"""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     ):







			'''simple docstring'''
			_UpperCamelCase  :						str					     =				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'''


										A__       :     Any								=			(3, 32, 128)
										A__       :     Optional[int]								=			tempfile.mkdtemp()

										# fmt: off
										A__       :     Union[str, 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
										A__       :     str								=			dict(zip(__lowerCamelCase   ,      range(len(__lowerCamelCase							)							)							)							)

										A__       :     str								=			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"""							)

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





			def 		lowerCamelCase					(			self   ,      **snake_case_							):







										'''simple docstring'''


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





			def 		lowerCamelCase					(			self   ,      **snake_case_							):







										'''simple docstring'''


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





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										shutil.rmtree(self.tmpdirname							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[int]								=			np.random.randint(255   ,      size=(3, 30, 400)   ,      dtype=np.uinta							)

										A__       :     Union[str, Any]								=			Image.fromarray(np.moveaxis(__lowerCamelCase   ,      0   ,      -1							)							)

										return image_input





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[Any]								=			self.get_tokenizer()
										A__       :     str								=			self.get_image_processor()

										A__       :     List[str]								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)
										processor.save_pretrained(self.tmpdirname							)
										A__       :     Optional[int]								=			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 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Any								=			self.get_tokenizer()
										A__       :     int								=			self.get_image_processor()

										A__       :     Union[str, Any]								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)
										processor.save_pretrained(self.tmpdirname							)

										A__       :     List[Any]								=			self.get_tokenizer(bos_token="""(BOS)"""   ,      eos_token="""(EOS)"""							)
										A__       :     List[Any]								=			self.get_image_processor(do_normalize=__lowerCamelCase   ,      padding_value=1.0							)

										A__       :     Any								=			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 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Tuple								=			self.get_image_processor()
										A__       :     Any								=			self.get_tokenizer()

										A__       :     Any								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)

										A__       :     Optional[Any]								=			self.prepare_image_inputs()

										A__       :     str								=			image_processor(__lowerCamelCase   ,      return_tensors="""np"""							)
										A__       :     Tuple								=			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 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Optional[Any]								=			self.get_image_processor()
										A__       :     List[Any]								=			self.get_tokenizer()

										A__       :     List[str]								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)

										A__       :     Union[str, Any]								=			'''test'''

										A__       :     Tuple								=			processor(text=__lowerCamelCase							)

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





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     int								=			self.get_image_processor()
										A__       :     Dict								=			self.get_tokenizer()

										A__       :     int								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)

										A__       :     List[Any]								=			'''test'''
										A__       :     List[Any]								=			self.prepare_image_inputs()

										A__       :     Any								=			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 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     int								=			self.get_image_processor()
										A__       :     Optional[int]								=			self.get_tokenizer()

										A__       :     Union[str, Any]								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)

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

										A__       :     Optional[Any]								=			processor.char_decode(__lowerCamelCase							)
										A__       :     int								=			tokenizer.batch_decode(__lowerCamelCase							)
										A__       :     int								=			[seq.replace(""" """   ,      """"""							) for seq in decoded_tok]

										self.assertListEqual(__lowerCamelCase   ,      __lowerCamelCase							)





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     int								=			self.get_image_processor()
										A__       :     Optional[int]								=			self.get_tokenizer()

										A__       :     Dict								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)

										A__       :     List[str]								=			None
										A__       :     Optional[int]								=			self.prepare_image_inputs()

										A__       :     Tuple								=			processor(text=__lowerCamelCase   ,      images=__lowerCamelCase							)

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





			def 		lowerCamelCase					(			self							):







										'''simple docstring'''


										A__       :     Dict								=			self.get_image_processor()
										A__       :     int								=			self.get_tokenizer()

										A__       :     Any								=			MgpstrProcessor(tokenizer=__lowerCamelCase   ,      image_processor=__lowerCamelCase							)

										A__       :     Union[str, Any]								=			torch.randn(1   ,      27   ,      38							)
										A__       :     Any								=			torch.randn(1   ,      27   ,      50_257							)
										A__       :     Union[str, Any]								=			torch.randn(1   ,      27   ,      30_522							)

										A__       :     Optional[Any]								=			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 ..utils import DummyObject, requires_backends




class 				UpperCAmelCase			(			metaclass=_snake_case						):
 UpperCAmelCase				=					["speech"]


 def __init__(      self							:	List[Any]			,       *__lowerCamelCase							:	List[Any]			,       **__lowerCamelCase							:	List[str] ):
    requires_backends(self			,       ['''speech'''] )




class 				UpperCAmelCase			(			metaclass=_snake_case						):
 UpperCAmelCase				=					["speech"]


 def __init__(      self							:	int			,       *__lowerCamelCase							:	List[Any]			,       **__lowerCamelCase							:	List[str] ):
    requires_backends(self			,       ['''speech'''] )



