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						):






 '''simple docstring'''






 UpperCAmelCase_     			= ViTImageProcessor if is_vision_available() else None




 @property
 def 		__snake_case						(      self :  str):







        '''simple docstring'''



        return self.image_processor_tester.prepare_image_processor_dict()




 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        lowerCAmelCase__					     = (3, 32, 128)
        lowerCAmelCase__					     = tempfile.mkdtemp()

        # fmt: off
        lowerCAmelCase__					     = ['[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
        lowerCAmelCase__					     = dict(zip(lowercase__      ,   range(len(lowercase__))))

        lowerCAmelCase__					     = 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')

        lowerCAmelCase__					     = {
            'do_normalize': False,
            'do_resize': True,
            'image_processor_type': 'ViTImageProcessor',
            'resample': 3,
            'size': {'height': 32, 'width': 128},
        }
        lowerCAmelCase__					     = os.path.join(self.tmpdirname      ,   lowercase__)
        with open(self.image_processor_file      ,   'w'      ,   encoding='utf-8') as fp:
               json.dump(lowercase__      ,   lowercase__)




 def 		__snake_case						(      self :  Tuple      ,   **lowercase__ :  List[str]):







        '''simple docstring'''



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




 def 		__snake_case						(      self :  List[str]      ,   **lowercase__ :  int):







        '''simple docstring'''



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




 def 		__snake_case						(      self :  Any):







        '''simple docstring'''



        shutil.rmtree(self.tmpdirname)




 def 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = np.random.randint(255      ,   size=(3, 30, 400)      ,   dtype=np.uinta)

        lowerCAmelCase__					     = Image.fromarray(np.moveaxis(lowercase__      ,   0      ,   -1))

        return image_input




 def 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_tokenizer()
        lowerCAmelCase__					     = self.get_image_processor()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)
        processor.save_pretrained(self.tmpdirname)
        lowerCAmelCase__					     = 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 		__snake_case						(      self :  int):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_tokenizer()
        lowerCAmelCase__					     = self.get_image_processor()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)
        processor.save_pretrained(self.tmpdirname)

        lowerCAmelCase__					     = self.get_tokenizer(bos_token='(BOS)'      ,   eos_token='(EOS)')
        lowerCAmelCase__					     = self.get_image_processor(do_normalize=lowercase__      ,   padding_value=1.0)

        lowerCAmelCase__					     = 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 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_image_processor()
        lowerCAmelCase__					     = self.get_tokenizer()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)

        lowerCAmelCase__					     = self.prepare_image_inputs()

        lowerCAmelCase__					     = image_processor(lowercase__      ,   return_tensors='np')
        lowerCAmelCase__					     = 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 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_image_processor()
        lowerCAmelCase__					     = self.get_tokenizer()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)

        lowerCAmelCase__					     = 'test'

        lowerCAmelCase__					     = processor(text=lowercase__)

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




 def 		__snake_case						(      self :  Dict):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_image_processor()
        lowerCAmelCase__					     = self.get_tokenizer()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)

        lowerCAmelCase__					     = 'test'
        lowerCAmelCase__					     = self.prepare_image_inputs()

        lowerCAmelCase__					     = 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 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_image_processor()
        lowerCAmelCase__					     = self.get_tokenizer()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)

        lowerCAmelCase__					     = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

        lowerCAmelCase__					     = processor.char_decode(lowercase__)
        lowerCAmelCase__					     = tokenizer.batch_decode(lowercase__)
        lowerCAmelCase__					     = [seq.replace(' '      ,   '') for seq in decoded_tok]

        self.assertListEqual(lowercase__      ,   lowercase__)




 def 		__snake_case						(      self :  str):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_image_processor()
        lowerCAmelCase__					     = self.get_tokenizer()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)

        lowerCAmelCase__					     = None
        lowerCAmelCase__					     = self.prepare_image_inputs()

        lowerCAmelCase__					     = processor(text=lowercase__      ,   images=lowercase__)

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




 def 		__snake_case						(      self :  Tuple):







        '''simple docstring'''



        lowerCAmelCase__					     = self.get_image_processor()
        lowerCAmelCase__					     = self.get_tokenizer()

        lowerCAmelCase__					     = MgpstrProcessor(tokenizer=lowercase__      ,   image_processor=lowercase__)

        lowerCAmelCase__					     = torch.randn(1      ,   27      ,   38)
        lowerCAmelCase__					     = torch.randn(1      ,   27      ,   50_257)
        lowerCAmelCase__					     = torch.randn(1      ,   27      ,   30_522)

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

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

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
    from ..ta.tokenization_ta import TaTokenizer
else:
    from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase__     						=			TaTokenizer

if is_tokenizers_available():
    from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
    from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase__     						=			TaTokenizerFast

lowerCAmelCase__     						=			{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			[
        'MT5EncoderModel',
        'MT5ForConditionalGeneration',
        'MT5ForQuestionAnswering',
        'MT5Model',
        'MT5PreTrainedModel',
        'MT5Stack',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__     						=			['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
    from .configuration_mta import MTaConfig, MTaOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mta import (
            MTaEncoderModel,
            MTaForConditionalGeneration,
            MTaForQuestionAnswering,
            MTaModel,
            MTaPreTrainedModel,
            MTaStack,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
    import sys

    lowerCAmelCase__     						=			_LazyModule(
        __name__,
        globals()['__file__'],
        _import_structure,
        extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
        module_spec=__spec__,
    )
