'''simple docstring'''




import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
   import torch


if is_vision_available():
   from PIL import Image

   from transformers import MgpstrProcessor, ViTImageProcessor






@require_torch
@require_vision
class 		__A							(unittest.TestCase ):
       snake_case							:List[str]					     =       ViTImageProcessor if is_vision_available() else None






       @property
       def       _snake_case    (   self   ):
              return self.image_processor_tester.prepare_image_processor_dict()






       def       _snake_case    (   self   ):
              __UpperCAmelCase	:					List[str]												=		(3, 32, 1_28)
              __UpperCAmelCase	:					List[Any]												=		tempfile.mkdtemp()

              # fmt: off
              __UpperCAmelCase	:					Optional[int]												=		["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
              # fmt: on
              __UpperCAmelCase	:					Dict												=		dict(zip(UpperCamelCase_					,  range(len(UpperCamelCase_   )   )   )   )

              __UpperCAmelCase	:					int												=		os.path.join(self.tmpdirname					,  VOCAB_FILES_NAMES["vocab_file"]   )
              with open(self.vocab_file					,  "w"					,  encoding="utf-8"   ) as fp:
                     fp.write(json.dumps(UpperCamelCase_   ) + "\n"   )

              __UpperCAmelCase	:					Any												=		{
                  """do_normalize""": False,
                  """do_resize""": True,
                  """image_processor_type""": """ViTImageProcessor""",
                  """resample""": 3,
                  """size""": {"""height""": 32, """width""": 1_28},
              }
              __UpperCAmelCase	:					Union[str, Any]												=		os.path.join(self.tmpdirname					,  UpperCamelCase_   )
              with open(self.image_processor_file					,  "w"					,  encoding="utf-8"   ) as fp:
                     json.dump(UpperCamelCase_					,  UpperCamelCase_   )






       def       _snake_case    (   self					,  **UpperCamelCase_   ):
              return MgpstrTokenizer.from_pretrained(self.tmpdirname					,  **UpperCamelCase_   )






       def       _snake_case    (   self					,  **UpperCamelCase_   ):
              return ViTImageProcessor.from_pretrained(self.tmpdirname					,  **UpperCamelCase_   )






       def       _snake_case    (   self   ):
              shutil.rmtree(self.tmpdirname   )






       def       _snake_case    (   self   ):
              __UpperCAmelCase	:					Optional[int]												=		np.random.randint(2_55					,  size=(3, 30, 4_00)					,  dtype=np.uinta   )

              __UpperCAmelCase	:					Union[str, Any]												=		Image.fromarray(np.moveaxis(UpperCamelCase_					,  0					,  -1   )   )

              return image_input






       def       _snake_case    (   self   ):
              __UpperCAmelCase	:					Optional[Any]												=		self.get_tokenizer()
              __UpperCAmelCase	:					Dict												=		self.get_image_processor()

              __UpperCAmelCase	:					Tuple												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )
              processor.save_pretrained(self.tmpdirname   )
              __UpperCAmelCase	:					Dict												=		MgpstrProcessor.from_pretrained(self.tmpdirname					,  use_fast=UpperCamelCase_   )

              self.assertEqual(processor.char_tokenizer.get_vocab()					,  tokenizer.get_vocab()   )
              self.assertIsInstance(processor.char_tokenizer					,  UpperCamelCase_   )

              self.assertEqual(processor.image_processor.to_json_string()					,  image_processor.to_json_string()   )
              self.assertIsInstance(processor.image_processor					,  UpperCamelCase_   )






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

              __UpperCAmelCase	:					List[Any]												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )
              processor.save_pretrained(self.tmpdirname   )

              __UpperCAmelCase	:					Optional[int]												=		self.get_tokenizer(bos_token="(BOS)"					,  eos_token="(EOS)"   )
              __UpperCAmelCase	:					Optional[Any]												=		self.get_image_processor(do_normalize=UpperCamelCase_					,  padding_value=1.0   )

              __UpperCAmelCase	:					Any												=		MgpstrProcessor.from_pretrained(
                  self.tmpdirname					,  bos_token="(BOS)"					,  eos_token="(EOS)"					,  do_normalize=UpperCamelCase_					,  padding_value=1.0   )

              self.assertEqual(processor.char_tokenizer.get_vocab()					,  tokenizer_add_kwargs.get_vocab()   )
              self.assertIsInstance(processor.char_tokenizer					,  UpperCamelCase_   )

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






       def       _snake_case    (   self   ):
              __UpperCAmelCase	:					Optional[int]												=		self.get_image_processor()
              __UpperCAmelCase	:					Union[str, Any]												=		self.get_tokenizer()

              __UpperCAmelCase	:					Optional[int]												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )

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

              __UpperCAmelCase	:					Optional[Any]												=		image_processor(UpperCamelCase_					,  return_tensors="np"   )
              __UpperCAmelCase	:					Tuple												=		processor(images=UpperCamelCase_					,  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       _snake_case    (   self   ):
              __UpperCAmelCase	:					Dict												=		self.get_image_processor()
              __UpperCAmelCase	:					str												=		self.get_tokenizer()

              __UpperCAmelCase	:					Dict												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )

              __UpperCAmelCase	:					int												=		"""test"""

              __UpperCAmelCase	:					Union[str, Any]												=		processor(text=UpperCamelCase_   )

              __UpperCAmelCase	:					List[Any]												=		tokenizer(UpperCamelCase_   )
              for key in encoded_tok.keys():
                     self.assertListEqual(encoded_tok[key]					,  encoded_processor[key]   )






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

              __UpperCAmelCase	:					Any												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )

              __UpperCAmelCase	:					List[str]												=		"""test"""
              __UpperCAmelCase	:					Dict												=		self.prepare_image_inputs()

              __UpperCAmelCase	:					Tuple												=		processor(text=UpperCamelCase_					,  images=UpperCamelCase_   )

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

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






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

              __UpperCAmelCase	:					Union[str, Any]												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )

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

              __UpperCAmelCase	:					Dict												=		processor.char_decode(UpperCamelCase_   )
              __UpperCAmelCase	:					Optional[int]												=		tokenizer.batch_decode(UpperCamelCase_   )
              __UpperCAmelCase	:					Optional[int]												=		[seq.replace(" "					,  ""   ) for seq in decoded_tok]

              self.assertListEqual(UpperCamelCase_					,  UpperCamelCase_   )






       def       _snake_case    (   self   ):
              __UpperCAmelCase	:					Optional[int]												=		self.get_image_processor()
              __UpperCAmelCase	:					Dict												=		self.get_tokenizer()

              __UpperCAmelCase	:					int												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )

              __UpperCAmelCase	:					str												=		None
              __UpperCAmelCase	:					List[str]												=		self.prepare_image_inputs()

              __UpperCAmelCase	:					List[Any]												=		processor(text=UpperCamelCase_					,  images=UpperCamelCase_   )

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







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

              __UpperCAmelCase	:					int												=		MgpstrProcessor(tokenizer=UpperCamelCase_					,  image_processor=UpperCamelCase_   )

              __UpperCAmelCase	:					Union[str, Any]												=		torch.randn(1					,  27					,  38   )
              __UpperCAmelCase	:					int												=		torch.randn(1					,  27					,  5_02_57   )
              __UpperCAmelCase	:					Dict												=		torch.randn(1					,  27					,  3_05_22   )

              __UpperCAmelCase	:					Union[str, Any]												=		processor.batch_decode([char_input, bpe_input, wp_input]   )

              self.assertListEqual(list(results.keys()   )					,  ["generated_text", "scores", "char_preds", "bpe_preds", "wp_preds"]   )










"""simple docstring"""
from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray

def 				_snake_case      (   __snake_case							:      float						, __snake_case							:      float						, __snake_case							:      bool = False   ):




   """simple docstring"""







   if radian_mode:
      return [magnitude * cos(__snake_case   ), magnitude * sin(__snake_case   )]
   return [magnitude * cos(radians(__snake_case   )   ), magnitude * sin(radians(__snake_case   )   )]

def 				_snake_case      (   __snake_case							:      NDArray[floataa]						, __snake_case							:      NDArray[floataa]						, __snake_case							:      float = 10**-1   ):




   """simple docstring"""







   _lowerCamelCase	:					NDArray[floataa]   =		cross(__snake_case						, __snake_case   )
   _lowerCamelCase	:					float   =		sum(__snake_case   )
   return abs(__snake_case   ) < eps


if __name__ == "__main__":
 # Test to check if it works
 UpperCAmelCase				=						array(
     [
         polar_force(718.4, 180 - 30),
         polar_force(879.54, 45),
         polar_force(100, -90),
     ]
 )

 UpperCAmelCase				=						array([[0, 0], [0, 0], [0, 0]])

 assert in_static_equilibrium(forces, location)

 # Problem 1 in image_data/2D_problems.jpg
 UpperCAmelCase				=						array(
     [
         polar_force(30 * 9.81, 15),
         polar_force(215, 180 - 45),
         polar_force(264, 90 - 30),
     ]
 )

 UpperCAmelCase				=						array([[0, 0], [0, 0], [0, 0]])

 assert in_static_equilibrium(forces, location)

 # Problem in image_data/2D_problems_1.jpg
 UpperCAmelCase				=						array([[0, -2000], [0, -1200], [0, 1_5600], [0, -1_2400]])

 UpperCAmelCase				=						array([[0, 0], [6, 0], [10, 0], [12, 0]])

 assert in_static_equilibrium(forces, location)

 import doctest

 doctest.testmod()

