



"""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):
			__magic_name__     					=     ViTImageProcessor if is_vision_available() else None



			@property
			def 				__lowercase					(			self							:				Union[str, Any]		)							->					Optional[Any]:
									return self.image_processor_tester.prepare_image_processor_dict()



			def 				__lowercase					(			self							:				Union[str, Any]		)							->					Any:
									snake_case   :			Union[str, Any]						    = (3, 32, 128)
									snake_case   :			Tuple						    = tempfile.mkdtemp()

									# fmt: off
									snake_case   :			Any						    = ["[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
									snake_case   :			Union[str, Any]						    = dict(zip(_lowercase   ,	range(len(_lowercase		)		)		)		)

									snake_case   :			Any						    = 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(_lowercase		) + "\n"		)

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



			def 				__lowercase					(			self							:				Optional[int]   ,	**_lowercase							:				str		)							->					List[Any]:
									return MgpstrTokenizer.from_pretrained(self.tmpdirname   ,	**_lowercase		)



			def 				__lowercase					(			self							:				Optional[Any]   ,	**_lowercase							:				Optional[Any]		)							->					Optional[Any]:
									return ViTImageProcessor.from_pretrained(self.tmpdirname   ,	**_lowercase		)



			def 				__lowercase					(			self							:				List[Any]		)							->					List[Any]:
									shutil.rmtree(self.tmpdirname		)



			def 				__lowercase					(			self							:				str		)							->					str:
									snake_case   :			List[Any]						    = np.random.randint(255   ,	size=(3, 30, 400)   ,	dtype=np.uinta		)

									snake_case   :			Dict						    = Image.fromarray(np.moveaxis(_lowercase   ,	0   ,	-1		)		)

									return image_input



			def 				__lowercase					(			self							:				Optional[Any]		)							->					Dict:
									snake_case   :			Optional[Any]						    = self.get_tokenizer()
									snake_case   :			Optional[int]						    = self.get_image_processor()

									snake_case   :			Dict						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)
									processor.save_pretrained(self.tmpdirname		)
									snake_case   :			List[Any]						    = MgpstrProcessor.from_pretrained(self.tmpdirname   ,	use_fast=_lowercase		)

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

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



			def 				__lowercase					(			self							:				Optional[int]		)							->					int:
									snake_case   :			Tuple						    = self.get_tokenizer()
									snake_case   :			int						    = self.get_image_processor()

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

									snake_case   :			Dict						    = self.get_tokenizer(bos_token="(BOS)"   ,	eos_token="(EOS)"		)
									snake_case   :			Dict						    = self.get_image_processor(do_normalize=_lowercase   ,	padding_value=1.0		)

									snake_case   :			Optional[int]						    = MgpstrProcessor.from_pretrained(
									    self.tmpdirname   ,	bos_token="(BOS)"   ,	eos_token="(EOS)"   ,	do_normalize=_lowercase   ,	padding_value=1.0		)

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

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



			def 				__lowercase					(			self							:				str		)							->					Any:
									snake_case   :			Any						    = self.get_image_processor()
									snake_case   :			Optional[int]						    = self.get_tokenizer()

									snake_case   :			Dict						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)

									snake_case   :			List[str]						    = self.prepare_image_inputs()

									snake_case   :			List[Any]						    = image_processor(_lowercase   ,	return_tensors="np"		)
									snake_case   :			Any						    = processor(images=_lowercase   ,	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 				__lowercase					(			self							:				Optional[Any]		)							->					List[Any]:
									snake_case   :			Any						    = self.get_image_processor()
									snake_case   :			Optional[Any]						    = self.get_tokenizer()

									snake_case   :			List[str]						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)

									snake_case   :			Any						    = "test"

									snake_case   :			Optional[int]						    = processor(text=_lowercase		)

									snake_case   :			Union[str, Any]						    = tokenizer(_lowercase		)
									for key in encoded_tok.keys():
															self.assertListEqual(encoded_tok[key]   ,	encoded_processor[key]		)



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

									snake_case   :			int						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)

									snake_case   :			int						    = "test"
									snake_case   :			Union[str, Any]						    = self.prepare_image_inputs()

									snake_case   :			Union[str, Any]						    = processor(text=_lowercase   ,	images=_lowercase		)

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

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



			def 				__lowercase					(			self							:				Union[str, Any]		)							->					Any:
									snake_case   :			Any						    = self.get_image_processor()
									snake_case   :			Union[str, Any]						    = self.get_tokenizer()

									snake_case   :			List[Any]						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)

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

									snake_case   :			List[str]						    = processor.char_decode(_lowercase		)
									snake_case   :			List[str]						    = tokenizer.batch_decode(_lowercase		)
									snake_case   :			str						    = [seq.replace(" "   ,	""		) for seq in decoded_tok]

									self.assertListEqual(_lowercase   ,	_lowercase		)



			def 				__lowercase					(			self							:				Optional[int]		)							->					int:
									snake_case   :			Dict						    = self.get_image_processor()
									snake_case   :			Optional[Any]						    = self.get_tokenizer()

									snake_case   :			List[str]						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)

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

									snake_case   :			Optional[int]						    = processor(text=_lowercase   ,	images=_lowercase		)

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



			def 				__lowercase					(			self							:				Any		)							->					str:
									snake_case   :			List[str]						    = self.get_image_processor()
									snake_case   :			Dict						    = self.get_tokenizer()

									snake_case   :			List[str]						    = MgpstrProcessor(tokenizer=_lowercase   ,	image_processor=_lowercase		)

									snake_case   :			Union[str, Any]						    = torch.randn(1   ,	27   ,	38		)
									snake_case   :			Tuple						    = torch.randn(1   ,	27   ,	50257		)
									snake_case   :			int						    = torch.randn(1   ,	27   ,	30522		)

									snake_case   :			Tuple						    = 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"""







import requests

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							str     ,		lowerCamelCase_:							str ):
						"""simple docstring"""






						snake_case   :			List[str]						    = {"Content-Type": "application/json"}
						snake_case   :			int						    = requests.post(lowerCamelCase_     ,		json={"text": message_body}     ,		headers=lowerCamelCase_ )
						if response.status_code != 2_0_0:
												snake_case   :			str						    = (
												    "Request to slack returned an error "
												    f'''{response.status_code}, the response is:\n{response.text}'''
												)
												raise ValueError(lowerCamelCase_ )


if __name__ == "__main__":
			# Set the slack url to the one provided by Slack when you create the webhook at
			# https://my.slack.com/services/new/incoming-webhook/
			send_slack_message('<YOUR MESSAGE BODY>', '<SLACK CHANNEL URL>')



