


'''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 						_snake_case    (   unittest.TestCase		):
					lowerCAmelCase					:Optional[int]            =    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__     :    str         =   (3, 32, 128)
								UpperCAmelCase__     :    Union[str, 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__     :    Optional[Any]         =   dict(zip(__UpperCAmelCase							,							range(len(__UpperCAmelCase))))

								UpperCAmelCase__     :    Dict         =   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__     :    Dict         =   {
								    """do_normalize""": False,
								    """do_resize""": True,
								    """image_processor_type""": """ViTImageProcessor""",
								    """resample""": 3,
								    """size""": {"""height""": 32, """width""": 128},
								}
								UpperCAmelCase__     :    Optional[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							,							**_lowerCamelCase):
								return MgpstrTokenizer.from_pretrained(self.tmpdirname							,							**__UpperCAmelCase)




					def  snake_case__  (					self							,							**_lowerCamelCase):
								return ViTImageProcessor.from_pretrained(self.tmpdirname							,							**__UpperCAmelCase)




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




					def  snake_case__  (					self):
								UpperCAmelCase__     :    Union[str, Any]         =   np.random.randint(255							,							size=(3, 30, 400)							,							dtype=np.uinta)

								UpperCAmelCase__     :    List[Any]         =   Image.fromarray(np.moveaxis(__UpperCAmelCase							,							0							,							-1))

								return image_input




					def  snake_case__  (					self):
								UpperCAmelCase__     :    Union[str, Any]         =   self.get_tokenizer()
								UpperCAmelCase__     :    Any         =   self.get_image_processor()

								UpperCAmelCase__     :    Dict         =   MgpstrProcessor(tokenizer=__UpperCAmelCase							,							image_processor=__UpperCAmelCase)
								processor.save_pretrained(self.tmpdirname)
								UpperCAmelCase__     :    Optional[Any]         =   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[Any]         =   self.get_tokenizer()
								UpperCAmelCase__     :    List[Any]         =   self.get_image_processor()

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

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

								UpperCAmelCase__     :    List[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__     :    str         =   self.get_image_processor()
								UpperCAmelCase__     :    Dict         =   self.get_tokenizer()

								UpperCAmelCase__     :    Tuple         =   MgpstrProcessor(tokenizer=__UpperCAmelCase							,							image_processor=__UpperCAmelCase)

								UpperCAmelCase__     :    int         =   self.prepare_image_inputs()

								UpperCAmelCase__     :    Tuple         =   image_processor(__UpperCAmelCase							,							return_tensors="""np""")
								UpperCAmelCase__     :    Any         =   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__     :    Optional[int]         =   self.get_image_processor()
								UpperCAmelCase__     :    Optional[Any]         =   self.get_tokenizer()

								UpperCAmelCase__     :    List[str]         =   MgpstrProcessor(tokenizer=__UpperCAmelCase							,							image_processor=__UpperCAmelCase)

								UpperCAmelCase__     :    str         =   """test"""

								UpperCAmelCase__     :    Tuple         =   processor(text=__UpperCAmelCase)

								UpperCAmelCase__     :    Optional[int]         =   tokenizer(__UpperCAmelCase)
								for key in encoded_tok.keys():
											self.assertListEqual(encoded_tok[key]							,							encoded_processor[key])




					def  snake_case__  (					self):
								UpperCAmelCase__     :    Dict         =   self.get_image_processor()
								UpperCAmelCase__     :    List[str]         =   self.get_tokenizer()

								UpperCAmelCase__     :    List[Any]         =   MgpstrProcessor(tokenizer=__UpperCAmelCase							,							image_processor=__UpperCAmelCase)

								UpperCAmelCase__     :    Optional[Any]         =   """test"""
								UpperCAmelCase__     :    Any         =   self.prepare_image_inputs()

								UpperCAmelCase__     :    Dict         =   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__     :    List[Any]         =   self.get_image_processor()
								UpperCAmelCase__     :    int         =   self.get_tokenizer()

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

								UpperCAmelCase__     :    Union[str, 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[Any]         =   tokenizer.batch_decode(__UpperCAmelCase)
								UpperCAmelCase__     :    Dict         =   [seq.replace(""" """							,							"""""") for seq in decoded_tok]

								self.assertListEqual(__UpperCAmelCase							,							__UpperCAmelCase)




					def  snake_case__  (					self):
								UpperCAmelCase__     :    Any         =   self.get_image_processor()
								UpperCAmelCase__     :    Dict         =   self.get_tokenizer()

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

								UpperCAmelCase__     :    List[Any]         =   None
								UpperCAmelCase__     :    int         =   self.prepare_image_inputs()

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

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




					def  snake_case__  (					self):
								UpperCAmelCase__     :    Union[str, Any]         =   self.get_image_processor()
								UpperCAmelCase__     :    int         =   self.get_tokenizer()

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

								UpperCAmelCase__     :    Tuple         =   torch.randn(1							,							27							,							38)
								UpperCAmelCase__     :    Optional[Any]         =   torch.randn(1							,							27							,							5_0257)
								UpperCAmelCase__     :    Dict         =   torch.randn(1							,							27							,							3_0522)

								UpperCAmelCase__     :    List[Any]         =   processor.batch_decode([char_input, bpe_input, wp_input])

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







def 						_a    (      a :int = 100 )							->			int:
 a		  =      n * (n + 1) * (2 * n + 1) / 6
 a		  =      (n * (n + 1) / 2) ** 2
 return int(square_of_sum - sum_of_squares )


if __name__ == "__main__":
     print(f"""{solution() = }""")


