
"""simple docstring"""


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available


if is_torch_available():
							from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_11
else:
							lowerCAmelCase			=		False

if is_vision_available():
							from PIL import Image

							from transformers import (
							    AutoProcessor,
							    PixaStructImageProcessor,
							    PixaStructProcessor,
							    PreTrainedTokenizerFast,
							    TaTokenizer,
							)

@unittest.skipIf(
    not is_torch_greater_or_equal_than_1_11   ,      reason="""`Pix2StructImageProcessor` requires `torch>=1.11.0`."""   ,      )
@require_vision
@require_torch
class 					A_			(  unittest.TestCase     ):



							"""simple docstring"""






							def    UpperCAmelCase__							(						self						:Tuple ):





										"""simple docstring"""

										lowerCamelCase__			:  Dict  =tempfile.mkdtemp()

										lowerCamelCase__			:  Any  =PixaStructImageProcessor()
										lowerCamelCase__			:  int  =TaTokenizer.from_pretrained('t5-small' )

										lowerCamelCase__			:  List[Any]  =PixaStructProcessor(lowerCamelCase_  ,							lowerCamelCase_ )

										processor.save_pretrained(self.tmpdirname )





							def    UpperCAmelCase__							(						self						:List[str]  ,							**lowerCamelCase_						:List[str] ):





										"""simple docstring"""

										return AutoProcessor.from_pretrained(self.tmpdirname  ,							**lowerCamelCase_ ).tokenizer





							def    UpperCAmelCase__							(						self						:Tuple  ,							**lowerCamelCase_						:int ):





										"""simple docstring"""

										return AutoProcessor.from_pretrained(self.tmpdirname  ,							**lowerCamelCase_ ).image_processor





							def    UpperCAmelCase__							(						self						:Optional[int] ):





										"""simple docstring"""

										shutil.rmtree(self.tmpdirname )





							def    UpperCAmelCase__							(						self						:Dict ):





										"""simple docstring"""

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

										lowerCamelCase__			:  Optional[Any]  =[Image.fromarray(np.moveaxis(lowerCamelCase_  ,							0  ,							-1 ) ) for x in image_inputs]

										return image_inputs





							def    UpperCAmelCase__							(						self						:Optional[Any] ):





										"""simple docstring"""

										lowerCamelCase__			:  Dict  =PixaStructProcessor(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__			:  Any  =self.get_image_processor(do_normalize=lowerCamelCase_  ,							padding_value=1.0 )

										lowerCamelCase__			:  Tuple  =PixaStructProcessor.from_pretrained(
										    self.tmpdirname  ,							bos_token='(BOS)'  ,							eos_token='(EOS)'  ,							do_normalize=lowerCamelCase_  ,							padding_value=1.0 )

										self.assertEqual(processor.tokenizer.get_vocab()  ,							tokenizer_add_kwargs.get_vocab() )
										self.assertIsInstance(processor.tokenizer  ,							lowerCamelCase_ )

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





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





										"""simple docstring"""

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

										lowerCamelCase__			:  Optional[Any]  =PixaStructProcessor(tokenizer=lowerCamelCase_  ,							image_processor=lowerCamelCase_ )

										lowerCamelCase__			:  Dict  =self.prepare_image_inputs()

										lowerCamelCase__			:  Optional[int]  =image_processor(lowerCamelCase_  ,							return_tensors='np' )
										lowerCamelCase__			:  Optional[int]  =processor(images=lowerCamelCase_  ,							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    UpperCAmelCase__							(						self						:Any ):





										"""simple docstring"""

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

										lowerCamelCase__			:  List[Any]  =PixaStructProcessor(tokenizer=lowerCamelCase_  ,							image_processor=lowerCamelCase_ )

										lowerCamelCase__			:  Optional[int]  ='lower newer'

										lowerCamelCase__			:  int  =processor(text=lowerCamelCase_ )

										lowerCamelCase__			:  Tuple  =tokenizer(lowerCamelCase_  ,							return_token_type_ids=lowerCamelCase_  ,							add_special_tokens=lowerCamelCase_ )

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





							def    UpperCAmelCase__							(						self						:Optional[int] ):





										"""simple docstring"""

										lowerCamelCase__			:  Tuple  =self.get_image_processor()
										lowerCamelCase__			:  Dict  =self.get_tokenizer()

										lowerCamelCase__			:  List[Any]  =PixaStructProcessor(tokenizer=lowerCamelCase_  ,							image_processor=lowerCamelCase_ )

										lowerCamelCase__			:  Optional[int]  ='lower newer'
										lowerCamelCase__			:  Union[str, Any]  =self.prepare_image_inputs()

										lowerCamelCase__			:  str  =processor(text=lowerCamelCase_  ,							images=lowerCamelCase_ )

										self.assertListEqual(
										    list(inputs.keys() )  ,							['flattened_patches', 'attention_mask', 'decoder_attention_mask', 'decoder_input_ids'] )

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





							def    UpperCAmelCase__							(						self						:Optional[Any] ):





										"""simple docstring"""

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

										lowerCamelCase__			:  Optional[int]  =PixaStructProcessor(tokenizer=lowerCamelCase_  ,							image_processor=lowerCamelCase_ )

										lowerCamelCase__			:  Dict  ='lower newer'
										lowerCamelCase__			:  Optional[Any]  =self.prepare_image_inputs()

										lowerCamelCase__			:  Dict  =processor(text=lowerCamelCase_  ,							images=lowerCamelCase_ )

										lowerCamelCase__			:  Optional[Any]  =[512, 1_024, 2_048, 4_096]
										lowerCamelCase__			:  Any  =[770, 770, 770, 770]
										# with text
										for i, max_patch in enumerate(lowerCamelCase_ ):
													lowerCamelCase__			:  Dict  =processor(text=lowerCamelCase_  ,							images=lowerCamelCase_  ,							max_patches=lowerCamelCase_ )
													self.assertEqual(inputs['flattened_patches'][0].shape[0]  ,							lowerCamelCase_ )
													self.assertEqual(inputs['flattened_patches'][0].shape[1]  ,							expected_hidden_size[i] )

										# without text input
										for i, max_patch in enumerate(lowerCamelCase_ ):
													lowerCamelCase__			:  Union[str, Any]  =processor(images=lowerCamelCase_  ,							max_patches=lowerCamelCase_ )
													self.assertEqual(inputs['flattened_patches'][0].shape[0]  ,							lowerCamelCase_ )
													self.assertEqual(inputs['flattened_patches'][0].shape[1]  ,							expected_hidden_size[i] )





							def    UpperCAmelCase__							(						self						:Optional[int] ):





										"""simple docstring"""

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

										lowerCamelCase__			:  Tuple  =PixaStructProcessor(tokenizer=lowerCamelCase_  ,							image_processor=lowerCamelCase_ )

										lowerCamelCase__			:  List[str]  =[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

										lowerCamelCase__			:  Dict  =processor.batch_decode(lowerCamelCase_ )
										lowerCamelCase__			:  List[Any]  =tokenizer.batch_decode(lowerCamelCase_ )

										self.assertListEqual(lowerCamelCase_  ,							lowerCamelCase_ )





							def    UpperCAmelCase__							(						self						:List[Any] ):





										"""simple docstring"""

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

										lowerCamelCase__			:  List[Any]  =PixaStructProcessor(tokenizer=lowerCamelCase_  ,							image_processor=lowerCamelCase_ )

										lowerCamelCase__			:  Optional[int]  ='lower newer'
										lowerCamelCase__			:  Union[str, Any]  =self.prepare_image_inputs()

										lowerCamelCase__			:  Union[str, Any]  =processor(text=lowerCamelCase_  ,							images=lowerCamelCase_ )

										# For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
										self.assertListEqual(
										    list(inputs.keys() )  ,							['flattened_patches', 'attention_mask', 'decoder_attention_mask', 'decoder_input_ids'] )

										lowerCamelCase__			:  int  =processor(text=lowerCamelCase_ )

										# For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
										self.assertListEqual(list(inputs.keys() )  ,							['input_ids', 'attention_mask'] )

"""simple docstring"""


import unittest
import warnings

from datasets.utils import experimental






@experimental
def      lowerCAmelCase_     (	)     ->Optional[Any]:
			return "success"

class 					A_			(  unittest.TestCase     ):



							"""simple docstring"""






							def    UpperCAmelCase__							(						self						:int ):





										"""simple docstring"""

										with warnings.catch_warnings(record=lowerCamelCase_ ) as w:
													warnings.simplefilter('always' )
													self.assertEqual(dummy_function()  ,							'success' )
										self.assertEqual(len(lowerCamelCase_ )  ,							1 )