


import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor





@require_tokenizers
@require_vision
class       A    (   unittest.TestCase ):


							def 			_A       (self					):
									__lowercase=			tempfile.mkdtemp()

									# fmt: off
									__lowercase=			['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
									# fmt: on
									__lowercase=			os.path.join(self.tmpdirname      ,				VOCAB_FILES_NAMES['vocab_file']					)
									with open(self.vocab_file      ,				'w'      ,				encoding='utf-8'					) as vocab_writer:
											vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]					)					)

									__lowercase=			{
									    'do_resize': True,
									    'size': {'height': 1_8, 'width': 1_8},
									    'do_normalize': True,
									    'image_mean': [0.5, 0.5, 0.5],
									    'image_std': [0.5, 0.5, 0.5],
									}
									__lowercase=			os.path.join(self.tmpdirname      ,				UpperCamelCase__					)
									with open(self.image_processor_file      ,				'w'      ,				encoding='utf-8'					) as fp:
											json.dump(UpperCamelCase__      ,				UpperCamelCase__					)


							def 			_A       (self      ,				**lowerCAmelCase					):
									return BertTokenizer.from_pretrained(self.tmpdirname      ,				**UpperCamelCase__					)


							def 			_A       (self      ,				**lowerCAmelCase					):
									return ViTImageProcessor.from_pretrained(self.tmpdirname      ,				**UpperCamelCase__					)


							def 			_A       (self					):
									shutil.rmtree(self.tmpdirname					)


							def 			_A       (self					):
									__lowercase=			[np.random.randint(2_5_5      ,				size=(3, 3_0, 4_0_0)      ,				dtype=np.uinta					)]

									__lowercase=			[Image.fromarray(np.moveaxis(UpperCamelCase__      ,				0      ,				-1					)					) for x in image_inputs]

									return image_inputs


							def 			_A       (self					):
									__lowercase=			self.get_tokenizer()
									__lowercase=			self.get_image_processor()

									__lowercase=			VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__      ,				image_processor=UpperCamelCase__					)

									processor.save_pretrained(self.tmpdirname					)
									__lowercase=			VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname					)

									self.assertEqual(processor.tokenizer.get_vocab()      ,				tokenizer.get_vocab()					)
									self.assertIsInstance(processor.tokenizer      ,				(BertTokenizer, BertTokenizerFast)					)

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


							def 			_A       (self					):
									__lowercase=			VisionTextDualEncoderProcessor(
									    tokenizer=self.get_tokenizer()      ,				image_processor=self.get_image_processor()					)
									processor.save_pretrained(self.tmpdirname					)

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

									__lowercase=			VisionTextDualEncoderProcessor.from_pretrained(
									    self.tmpdirname      ,				bos_token='(BOS)'      ,				eos_token='(EOS)'      ,				do_normalize=UpperCamelCase__      ,				padding_value=1.0					)

									self.assertEqual(processor.tokenizer.get_vocab()      ,				tokenizer_add_kwargs.get_vocab()					)
									self.assertIsInstance(processor.tokenizer      ,				(BertTokenizer, BertTokenizerFast)					)

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


							def 			_A       (self					):
									__lowercase=			self.get_image_processor()
									__lowercase=			self.get_tokenizer()

									__lowercase=			VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__      ,				image_processor=UpperCamelCase__					)

									__lowercase=			self.prepare_image_inputs()

									__lowercase=			image_processor(UpperCamelCase__      ,				return_tensors='np'					)
									__lowercase=			processor(images=UpperCamelCase__      ,				return_tensors='np'					)

									for key in input_feat_extract.keys():
											self.assertAlmostEqual(input_feat_extract[key].sum()      ,				input_processor[key].sum()      ,				delta=1E-2					)


							def 			_A       (self					):
									__lowercase=			self.get_image_processor()
									__lowercase=			self.get_tokenizer()

									__lowercase=			VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__      ,				image_processor=UpperCamelCase__					)

									__lowercase=			'lower newer'

									__lowercase=			processor(text=UpperCamelCase__					)

									__lowercase=			tokenizer(UpperCamelCase__					)

									for key in encoded_tok.keys():
											self.assertListEqual(encoded_tok[key]      ,				encoded_processor[key]					)


							def 			_A       (self					):
									__lowercase=			self.get_image_processor()
									__lowercase=			self.get_tokenizer()

									__lowercase=			VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__      ,				image_processor=UpperCamelCase__					)

									__lowercase=			'lower newer'
									__lowercase=			self.prepare_image_inputs()

									__lowercase=			processor(text=UpperCamelCase__      ,				images=UpperCamelCase__					)

									self.assertListEqual(list(inputs.keys()					)      ,				['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values']					)

									# test if it raises when no input is passed
									with self.assertRaises(UpperCamelCase__					):
											processor()


							def 			_A       (self					):
									__lowercase=			self.get_image_processor()
									__lowercase=			self.get_tokenizer()

									__lowercase=			VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__      ,				image_processor=UpperCamelCase__					)

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

									__lowercase=			processor.batch_decode(UpperCamelCase__					)
									__lowercase=			tokenizer.batch_decode(UpperCamelCase__					)

									self.assertListEqual(UpperCamelCase__      ,				UpperCamelCase__					)







							def 			_A       (self					):
									__lowercase=			self.get_image_processor()
									__lowercase=			self.get_tokenizer()

									__lowercase=			VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__      ,				image_processor=UpperCamelCase__					)

									__lowercase=			'lower newer'
									__lowercase=			self.prepare_image_inputs()

									__lowercase=			processor(text=UpperCamelCase__      ,				images=UpperCamelCase__					)

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











'''simple docstring'''


_lowerCamelCase	:       int      	=	"0.21.0"

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
   from .utils import rich

