




'''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:
     a_   :	str							   = 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 						__UpperCamelCase (				unittest.TestCase       ):






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=tempfile.mkdtemp()

              lowerCamelCase_							=PixaStructImageProcessor()
              lowerCamelCase_							=TaTokenizer.from_pretrained('''t5-small'''						)

              lowerCamelCase_							=PixaStructProcessor(lowerCAmelCase,	lowerCAmelCase						)

              processor.save_pretrained(self.tmpdirname						)






       def   lowercase__  (							self,	**lowerCAmelCase						):



              """simple docstring"""







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






       def   lowercase__  (							self,	**lowerCAmelCase						):



              """simple docstring"""







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






       def   lowercase__  (							self						):



              """simple docstring"""







              shutil.rmtree(self.tmpdirname						)






       def   lowercase__  (							self						):



              """simple docstring"""







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

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

              return image_inputs






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=PixaStructProcessor(tokenizer=self.get_tokenizer(),	image_processor=self.get_image_processor()						)
              processor.save_pretrained(self.tmpdirname						)

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

              lowerCamelCase_							=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   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_image_processor()
              lowerCamelCase_							=self.get_tokenizer()

              lowerCamelCase_							=PixaStructProcessor(tokenizer=lowerCAmelCase,	image_processor=lowerCAmelCase						)

              lowerCamelCase_							=self.prepare_image_inputs()

              lowerCamelCase_							=image_processor(lowerCAmelCase,	return_tensors='''np'''						)
              lowerCamelCase_							=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   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_image_processor()
              lowerCamelCase_							=self.get_tokenizer()

              lowerCamelCase_							=PixaStructProcessor(tokenizer=lowerCAmelCase,	image_processor=lowerCAmelCase						)

              lowerCamelCase_							='''lower newer'''

              lowerCamelCase_							=processor(text=lowerCAmelCase						)

              lowerCamelCase_							=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   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_image_processor()
              lowerCamelCase_							=self.get_tokenizer()

              lowerCamelCase_							=PixaStructProcessor(tokenizer=lowerCAmelCase,	image_processor=lowerCAmelCase						)

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

              lowerCamelCase_							=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   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_image_processor()
              lowerCamelCase_							=self.get_tokenizer()

              lowerCamelCase_							=PixaStructProcessor(tokenizer=lowerCAmelCase,	image_processor=lowerCAmelCase						)

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

              lowerCamelCase_							=processor(text=lowerCAmelCase,	images=lowerCAmelCase						)

              lowerCamelCase_							=[512, 1_024, 2_048, 4_096]
              lowerCamelCase_							=[770, 770, 770, 770]
              # with text
              for i, max_patch in enumerate(lowerCAmelCase						):
                     lowerCamelCase_							=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_							=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   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_image_processor()
              lowerCamelCase_							=self.get_tokenizer()

              lowerCamelCase_							=PixaStructProcessor(tokenizer=lowerCAmelCase,	image_processor=lowerCAmelCase						)

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

              lowerCamelCase_							=processor.batch_decode(lowerCAmelCase						)
              lowerCamelCase_							=tokenizer.batch_decode(lowerCAmelCase						)

              self.assertListEqual(lowerCAmelCase,	lowerCAmelCase						)






       def   lowercase__  (							self						):



              """simple docstring"""







              lowerCamelCase_							=self.get_image_processor()
              lowerCamelCase_							=self.get_tokenizer()

              lowerCamelCase_							=PixaStructProcessor(tokenizer=lowerCAmelCase,	image_processor=lowerCAmelCase						)

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

              lowerCamelCase_							=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_							=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'''




from .hash_table import HashTable


class 						__UpperCamelCase (				lowerCamelCase__       ):






       def __init__(							self,	*lowerCAmelCase,	**lowerCAmelCase						):



              """simple docstring"""







              super().__init__(*lowerCAmelCase,	**lowerCAmelCase						)






       def   lowercase__  (							self,	lowerCAmelCase,	lowerCAmelCase=None						):



              """simple docstring"""







              lowerCamelCase_							=1
              lowerCamelCase_							=self.hash_function(key + i * i						)

              while self.values[new_key] is not None and self.values[new_key] != key:
                     i += 1
                     lowerCamelCase_							=(
                         self.hash_function(key + i * i						)
                         if not self.balanced_factor() >= self.lim_charge
                         else None
                     )

                     if new_key is None:
                            break

              return new_key




