"""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 				A__       (						self						):







            """simple docstring"""



            return self.image_processor_tester.prepare_image_processor_dict()

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	(3, 32, 128)
            lowercase														=	tempfile.mkdtemp()

            # fmt: off
            lowercase														=	["""[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
            lowercase														=	dict(zip(__lowerCAmelCase		,       range(len(__lowerCAmelCase						)						)						)						)

            lowercase														=	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(__lowerCAmelCase						) + """\n"""						)

            lowercase														=	{
                """do_normalize""": False,
                """do_resize""": True,
                """image_processor_type""": """ViTImageProcessor""",
                """resample""": 3,
                """size""": {"""height""": 32, """width""": 128},
            }
            lowercase														=	os.path.join(self.tmpdirname		,       __lowerCAmelCase						)
            with open(self.image_processor_file		,       """w"""		,       encoding="""utf-8"""						) as fp:
                  json.dump(__lowerCAmelCase		,       __lowerCAmelCase						)

      def 				A__       (						self		,       **__lowerCAmelCase						):







            """simple docstring"""



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

      def 				A__       (						self		,       **__lowerCAmelCase						):







            """simple docstring"""



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

      def 				A__       (						self						):







            """simple docstring"""



            shutil.rmtree(self.tmpdirname						)

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	np.random.randint(255		,       size=(3, 30, 400)		,       dtype=np.uinta						)

            lowercase														=	Image.fromarray(np.moveaxis(__lowerCAmelCase		,       0		,       -1						)						)

            return image_input

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_tokenizer()
            lowercase														=	self.get_image_processor()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)
            processor.save_pretrained(self.tmpdirname						)
            lowercase														=	MgpstrProcessor.from_pretrained(self.tmpdirname		,       use_fast=__lowerCAmelCase						)

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

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

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_tokenizer()
            lowercase														=	self.get_image_processor()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)
            processor.save_pretrained(self.tmpdirname						)

            lowercase														=	self.get_tokenizer(bos_token="""(BOS)"""		,       eos_token="""(EOS)"""						)
            lowercase														=	self.get_image_processor(do_normalize=__lowerCAmelCase		,       padding_value=1.0						)

            lowercase														=	MgpstrProcessor.from_pretrained(
                self.tmpdirname		,       bos_token="""(BOS)"""		,       eos_token="""(EOS)"""		,       do_normalize=__lowerCAmelCase		,       padding_value=1.0						)

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

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

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	self.prepare_image_inputs()

            lowercase														=	image_processor(__lowerCAmelCase		,       return_tensors="""np"""						)
            lowercase														=	processor(images=__lowerCAmelCase		,       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						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	"""test"""

            lowercase														=	processor(text=__lowerCAmelCase						)

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

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	"""test"""
            lowercase														=	self.prepare_image_inputs()

            lowercase														=	processor(text=__lowerCAmelCase		,       images=__lowerCAmelCase						)

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

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

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

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

            lowercase														=	processor.char_decode(__lowerCAmelCase						)
            lowercase														=	tokenizer.batch_decode(__lowerCAmelCase						)
            lowercase														=	[seq.replace(""" """		,       """"""						) for seq in decoded_tok]

            self.assertListEqual(__lowerCAmelCase		,       __lowerCAmelCase						)

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	None
            lowercase														=	self.prepare_image_inputs()

            lowercase														=	processor(text=__lowerCAmelCase		,       images=__lowerCAmelCase						)

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







      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	MgpstrProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	torch.randn(1		,       27		,       38						)
            lowercase														=	torch.randn(1		,       27		,       5_0257						)
            lowercase														=	torch.randn(1		,       27		,       3_0522						)

            lowercase														=	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"""






def 			UpperCAmelCase__       (				lowerCAmelCase__     :str					,		lowerCAmelCase__     :Optional[Any]		) ->    int:
      '''simple docstring'''


      lowercase														=	[0 for i in range(r + 1		)]
      # nc0 = 1
      lowercase														=	1
      for i in range(1					,		n + 1		):
            # to compute current row from previous row.
            lowercase														=	min(lowerCAmelCase__					,		lowerCAmelCase__		)
            while j > 0:
                  c[j] += c[j - 1]
                  j -= 1
      return c[r]






print(binomial_coefficient(n=1_0, r=5))



