






"""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 			lowerCAmelCase__			(    unittest.TestCase   ):
   def       __a							(		self      :	Optional[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Union[str, Any]							=							tempfile.mkdtemp()

        # fmt: off
        UpperCAmelCase__						:    List[str]							=							["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__						:    str							=							dict(zip(snake_case__							,			range(len(snake_case__							)							)							)							)
        UpperCAmelCase__						:    Tuple							=							["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
        UpperCAmelCase__						:    Optional[int]							=							{"unk_token": "<unk>"}

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

        UpperCAmelCase__						:    Any							=							{
            "do_resize": True,
            "size": 2_0,
            "do_center_crop": True,
            "crop_size": 1_8,
            "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],
        }
        UpperCAmelCase__						:    Dict							=							os.path.join(self.tmpdirname							,			snake_case__							)
        with open(self.image_processor_file							,			"w"							,			encoding="utf-8"							) as fp:
             json.dump(snake_case__							,			snake_case__							)
   def       __a							(		self      :	Union[str, Any]							,			**snake_case__      :	str							):


        '''simple docstring'''
        return CLIPTokenizer.from_pretrained(self.tmpdirname							,			**snake_case__							)
   def       __a							(		self      :	List[Any]							,			**snake_case__      :	Optional[Any]							):


        '''simple docstring'''
        return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,			**snake_case__							)
   def       __a							(		self      :	List[str]							,			**snake_case__      :	Optional[int]							):


        '''simple docstring'''
        return CLIPImageProcessor.from_pretrained(self.tmpdirname							,			**snake_case__							)
   def       __a							(		self      :	Optional[Any]							):


        '''simple docstring'''
        shutil.rmtree(self.tmpdirname							)
   def       __a							(		self      :	Union[str, Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    str							=							[np.random.randint(2_5_5							,			size=(3, 3_0, 4_0_0)							,			dtype=np.uinta							)]

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

        return image_inputs
   def       __a							(		self      :	List[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Any							=							self.get_tokenizer()
        UpperCAmelCase__						:    int							=							self.get_rust_tokenizer()
        UpperCAmelCase__						:    List[Any]							=							self.get_image_processor()

        UpperCAmelCase__						:    Optional[int]							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)
        processor_slow.save_pretrained(self.tmpdirname							)
        UpperCAmelCase__						:    Dict							=							CLIPProcessor.from_pretrained(self.tmpdirname							,			use_fast=snake_case__							)

        UpperCAmelCase__						:    Optional[Any]							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)
        processor_fast.save_pretrained(self.tmpdirname							)
        UpperCAmelCase__						:    Union[str, Any]							=							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							,			snake_case__							)
        self.assertIsInstance(processor_fast.tokenizer							,			snake_case__							)

        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							,			snake_case__							)
        self.assertIsInstance(processor_fast.image_processor							,			snake_case__							)
   def       __a							(		self      :	str							):


        '''simple docstring'''
        UpperCAmelCase__						:    Tuple							=							CLIPProcessor(tokenizer=self.get_tokenizer()							,			image_processor=self.get_image_processor()							)
        processor.save_pretrained(self.tmpdirname							)

        UpperCAmelCase__						:    List[Any]							=							self.get_tokenizer(bos_token="(BOS)"							,			eos_token="(EOS)"							)
        UpperCAmelCase__						:    Dict							=							self.get_image_processor(do_normalize=snake_case__							,			padding_value=1.0							)

        UpperCAmelCase__						:    List[Any]							=							CLIPProcessor.from_pretrained(
            self.tmpdirname							,			bos_token="(BOS)"							,			eos_token="(EOS)"							,			do_normalize=snake_case__							,			padding_value=1.0							)

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

        self.assertEqual(processor.image_processor.to_json_string()							,			image_processor_add_kwargs.to_json_string()							)
        self.assertIsInstance(processor.image_processor							,			snake_case__							)
   def       __a							(		self      :	Dict							):


        '''simple docstring'''
        UpperCAmelCase__						:    Union[str, Any]							=							self.get_image_processor()
        UpperCAmelCase__						:    int							=							self.get_tokenizer()

        UpperCAmelCase__						:    Optional[int]							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    str							=							self.prepare_image_inputs()

        UpperCAmelCase__						:    Dict							=							image_processor(snake_case__							,			return_tensors="np"							)
        UpperCAmelCase__						:    int							=							processor(images=snake_case__							,			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      :	Union[str, Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    int							=							self.get_image_processor()
        UpperCAmelCase__						:    Tuple							=							self.get_tokenizer()

        UpperCAmelCase__						:    Optional[int]							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    int							=							"lower newer"

        UpperCAmelCase__						:    Any							=							processor(text=snake_case__							)

        UpperCAmelCase__						:    str							=							tokenizer(snake_case__							)

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


        '''simple docstring'''
        UpperCAmelCase__						:    List[str]							=							self.get_image_processor()
        UpperCAmelCase__						:    List[str]							=							self.get_tokenizer()

        UpperCAmelCase__						:    Optional[int]							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    Any							=							"lower newer"
        UpperCAmelCase__						:    Any							=							self.prepare_image_inputs()

        UpperCAmelCase__						:    Optional[int]							=							processor(text=snake_case__							,			images=snake_case__							)

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

        # test if it raises when no input is passed
        with pytest.raises(snake_case__							):
             processor()
   def       __a							(		self      :	Optional[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Dict							=							self.get_image_processor()
        UpperCAmelCase__						:    List[Any]							=							self.get_tokenizer()

        UpperCAmelCase__						:    int							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    int							=							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        UpperCAmelCase__						:    List[Any]							=							processor.batch_decode(snake_case__							)
        UpperCAmelCase__						:    Union[str, Any]							=							tokenizer.batch_decode(snake_case__							)

        self.assertListEqual(snake_case__							,			snake_case__							)




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


        '''simple docstring'''
        UpperCAmelCase__						:    int							=							self.get_image_processor()
        UpperCAmelCase__						:    Optional[Any]							=							self.get_tokenizer()

        UpperCAmelCase__						:    List[Any]							=							CLIPProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    List[Any]							=							"lower newer"
        UpperCAmelCase__						:    Dict							=							self.prepare_image_inputs()

        UpperCAmelCase__						:    List[str]							=							processor(text=snake_case__							,			images=snake_case__							)

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










"""simple docstring"""



from __future__ import annotations

from math import pow, sqrt


def 	SCREAMING_SNAKE_CASE__       (  snake_case       : float			,					snake_case       : float			,					snake_case       : float				)->		dict[str, float]:






     '''simple docstring'''



     if (resistance, reactance, impedance).count(0				) != 1:
          raise ValueError("One and only one argument must be 0"				)
     if resistance == 0:
          return {"resistance": sqrt(pow(snake_case			,					2				) - pow(snake_case			,					2				)				)}
     elif reactance == 0:
          return {"reactance": sqrt(pow(snake_case			,					2				) - pow(snake_case			,					2				)				)}
     elif impedance == 0:
          return {"impedance": sqrt(pow(snake_case			,					2				) + pow(snake_case			,					2				)				)}
     else:
          raise ValueError("Exactly one argument must be 0"				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


