





'''simple docstring'''

from __future__ import annotations

from collections.abc import MutableSequence

class       UpperCAmelCase :




		def __init__(self      :	str							,			A__      :	str							,			A__      :	Any				)					-> None:
						if len(lowerCamelCase_				) != degree + 1:
										raise ValueError(
										    "The number of coefficients should be equal to the degree + 1."				)

						lowercase         = list(lowerCamelCase_				)
						lowercase         = degree




		def __add__(self      :	List[str]							,			A__      :	Union[str, Any]				)					-> Polynomial:

						if self.degree > polynomial_a.degree:
										lowercase         = self.coefficients[:]
										for i in range(polynomial_a.degree + 1				):
														coefficients[i] += polynomial_a.coefficients[i]
										return Polynomial(self.degree							,			lowerCamelCase_				)
						else:
										lowercase         = polynomial_a.coefficients[:]
										for i in range(self.degree + 1				):
														coefficients[i] += self.coefficients[i]
										return Polynomial(polynomial_a.degree							,			lowerCamelCase_				)




		def __sub__(self      :	Optional[int]							,			A__      :	List[Any]				)					-> Polynomial:
						return self + polynomial_a * Polynomial(0							,			[-1]				)




		def __neg__(self      :	int				)					-> Polynomial:
						return Polynomial(self.degree							,			[-c for c in self.coefficients]				)




		def __mul__(self      :	Tuple							,			A__      :	Any				)					-> Polynomial:
						lowercase         = [0] * (self.degree + polynomial_a.degree + 1)
						for i in range(self.degree + 1				):
										for j in range(polynomial_a.degree + 1				):
														coefficients[i + j] += (
														    self.coefficients[i] * polynomial_a.coefficients[j]
														)

						return Polynomial(self.degree + polynomial_a.degree							,			lowerCamelCase_				)




		def 				UpperCAmelCase__   (self      :	str							,			A__      :	List[str]				)					-> int | float:
						lowercase         = 0
						for i in range(self.degree + 1				):
										result += self.coefficients[i] * (substitution**i)
						return result




		def __str__(self      :	Optional[Any]				)					-> str:
						lowercase         = ""
						for i in range(self.degree							,			-1							,			-1				):
										if self.coefficients[i] == 0:
														continue
										elif self.coefficients[i] > 0:
														if polynomial:
																		polynomial += " + "
										else:
														polynomial += " - "

										if i == 0:
														polynomial += str(abs(self.coefficients[i]				)				)
										elif i == 1:
														polynomial += str(abs(self.coefficients[i]				)				) + "x"
										else:
														polynomial += str(abs(self.coefficients[i]				)				) + "x^" + str(lowerCamelCase_				)

						return polynomial




		def __repr__(self      :	Dict				)					-> str:
						return self.__str__()




		def 				UpperCAmelCase__   (self      :	Union[str, Any]				)					-> Polynomial:
						lowercase         = [0] * self.degree
						for i in range(self.degree				):
										lowercase         = self.coefficients[i + 1] * (i + 1)
						return Polynomial(self.degree - 1							,			lowerCamelCase_				)




		def 				UpperCAmelCase__   (self      :	List[Any]							,			A__      :	Optional[int] = 0				)					-> Polynomial:
						lowercase         = [0] * (self.degree + 2)
						lowercase         = constant
						for i in range(self.degree + 1				):
										lowercase         = self.coefficients[i] / (i + 1)
						return Polynomial(self.degree + 1							,			lowerCamelCase_				)




		def __eq__(self      :	List[str]							,			A__      :	Tuple				)					-> bool:
						if not isinstance(lowerCamelCase_							,			lowerCamelCase_				):
										return False

						if self.degree != polynomial_a.degree:
										return False

						for i in range(self.degree + 1				):
										if self.coefficients[i] != polynomial_a.coefficients[i]:
														return False

						return True





		def __ne__(self      :	Any							,			A__      :	List[str]				)					-> bool:
						return not self.__eq__(lowerCamelCase_				)











'''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       UpperCAmelCase (						unittest.TestCase  ):
		UpperCAmelCase					:	Optional[int] 			=		ViTImageProcessor if is_vision_available() else None




		@property
		def 				UpperCAmelCase__   (self      :	Optional[int]				)					-> Optional[Any]:
						return self.image_processor_tester.prepare_image_processor_dict()




		def 				UpperCAmelCase__   (self      :	str				)					-> int:
						lowercase         = (3, 3_2, 1_2_8)
						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(A__							,			range(len(A__				)				)				)				)

						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(A__				) + "\n"				)

						lowercase         = {
						    "do_normalize": False,
						    "do_resize": True,
						    "image_processor_type": "ViTImageProcessor",
						    "resample": 3,
						    "size": {"height": 3_2, "width": 1_2_8},
						}
						lowercase         = os.path.join(self.tmpdirname							,			A__				)
						with open(self.image_processor_file							,			"w"							,			encoding="utf-8"				) as fp:
										json.dump(A__							,			A__				)




		def 				UpperCAmelCase__   (self      :	Dict							,			**A__      :	List[Any]				)					-> Union[str, Any]:
						return MgpstrTokenizer.from_pretrained(self.tmpdirname							,			**A__				)




		def 				UpperCAmelCase__   (self      :	Any							,			**A__      :	Tuple				)					-> Tuple:
						return ViTImageProcessor.from_pretrained(self.tmpdirname							,			**A__				)




		def 				UpperCAmelCase__   (self      :	Optional[int]				)					-> int:
						shutil.rmtree(self.tmpdirname				)




		def 				UpperCAmelCase__   (self      :	str				)					-> List[str]:
						lowercase         = np.random.randint(2_5_5							,			size=(3, 3_0, 4_0_0)							,			dtype=np.uinta				)

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

						return image_input




		def 				UpperCAmelCase__   (self      :	str				)					-> List[Any]:
						lowercase         = self.get_tokenizer()
						lowercase         = self.get_image_processor()

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

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

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




		def 				UpperCAmelCase__   (self      :	Any				)					-> Optional[int]:
						lowercase         = self.get_tokenizer()
						lowercase         = self.get_image_processor()

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

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

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

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

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




		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> List[Any]:
						lowercase         = self.get_image_processor()
						lowercase         = self.get_tokenizer()

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

						lowercase         = self.prepare_image_inputs()

						lowercase         = image_processor(A__							,			return_tensors="np"				)
						lowercase         = processor(images=A__							,			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 				UpperCAmelCase__   (self      :	List[Any]				)					-> Union[str, Any]:
						lowercase         = self.get_image_processor()
						lowercase         = self.get_tokenizer()

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

						lowercase         = "test"

						lowercase         = processor(text=A__				)

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




		def 				UpperCAmelCase__   (self      :	int				)					-> Optional[int]:
						lowercase         = self.get_image_processor()
						lowercase         = self.get_tokenizer()

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

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

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

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

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




		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> Union[str, Any]:
						lowercase         = self.get_image_processor()
						lowercase         = self.get_tokenizer()

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

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

						self.assertListEqual(A__							,			A__				)




		def 				UpperCAmelCase__   (self      :	Any				)					-> Optional[int]:
						lowercase         = self.get_image_processor()
						lowercase         = self.get_tokenizer()

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

						lowercase         = None
						lowercase         = self.prepare_image_inputs()

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

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





		def 				UpperCAmelCase__   (self      :	int				)					-> Optional[Any]:
						lowercase         = self.get_image_processor()
						lowercase         = self.get_tokenizer()

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

						lowercase         = torch.randn(1							,			2_7							,			3_8				)
						lowercase         = torch.randn(1							,			2_7							,			5_0_2_5_7				)
						lowercase         = torch.randn(1							,			2_7							,			3_0_5_2_2				)

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

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




