





"""simple docstring"""





import cmath
import math


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  )						->complex:





  """simple docstring"""


  __UpperCAmelCase    :						Optional[int]       =						math.radians(UpperCAmelCase_  )
  __UpperCAmelCase    :						Union[str, Any]       =						math.radians(UpperCAmelCase_  )

  # Convert voltage and current to rectangular form
  __UpperCAmelCase    :						Dict       =						cmath.rect(UpperCAmelCase_  ,			UpperCAmelCase_  )
  __UpperCAmelCase    :						Optional[int]       =						cmath.rect(UpperCAmelCase_  ,			UpperCAmelCase_  )

  # Calculate apparent power
  return voltage_rect * current_rect


if __name__ == "__main__":
  import doctest

  doctest.testmod()






"""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 							snake_case							(			unittest.TestCase ):

      '''simple docstring'''



      def       A_					(							self       :      List[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Any       =						tempfile.mkdtemp()

        # fmt: off
        __UpperCAmelCase    :						Optional[int]       =						['''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
        __UpperCAmelCase    :						List[str]       =						dict(zip(__lowercase						,				range(len(__lowercase ) ) ) )
        __UpperCAmelCase    :						Any       =						['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
        __UpperCAmelCase    :						Dict       =						{'''unk_token''': '''<unk>'''}

        __UpperCAmelCase    :						Optional[int]       =						os.path.join(self.tmpdirname						,				VOCAB_FILES_NAMES['''vocab_file'''] )
        __UpperCAmelCase    :						Any       =						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(__lowercase ) + '''\n''' )
        with open(self.merges_file						,				'''w'''						,				encoding='''utf-8''' ) as fp:
          fp.write('''\n'''.join(__lowercase ) )

        __UpperCAmelCase    :						List[str]       =						{
            '''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],
        }
        __UpperCAmelCase    :						Any       =						os.path.join(self.tmpdirname						,				__lowercase )
        with open(self.image_processor_file						,				'''w'''						,				encoding='''utf-8''' ) as fp:
          json.dump(__lowercase						,				__lowercase )

      def       A_					(							self       :      Optional[Any]						,				**__lowercase       :      Tuple ):


        '''simple docstring'''




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

      def       A_					(							self       :      Any						,				**__lowercase       :      Optional[Any] ):


        '''simple docstring'''




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

      def       A_					(							self       :      Dict						,				**__lowercase       :      str ):


        '''simple docstring'''




        return ViTImageProcessor.from_pretrained(self.tmpdirname						,				**__lowercase )

      def       A_					(							self       :      List[str] ):


        '''simple docstring'''




        shutil.rmtree(self.tmpdirname )

      def       A_					(							self       :      Union[str, Any] ):


        '''simple docstring'''




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

        __UpperCAmelCase    :						int       =						[Image.fromarray(np.moveaxis(__lowercase						,				0						,				-1 ) ) for x in image_inputs]

        return image_inputs

      def       A_					(							self       :      Optional[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Optional[int]       =						self.get_tokenizer()
        __UpperCAmelCase    :						Dict       =						self.get_rust_tokenizer()
        __UpperCAmelCase    :						Optional[Any]       =						self.get_image_processor()

        __UpperCAmelCase    :						Any       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )
        processor_slow.save_pretrained(self.tmpdirname )
        __UpperCAmelCase    :						List[Any]       =						CLIPSegProcessor.from_pretrained(self.tmpdirname						,				use_fast=__lowercase )

        __UpperCAmelCase    :						Tuple       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )
        processor_fast.save_pretrained(self.tmpdirname )
        __UpperCAmelCase    :						str       =						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						,				__lowercase )
        self.assertIsInstance(processor_fast.tokenizer						,				__lowercase )

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

      def       A_					(							self       :      Optional[int] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Any       =						CLIPSegProcessor(tokenizer=self.get_tokenizer()						,				image_processor=self.get_image_processor() )
        processor.save_pretrained(self.tmpdirname )

        __UpperCAmelCase    :						Any       =						self.get_tokenizer(bos_token='''(BOS)'''						,				eos_token='''(EOS)''' )
        __UpperCAmelCase    :						Tuple       =						self.get_image_processor(do_normalize=__lowercase						,				padding_value=1.0 )

        __UpperCAmelCase    :						List[str]       =						CLIPSegProcessor.from_pretrained(
            self.tmpdirname						,				bos_token='''(BOS)'''						,				eos_token='''(EOS)'''						,				do_normalize=__lowercase						,				padding_value=1.0 )

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

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

      def       A_					(							self       :      int ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						self.get_image_processor()
        __UpperCAmelCase    :						List[str]       =						self.get_tokenizer()

        __UpperCAmelCase    :						Optional[Any]       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )

        __UpperCAmelCase    :						List[Any]       =						self.prepare_image_inputs()

        __UpperCAmelCase    :						Dict       =						image_processor(__lowercase						,				return_tensors='''np''' )
        __UpperCAmelCase    :						Optional[int]       =						processor(images=__lowercase						,				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       :      Dict ):


        '''simple docstring'''




        __UpperCAmelCase    :						Tuple       =						self.get_image_processor()
        __UpperCAmelCase    :						Any       =						self.get_tokenizer()

        __UpperCAmelCase    :						Any       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )

        __UpperCAmelCase    :						int       =						'''lower newer'''

        __UpperCAmelCase    :						int       =						processor(text=__lowercase )

        __UpperCAmelCase    :						Any       =						tokenizer(__lowercase )

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

      def       A_					(							self       :      List[str] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Tuple       =						self.get_image_processor()
        __UpperCAmelCase    :						Union[str, Any]       =						self.get_tokenizer()

        __UpperCAmelCase    :						List[Any]       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )

        __UpperCAmelCase    :						str       =						'''lower newer'''
        __UpperCAmelCase    :						int       =						self.prepare_image_inputs()

        __UpperCAmelCase    :						str       =						processor(text=__lowercase						,				images=__lowercase )

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

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

      def       A_					(							self       :      List[str] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Dict       =						self.get_image_processor()
        __UpperCAmelCase    :						str       =						self.get_tokenizer()

        __UpperCAmelCase    :						Any       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )

        __UpperCAmelCase    :						Union[str, Any]       =						self.prepare_image_inputs()
        __UpperCAmelCase    :						Optional[Any]       =						self.prepare_image_inputs()

        __UpperCAmelCase    :						Tuple       =						processor(images=__lowercase						,				visual_prompt=__lowercase )

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

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







      def       A_					(							self       :      str ):


        '''simple docstring'''




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

        __UpperCAmelCase    :						Any       =						CLIPSegProcessor(tokenizer=__lowercase						,				image_processor=__lowercase )

        __UpperCAmelCase    :						Dict       =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        __UpperCAmelCase    :						int       =						processor.batch_decode(__lowercase )
        __UpperCAmelCase    :						int       =						tokenizer.batch_decode(__lowercase )

        self.assertListEqual(__lowercase						,				__lowercase )