         processor_fast.save_pretrained(self.tmpdirname    )
         __snake_case				=							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	,      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  lowercase					(		self							:     Union[str, Any]    )    ->       Any:
         __snake_case				=							CLIPSegProcessor(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				=							CLIPSegProcessor.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  lowercase					(		self							:     Any    )    ->       str:
         __snake_case				=							self.get_image_processor()
         __snake_case				=							self.get_tokenizer()

         __snake_case				=							CLIPSegProcessor(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_feat_extract.keys():
              self.assertAlmostEqual(input_feat_extract[key].sum()	,      input_processor[key].sum()	,      delta=1E-2    )
    def  lowercase					(		self							:     List[str]    )    ->       List[Any]:
         __snake_case				=							self.get_image_processor()
         __snake_case				=							self.get_tokenizer()

         __snake_case				=							CLIPSegProcessor(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  lowercase					(		self							:     List[Any]    )    ->       str:
         __snake_case				=							self.get_image_processor()
         __snake_case				=							self.get_tokenizer()

         __snake_case				=							CLIPSegProcessor(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  lowercase					(		self							:     Union[str, Any]    )    ->       Any:
         __snake_case				=							self.get_image_processor()
         __snake_case				=							self.get_tokenizer()

         __snake_case				=							CLIPSegProcessor(tokenizer=A_	,      image_processor=A_    )

         __snake_case				=							self.prepare_image_inputs()
         __snake_case				=							self.prepare_image_inputs()

         __snake_case				=							processor(images=A_	,      visual_prompt=A_    )

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

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







    def  lowercase					(		self							:     Optional[int]    )    ->       Dict:
         __snake_case				=							self.get_image_processor()
         __snake_case				=							self.get_tokenizer()

         __snake_case				=							CLIPSegProcessor(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_    )