





"""simple docstring"""





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

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


if is_vision_available():
							from PIL import Image

							from transformers import AlignProcessor, EfficientNetImageProcessor
@require_vision
class 		SCREAMING_SNAKE_CASE_				(     unittest.TestCase ):
				"""simple docstring"""




				def        __lowercase	(  self	:int      ):
											__lowerCamelCase   :   str       =tempfile.mkdtemp()

											__lowerCamelCase   :   List[Any]       =[
											    '''[UNK]''',
											    '''[CLS]''',
											    '''[SEP]''',
											    '''[PAD]''',
											    '''[MASK]''',
											    '''want''',
											    '''##want''',
											    '''##ed''',
											    '''wa''',
											    '''un''',
											    '''runn''',
											    '''##ing''',
											    ''',''',
											    '''low''',
											    '''lowest''',
											]
											__lowerCamelCase   :   List[Any]       =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]      )      )

											__lowerCamelCase   :   Any       ={
											    '''do_resize''': True,
											    '''size''': 20,
											    '''do_center_crop''': True,
											    '''crop_size''': 18,
											    '''do_normalize''': True,
											    '''image_mean''': [0.48145466, 0.4578275, 0.40821073],
											    '''image_std''': [0.26862954, 0.26130258, 0.27577711],
											}
											__lowerCamelCase   :   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	:int    ,     **__lowercase	:List[Any]      ):
											return BertTokenizer.from_pretrained(self.tmpdirname    ,     **__lowercase      )




				def        __lowercase	(  self	:Optional[Any]    ,     **__lowercase	:int      ):
											return BertTokenizerFast.from_pretrained(self.tmpdirname    ,     **__lowercase      )




				def        __lowercase	(  self	:List[str]    ,     **__lowercase	:str      ):
											return EfficientNetImageProcessor.from_pretrained(self.tmpdirname    ,     **__lowercase      )




				def        __lowercase	(  self	:str      ):
											shutil.rmtree(self.tmpdirname      )




				def        __lowercase	(  self	:Dict      ):
											__lowerCamelCase   :   Union[str, Any]       =[np.random.randint(255    ,     size=(3, 30, 400)    ,     dtype=np.uinta      )]
											__lowerCamelCase   :   Union[str, Any]       =[Image.fromarray(np.moveaxis(__lowercase    ,     0    ,     -1      )      ) for x in image_inputs]
											return image_inputs




				def        __lowercase	(  self	:Any      ):
											__lowerCamelCase   :   List[str]       =self.get_tokenizer()
											__lowerCamelCase   :   List[str]       =self.get_rust_tokenizer()
											__lowerCamelCase   :   str       =self.get_image_processor()

											__lowerCamelCase   :   Tuple       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )
											processor_slow.save_pretrained(self.tmpdirname      )
											__lowerCamelCase   :   str       =AlignProcessor.from_pretrained(self.tmpdirname    ,     use_fast=__lowercase      )

											__lowerCamelCase   :   List[str]       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )
											processor_fast.save_pretrained(self.tmpdirname      )
											__lowerCamelCase   :   List[str]       =AlignProcessor.from_pretrained(self.tmpdirname      )

											self.assertEqual(processor_slow.tokenizer.get_vocab()    ,     tokenizer_slow.get_vocab()      )
											self.assertEqual(processor_fast.tokenizer.get_vocab()    ,     tokenizer_fast.get_vocab()      )
											self.assertEqual(tokenizer_slow.get_vocab()    ,     tokenizer_fast.get_vocab()      )
											self.assertIsInstance(processor_slow.tokenizer    ,     __lowercase      )
											self.assertIsInstance(processor_fast.tokenizer    ,     __lowercase      )

											self.assertEqual(processor_slow.image_processor.to_json_string()    ,     image_processor.to_json_string()      )
											self.assertEqual(processor_fast.image_processor.to_json_string()    ,     image_processor.to_json_string()      )
											self.assertIsInstance(processor_slow.image_processor    ,     __lowercase      )
											self.assertIsInstance(processor_fast.image_processor    ,     __lowercase      )




				def        __lowercase	(  self	:Any      ):
											__lowerCamelCase   :   Tuple       =AlignProcessor(tokenizer=self.get_tokenizer()    ,     image_processor=self.get_image_processor()      )
											processor.save_pretrained(self.tmpdirname      )

											__lowerCamelCase   :   List[str]       =self.get_tokenizer(bos_token='''(BOS)'''    ,     eos_token='''(EOS)'''      )
											__lowerCamelCase   :   List[str]       =self.get_image_processor(do_normalize=__lowercase    ,     padding_value=1.0      )

											__lowerCamelCase   :   List[str]       =AlignProcessor.from_pretrained(
											    self.tmpdirname    ,     bos_token='''(BOS)'''    ,     eos_token='''(EOS)'''    ,     do_normalize=__lowercase    ,     padding_value=1.0      )

											self.assertEqual(processor.tokenizer.get_vocab()    ,     tokenizer_add_kwargs.get_vocab()      )
											self.assertIsInstance(processor.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	:Union[str, Any]      ):
											__lowerCamelCase   :   Optional[int]       =self.get_image_processor()
											__lowerCamelCase   :   Any       =self.get_tokenizer()

											__lowerCamelCase   :   Optional[int]       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )

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

											__lowerCamelCase   :   int       =image_processor(__lowercase    ,     return_tensors='''np'''      )
											__lowerCamelCase   :   str       =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	:Dict      ):
											__lowerCamelCase   :   Tuple       =self.get_image_processor()
											__lowerCamelCase   :   str       =self.get_tokenizer()

											__lowerCamelCase   :   Any       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )

											__lowerCamelCase   :   Optional[Any]       ='''lower newer'''

											__lowerCamelCase   :   int       =processor(text=__lowercase      )

											__lowerCamelCase   :   Optional[Any]       =tokenizer(__lowercase    ,     padding='''max_length'''    ,     max_length=64      )

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




				def        __lowercase	(  self	:List[Any]      ):
											__lowerCamelCase   :   Optional[Any]       =self.get_image_processor()
											__lowerCamelCase   :   str       =self.get_tokenizer()

											__lowerCamelCase   :   Any       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )

											__lowerCamelCase   :   Tuple       ='''lower newer'''
											__lowerCamelCase   :   Union[str, Any]       =self.prepare_image_inputs()

											__lowerCamelCase   :   List[str]       =processor(text=__lowercase    ,     images=__lowercase      )

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

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




				def        __lowercase	(  self	:Dict      ):
											__lowerCamelCase   :   List[str]       =self.get_image_processor()
											__lowerCamelCase   :   int       =self.get_tokenizer()

											__lowerCamelCase   :   Dict       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )

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

											__lowerCamelCase   :   Tuple       =processor.batch_decode(__lowercase      )
											__lowerCamelCase   :   Any       =tokenizer.batch_decode(__lowercase      )

											self.assertListEqual(__lowercase    ,     __lowercase      )




				def        __lowercase	(  self	:int      ):
											__lowerCamelCase   :   List[Any]       =self.get_image_processor()
											__lowerCamelCase   :   List[Any]       =self.get_tokenizer()

											__lowerCamelCase   :   Any       =AlignProcessor(tokenizer=__lowercase    ,     image_processor=__lowercase      )

											__lowerCamelCase   :   Optional[Any]       ='''lower newer'''
											__lowerCamelCase   :   Tuple       =self.prepare_image_inputs()

											__lowerCamelCase   :   Union[str, Any]       =processor(text=__lowercase    ,     images=__lowercase      )

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











"""simple docstring"""





import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment
@require_huggingface_suite
class 		SCREAMING_SNAKE_CASE_				(     unittest.TestCase ):
				"""simple docstring"""




				def        __lowercase	(  self	:Dict      ):
											__lowerCamelCase   :   Union[str, Any]       =inspect.getfile(accelerate.test_utils      )
											__lowerCamelCase   :   Union[str, Any]       =os.path.sep.join(
											    mod_file.split(os.path.sep      )[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']      )

											from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

											__lowerCamelCase   :   List[str]       =test_metrics




				@require_cpu
				def        __lowercase	(  self	:Optional[Any]      ):
											debug_launcher(self.test_metrics.main    ,     num_processes=1      )




				@require_cpu
				def        __lowercase	(  self	:int      ):
											debug_launcher(self.test_metrics.main      )




				@require_single_gpu
				def        __lowercase	(  self	:int      ):
											self.test_metrics.main()




				@require_multi_gpu
				def        __lowercase	(  self	:Dict      ):
											print(f'Found {torch.cuda.device_count()} devices.'      )
											__lowerCamelCase   :   Union[str, Any]       =['''torchrun''', f'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
											with patch_environment(omp_num_threads=1      ):
																		execute_subprocess_async(__lowercase    ,     env=os.environ.copy()      )




