
"""simple docstring"""




import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
						from PIL import Image

						from transformers import (
						    AutoProcessor,
						    BertTokenizerFast,
						    BlipImageProcessor,
						    GPTaTokenizer,
						    InstructBlipProcessor,
						    PreTrainedTokenizerFast,
						)





@require_vision
class  snake_case     (							unittest.TestCase   ):

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = tempfile.mkdtemp()

									SCREAMING_SNAKE_CASE_						 = BlipImageProcessor()
									SCREAMING_SNAKE_CASE_						 = GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''    )
									SCREAMING_SNAKE_CASE_						 = BertTokenizerFast.from_pretrained('''hf-internal-testing/tiny-random-bert'''    )

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									processor.save_pretrained(self.tmpdirname    )

							def _lowercase					(self       ,       **SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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

							def _lowercase					(self       ,       **SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







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

							def _lowercase					(self       ,       **SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									return AutoProcessor.from_pretrained(self.tmpdirname       ,       **SCREAMING_SNAKE_CASE_    ).qformer_tokenizer

							def _lowercase					(self    ):

									"""simple docstring"""







									shutil.rmtree(self.tmpdirname    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = [np.random.randint(2_55       ,       size=(3, 30, 4_00)       ,       dtype=np.uinta    )]

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

									return image_inputs

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(
									    tokenizer=self.get_tokenizer()       ,       image_processor=self.get_image_processor()       ,       qformer_tokenizer=self.get_qformer_tokenizer()       ,       )
									processor.save_pretrained(self.tmpdirname    )

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

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor.from_pretrained(
									    self.tmpdirname       ,       bos_token='''(BOS)'''       ,       eos_token='''(EOS)'''       ,       do_normalize=SCREAMING_SNAKE_CASE_       ,       padding_value=1.0    )

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

									self.assertEqual(processor.image_processor.to_json_string()       ,       image_processor_add_kwargs.to_json_string()    )
									self.assertIsInstance(processor.image_processor       ,       SCREAMING_SNAKE_CASE_    )
									self.assertIsInstance(processor.qformer_tokenizer       ,       SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.get_image_processor()
									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_qformer_tokenizer()

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(
									    tokenizer=SCREAMING_SNAKE_CASE_       ,       image_processor=SCREAMING_SNAKE_CASE_       ,       qformer_tokenizer=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE_						 = image_processor(SCREAMING_SNAKE_CASE_       ,       return_tensors='''np'''    )
									SCREAMING_SNAKE_CASE_						 = processor(images=SCREAMING_SNAKE_CASE_       ,       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"""







									SCREAMING_SNAKE_CASE_						 = self.get_image_processor()
									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_qformer_tokenizer()

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(
									    tokenizer=SCREAMING_SNAKE_CASE_       ,       image_processor=SCREAMING_SNAKE_CASE_       ,       qformer_tokenizer=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = '''lower newer'''

									SCREAMING_SNAKE_CASE_						 = processor(text=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = tokenizer(SCREAMING_SNAKE_CASE_       ,       return_token_type_ids=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = qformer_tokenizer(SCREAMING_SNAKE_CASE_       ,       return_token_type_ids=SCREAMING_SNAKE_CASE_    )

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

									for key in encoded_tokens_qformer.keys():
											self.assertListEqual(encoded_tokens_qformer[key]       ,       encoded_processor['''qformer_''' + key]    )

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.get_image_processor()
									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_qformer_tokenizer()

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(
									    tokenizer=SCREAMING_SNAKE_CASE_       ,       image_processor=SCREAMING_SNAKE_CASE_       ,       qformer_tokenizer=SCREAMING_SNAKE_CASE_    )

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

									SCREAMING_SNAKE_CASE_						 = processor(text=SCREAMING_SNAKE_CASE_       ,       images=SCREAMING_SNAKE_CASE_    )

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

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

							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.get_image_processor()
									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_qformer_tokenizer()

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(
									    tokenizer=SCREAMING_SNAKE_CASE_       ,       image_processor=SCREAMING_SNAKE_CASE_       ,       qformer_tokenizer=SCREAMING_SNAKE_CASE_    )

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

									SCREAMING_SNAKE_CASE_						 = processor.batch_decode(SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = tokenizer.batch_decode(SCREAMING_SNAKE_CASE_    )

									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )







							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = self.get_image_processor()
									SCREAMING_SNAKE_CASE_						 = self.get_tokenizer()
									SCREAMING_SNAKE_CASE_						 = self.get_qformer_tokenizer()

									SCREAMING_SNAKE_CASE_						 = InstructBlipProcessor(
									    tokenizer=SCREAMING_SNAKE_CASE_       ,       image_processor=SCREAMING_SNAKE_CASE_       ,       qformer_tokenizer=SCREAMING_SNAKE_CASE_    )

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

									SCREAMING_SNAKE_CASE_						 = processor(text=SCREAMING_SNAKE_CASE_       ,       images=SCREAMING_SNAKE_CASE_    )

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

"""simple docstring"""




import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin





class  snake_case     (							__lowercase       ,			unittest.TestCase   ):
							UpperCAmelCase__						     =      CTRLTokenizer
							UpperCAmelCase__						     =      False
							UpperCAmelCase__						     =      False

							def _lowercase					(self    ):

									"""simple docstring"""







									super().setUp()

									# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
									SCREAMING_SNAKE_CASE_						 = ['''adapt''', '''re@@''', '''a@@''', '''apt''', '''c@@''', '''t''', '''<unk>''']
									SCREAMING_SNAKE_CASE_						 = dict(zip(SCREAMING_SNAKE_CASE_       ,       range(len(SCREAMING_SNAKE_CASE_    )    )    )    )
									SCREAMING_SNAKE_CASE_						 = ['''#version: 0.2''', '''a p''', '''ap t</w>''', '''r e''', '''a d''', '''ad apt</w>''', '''''']
									SCREAMING_SNAKE_CASE_						 = {'''unk_token''': '''<unk>'''}

									SCREAMING_SNAKE_CASE_						 = os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''vocab_file''']    )
									SCREAMING_SNAKE_CASE_						 = os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''merges_file''']    )
									with open(self.vocab_file       ,       '''w'''       ,       encoding='''utf-8'''    ) as fp:
											fp.write(json.dumps(SCREAMING_SNAKE_CASE_    ) + '''\n'''    )
									with open(self.merges_file       ,       '''w'''       ,       encoding='''utf-8'''    ) as fp:
											fp.write('''\n'''.join(SCREAMING_SNAKE_CASE_    )    )

							def _lowercase					(self       ,       **SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									kwargs.update(self.special_tokens_map    )
									return CTRLTokenizer.from_pretrained(self.tmpdirname       ,       **SCREAMING_SNAKE_CASE_    )

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = '''adapt react readapt apt'''
									SCREAMING_SNAKE_CASE_						 = '''adapt react readapt apt'''
									return input_text, output_text







							def _lowercase					(self    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = CTRLTokenizer(self.vocab_file       ,       self.merges_file       ,       **self.special_tokens_map    )
									SCREAMING_SNAKE_CASE_						 = '''adapt react readapt apt'''
									SCREAMING_SNAKE_CASE_						 = '''adapt re@@ a@@ c@@ t re@@ adapt apt'''.split()
									SCREAMING_SNAKE_CASE_						 = tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
									self.assertListEqual(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = tokens + [tokenizer.unk_token]

									SCREAMING_SNAKE_CASE_						 = [0, 1, 2, 4, 5, 1, 0, 3, 6]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_    )       ,       SCREAMING_SNAKE_CASE_    )