






'''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 	SCREAMING_SNAKE_CASE	(      unittest.TestCase  ):




       def 					a_					(					self      : Any					):


            """simple docstring"""







            __lowerCamelCase						:       str				   =				tempfile.mkdtemp()

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

            __lowerCamelCase						:       Tuple				   =				os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["""vocab_file"""]					)
            __lowerCamelCase						:       List[str]				   =				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__					)					)

            __lowerCamelCase						:       Union[str, Any]				   =				{
                """do_resize""": True,
                """size""": 20,
                """do_center_crop""": True,
                """crop_size""": 18,
                """do_normalize""": True,
                """image_mean""": [0.4814_5466, 0.457_8275, 0.4082_1073],
                """image_std""": [0.2686_2954, 0.2613_0258, 0.2757_7711],
            }
            __lowerCamelCase						:       str				   =				os.path.join(self.tmpdirname	,    A__					)
            with open(self.image_processor_file	,    """w"""	,    encoding="""utf-8"""					) as fp:
                 json.dump(A__	,    A__					)




       def 					a_					(					self      : Dict	,    **A__      : Optional[Any]					):


            """simple docstring"""







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




       def 					a_					(					self      : Optional[int]	,    **A__      : Any					):


            """simple docstring"""







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




       def 					a_					(					self      : str	,    **A__      : Union[str, Any]					):


            """simple docstring"""







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




       def 					a_					(					self      : List[Any]					):


            """simple docstring"""







            shutil.rmtree(self.tmpdirname					)




       def 					a_					(					self      : List[str]					):


            """simple docstring"""







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

            __lowerCamelCase						:       Tuple				   =				[Image.fromarray(np.moveaxis(A__	,    0	,    -1					)					) for x in image_inputs]

            return image_inputs




       def 					a_					(					self      : Optional[int]					):


            """simple docstring"""







            __lowerCamelCase						:       int				   =				self.get_tokenizer()
            __lowerCamelCase						:       List[Any]				   =				self.get_rust_tokenizer()
            __lowerCamelCase						:       Any				   =				self.get_image_processor()

            __lowerCamelCase						:       Dict				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)
            processor_slow.save_pretrained(self.tmpdirname					)
            __lowerCamelCase						:       Optional[Any]				   =				CLIPProcessor.from_pretrained(self.tmpdirname	,    use_fast=A__					)

            __lowerCamelCase						:       Optional[int]				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)
            processor_fast.save_pretrained(self.tmpdirname					)
            __lowerCamelCase						:       List[str]				   =				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 					a_					(					self      : Optional[int]					):


            """simple docstring"""







            __lowerCamelCase						:       List[str]				   =				CLIPProcessor(tokenizer=self.get_tokenizer()	,    image_processor=self.get_image_processor()					)
            processor.save_pretrained(self.tmpdirname					)

            __lowerCamelCase						:       Any				   =				self.get_tokenizer(bos_token="""(BOS)"""	,    eos_token="""(EOS)"""					)
            __lowerCamelCase						:       str				   =				self.get_image_processor(do_normalize=A__	,    padding_value=1.0					)

            __lowerCamelCase						:       int				   =				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 					a_					(					self      : int					):


            """simple docstring"""







            __lowerCamelCase						:       List[Any]				   =				self.get_image_processor()
            __lowerCamelCase						:       Any				   =				self.get_tokenizer()

            __lowerCamelCase						:       Tuple				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)

            __lowerCamelCase						:       str				   =				self.prepare_image_inputs()

            __lowerCamelCase						:       Tuple				   =				image_processor(A__	,    return_tensors="""np"""					)
            __lowerCamelCase						:       Union[str, Any]				   =				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 					a_					(					self      : Any					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[Any]				   =				self.get_image_processor()
            __lowerCamelCase						:       Optional[int]				   =				self.get_tokenizer()

            __lowerCamelCase						:       str				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)

            __lowerCamelCase						:       str				   =				"""lower newer"""

            __lowerCamelCase						:       Optional[int]				   =				processor(text=A__					)

            __lowerCamelCase						:       Tuple				   =				tokenizer(A__					)

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




       def 					a_					(					self      : Dict					):


            """simple docstring"""







            __lowerCamelCase						:       List[Any]				   =				self.get_image_processor()
            __lowerCamelCase						:       Optional[Any]				   =				self.get_tokenizer()

            __lowerCamelCase						:       str				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)

            __lowerCamelCase						:       Optional[int]				   =				"""lower newer"""
            __lowerCamelCase						:       Union[str, Any]				   =				self.prepare_image_inputs()

            __lowerCamelCase						:       List[Any]				   =				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 					a_					(					self      : Dict					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[int]				   =				self.get_image_processor()
            __lowerCamelCase						:       List[Any]				   =				self.get_tokenizer()

            __lowerCamelCase						:       Optional[Any]				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)

            __lowerCamelCase						:       Any				   =				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            __lowerCamelCase						:       Tuple				   =				processor.batch_decode(A__					)
            __lowerCamelCase						:       int				   =				tokenizer.batch_decode(A__					)

            self.assertListEqual(A__	,    A__					)




       def 					a_					(					self      : List[str]					):


            """simple docstring"""







            __lowerCamelCase						:       List[Any]				   =				self.get_image_processor()
            __lowerCamelCase						:       Union[str, Any]				   =				self.get_tokenizer()

            __lowerCamelCase						:       List[Any]				   =				CLIPProcessor(tokenizer=A__	,    image_processor=A__					)

            __lowerCamelCase						:       int				   =				"""lower newer"""
            __lowerCamelCase						:       Optional[Any]				   =				self.prepare_image_inputs()

            __lowerCamelCase						:       Union[str, Any]				   =				processor(text=A__	,    images=A__					)

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











'''simple docstring'''

from __future__ import annotations

from typing import Any
def     __lowercase  (_lowercase     )   ->     int:


     """simple docstring"""
     if not postfix_notation:
          return 0

     __lowerCamelCase						:       Optional[int]				   =				{"""+""", """-""", """*""", """/"""}
     __lowerCamelCase						:       list[Any]				   =				[]

     for token in postfix_notation:
          if token in operations:
               __lowerCamelCase   ,      __lowerCamelCase						:       List[Any]				   =				stack.pop(), stack.pop()
               if token == "+":
                    stack.append(a + b     )
               elif token == "-":
                    stack.append(a - b     )
               elif token == "*":
                    stack.append(a * b     )
               else:
                    if a * b < 0 and a % b != 0:
                         stack.append(a // b + 1     )
                    else:
                         stack.append(a // b     )
          else:
               stack.append(int(_lowercase     )     )

     return stack.pop()


if __name__ == "__main__":
   import doctest

   doctest.testmod()



