


'''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        lowercase     (							unittest.TestCase ):

		"""simple docstring"""

		_a   			=    ViTImageProcessor if is_vision_available() else None




		@property
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							return self.image_processor_tester.prepare_image_processor_dict()




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :str							 =			(3, 32, 128)
							UpperCamelCase__       :Dict							 =			tempfile.mkdtemp()

							# fmt: off
							UpperCamelCase__       :List[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
							UpperCamelCase__       :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__       :Tuple							 =			{
							    '''do_normalize''': False,
							    '''do_resize''': True,
							    '''image_processor_type''': '''ViTImageProcessor''',
							    '''resample''': 3,
							    '''size''': {'''height''': 32, '''width''': 128},
							}
							UpperCamelCase__       :Any							 =			os.path.join(self.tmpdirname   ,       UpperCamelCase_							)
							with open(self.image_processor_file   ,       '''w'''   ,       encoding='''utf-8'''							) as fp:
												json.dump(UpperCamelCase_   ,       UpperCamelCase_							)




		def    lowerCAmelCase__    (		self   ,       **UpperCamelCase_							):

							'''simple docstring'''


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




		def    lowerCAmelCase__    (		self   ,       **UpperCamelCase_							):

							'''simple docstring'''


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




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							shutil.rmtree(self.tmpdirname							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							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    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Tuple							 =			self.get_tokenizer()
							UpperCamelCase__       :str							 =			self.get_image_processor()

							UpperCamelCase__       :Dict							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)
							processor.save_pretrained(self.tmpdirname							)
							UpperCamelCase__       :int							 =			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    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :List[str]							 =			self.get_tokenizer()
							UpperCamelCase__       :List[str]							 =			self.get_image_processor()

							UpperCamelCase__       :int							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)
							processor.save_pretrained(self.tmpdirname							)

							UpperCamelCase__       :Any							 =			self.get_tokenizer(bos_token='''(BOS)'''   ,       eos_token='''(EOS)'''							)
							UpperCamelCase__       :List[Any]							 =			self.get_image_processor(do_normalize=UpperCamelCase_   ,       padding_value=1.0							)

							UpperCamelCase__       :Union[str, 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    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :int							 =			self.get_image_processor()
							UpperCamelCase__       :Tuple							 =			self.get_tokenizer()

							UpperCamelCase__       :List[str]							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

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

							UpperCamelCase__       :List[Any]							 =			image_processor(UpperCamelCase_   ,       return_tensors='''np'''							)
							UpperCamelCase__       :str							 =			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    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :int							 =			self.get_image_processor()
							UpperCamelCase__       :List[Any]							 =			self.get_tokenizer()

							UpperCamelCase__       :List[Any]							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :Any							 =			'''test'''

							UpperCamelCase__       :Dict							 =			processor(text=UpperCamelCase_							)

							UpperCamelCase__       :List[Any]							 =			tokenizer(UpperCamelCase_							)
							for key in encoded_tok.keys():
												self.assertListEqual(encoded_tok[key]   ,       encoded_processor[key]							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Tuple							 =			self.get_image_processor()
							UpperCamelCase__       :Optional[Any]							 =			self.get_tokenizer()

							UpperCamelCase__       :Union[str, Any]							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :Optional[Any]							 =			'''test'''
							UpperCamelCase__       :Tuple							 =			self.prepare_image_inputs()

							UpperCamelCase__       :List[str]							 =			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    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :List[Any]							 =			self.get_image_processor()
							UpperCamelCase__       :Tuple							 =			self.get_tokenizer()

							UpperCamelCase__       :Tuple							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

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

							UpperCamelCase__       :int							 =			processor.char_decode(UpperCamelCase_							)
							UpperCamelCase__       :List[str]							 =			tokenizer.batch_decode(UpperCamelCase_							)
							UpperCamelCase__       :Tuple							 =			[seq.replace(''' '''   ,       ''''''							) for seq in decoded_tok]

							self.assertListEqual(UpperCamelCase_   ,       UpperCamelCase_							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Union[str, Any]							 =			self.get_image_processor()
							UpperCamelCase__       :str							 =			self.get_tokenizer()

							UpperCamelCase__       :Optional[int]							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

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

							UpperCamelCase__       :int							 =			processor(text=UpperCamelCase_   ,       images=UpperCamelCase_							)

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




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Union[str, Any]							 =			self.get_image_processor()
							UpperCamelCase__       :str							 =			self.get_tokenizer()

							UpperCamelCase__       :Dict							 =			MgpstrProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :Dict							 =			torch.randn(1   ,       27   ,       38							)
							UpperCamelCase__       :Optional[Any]							 =			torch.randn(1   ,       27   ,       50257							)
							UpperCamelCase__       :Dict							 =			torch.randn(1   ,       27   ,       30522							)

							UpperCamelCase__       :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'''
from __future__ import annotations

from typing import Any


def       a				(      __a       )  ->     None:



					'''simple docstring'''






					create_state_space_tree(__a			, []			, 0       )


def       a				(      __a			, __a			, __a       )  ->     None:



					'''simple docstring'''






					if index == len(__a       ):
										print(__a       )
										return

					create_state_space_tree(__a			, __a			, index + 1       )
					current_subsequence.append(sequence[index]       )
					create_state_space_tree(__a			, __a			, index + 1       )
					current_subsequence.pop()


if __name__ == "__main__":
		__snake_case											=					[3, 1, 2, 4]
		generate_all_subsequences(seq)

		seq.clear()
		seq.extend(['''A''', '''B''', '''C'''])
		generate_all_subsequences(seq)