
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       _lowerCAmelCase  (		unittest.TestCase							):

 """simple docstring"""
 SCREAMING_SNAKE_CASE_				:					str       						=ViTImageProcessor if is_vision_available() else None

 @property
 def      __lowerCAmelCase  (						self			:			Union[str, Any]   ):






      """simple docstring"""



      return self.image_processor_tester.prepare_image_processor_dict()

 def      __lowerCAmelCase  (						self			:			int   ):






      """simple docstring"""



      UpperCamelCase						    =					(3, 32, 1_28)
      UpperCamelCase						    =					tempfile.mkdtemp()

      # fmt: off
      UpperCamelCase						    =					['[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(zip(SCREAMING_SNAKE_CASE__					, range(len(SCREAMING_SNAKE_CASE__   )   )   )   )

      UpperCamelCase						    =					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(SCREAMING_SNAKE_CASE__   ) + '\n'   )

      UpperCamelCase						    =					{
          'do_normalize': False,
          'do_resize': True,
          'image_processor_type': 'ViTImageProcessor',
          'resample': 3,
          'size': {'height': 32, 'width': 1_28},
      }
      UpperCamelCase						    =					os.path.join(self.tmpdirname					, SCREAMING_SNAKE_CASE__   )
      with open(self.image_processor_file					, 'w'					, encoding='utf-8'   ) as fp:
           json.dump(SCREAMING_SNAKE_CASE__					, SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			int					, **SCREAMING_SNAKE_CASE__			:			int   ):






      """simple docstring"""



      return MgpstrTokenizer.from_pretrained(self.tmpdirname					, **SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			str					, **SCREAMING_SNAKE_CASE__			:			str   ):






      """simple docstring"""



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

 def      __lowerCAmelCase  (						self			:			Optional[int]   ):






      """simple docstring"""



      shutil.rmtree(self.tmpdirname   )

 def      __lowerCAmelCase  (						self			:			int   ):






      """simple docstring"""



      UpperCamelCase						    =					np.random.randint(2_55					, size=(3, 30, 4_00)					, dtype=np.uinta   )

      UpperCamelCase						    =					Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE__					, 0					, -1   )   )

      return image_input

 def      __lowerCAmelCase  (						self			:			str   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_tokenizer()
      UpperCamelCase						    =					self.get_image_processor()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )
      processor.save_pretrained(self.tmpdirname   )
      UpperCamelCase						    =					MgpstrProcessor.from_pretrained(self.tmpdirname					, use_fast=SCREAMING_SNAKE_CASE__   )

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

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

 def      __lowerCAmelCase  (						self			:			Optional[Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_tokenizer()
      UpperCamelCase						    =					self.get_image_processor()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )
      processor.save_pretrained(self.tmpdirname   )

      UpperCamelCase						    =					self.get_tokenizer(bos_token='(BOS)'					, eos_token='(EOS)'   )
      UpperCamelCase						    =					self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE__					, padding_value=1.0   )

      UpperCamelCase						    =					MgpstrProcessor.from_pretrained(
          self.tmpdirname					, bos_token='(BOS)'					, eos_token='(EOS)'					, do_normalize=SCREAMING_SNAKE_CASE__					, padding_value=1.0   )

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

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

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					self.prepare_image_inputs()

      UpperCamelCase						    =					image_processor(SCREAMING_SNAKE_CASE__					, return_tensors='np'   )
      UpperCamelCase						    =					processor(images=SCREAMING_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      __lowerCAmelCase  (						self			:			Union[str, Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					'test'

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					tokenizer(SCREAMING_SNAKE_CASE__   )
      for key in encoded_tok.keys():
           self.assertListEqual(encoded_tok[key]					, encoded_processor[key]   )

 def      __lowerCAmelCase  (						self			:			List[str]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					'test'
      UpperCamelCase						    =					self.prepare_image_inputs()

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__					, images=SCREAMING_SNAKE_CASE__   )

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

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

 def      __lowerCAmelCase  (						self			:			int   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

      UpperCamelCase						    =					processor.char_decode(SCREAMING_SNAKE_CASE__   )
      UpperCamelCase						    =					tokenizer.batch_decode(SCREAMING_SNAKE_CASE__   )
      UpperCamelCase						    =					[seq.replace(' '					, ''   ) for seq in decoded_tok]

      self.assertListEqual(SCREAMING_SNAKE_CASE__					, SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					None
      UpperCamelCase						    =					self.prepare_image_inputs()

      UpperCamelCase						    =					processor(text=SCREAMING_SNAKE_CASE__					, images=SCREAMING_SNAKE_CASE__   )

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






 def      __lowerCAmelCase  (						self			:			List[str]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.get_image_processor()
      UpperCamelCase						    =					self.get_tokenizer()

      UpperCamelCase						    =					MgpstrProcessor(tokenizer=SCREAMING_SNAKE_CASE__					, image_processor=SCREAMING_SNAKE_CASE__   )

      UpperCamelCase						    =					torch.randn(1					, 27					, 38   )
      UpperCamelCase						    =					torch.randn(1					, 27					, 5_02_57   )
      UpperCamelCase						    =					torch.randn(1					, 27					, 3_05_22   )

      UpperCamelCase						    =					processor.batch_decode([char_input, bpe_input, wp_input]   )

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




from decimal import Decimal, getcontext
from math import ceil, factorial

def  __lowerCamelCase					( _lowercase			)       ->      str:

     if not isinstance(_lowercase						,     _lowercase			):
          raise TypeError('Undefined for non-integers'			)
     elif precision < 1:
          raise ValueError('Undefined for non-natural numbers'			)

     UpperCamelCase						    =					precision
     UpperCamelCase						    =					ceil(precision / 14			)
     UpperCamelCase						    =					426880 * Decimal(10005			).sqrt()
     UpperCamelCase						    =					1
     UpperCamelCase						    =					13591409
     UpperCamelCase						    =					Decimal(_lowercase			)
     for k in range(1						,     _lowercase			):
          UpperCamelCase						    =					factorial(6 * k			) // (factorial(3 * k			) * factorial(_lowercase			) ** 3)
          linear_term += 545140134
          exponential_term *= -262537412640768000
          partial_sum += Decimal(multinomial_term * linear_term			) / exponential_term
     return str(constant_term / partial_sum			)[:-1]


if __name__ == "__main__":
 _snake_case      = 50
 print(F"The first {n} digits of pi is: {pi(n)}")


