






import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
		from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
		__magic_name__:					Any							=     get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
		from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__magic_name__:					Tuple							=     128_022
__magic_name__:					Any							=     128_028





@require_sentencepiece
class 	snake_case__ (							_lowerCAmelCase						,  unittest.TestCase				):
	lowercase__						:					Tuple											=   MaMaaaTokenizer
	lowercase__						:					Any											=   False
	lowercase__						:					Optional[Any]											=   False
	lowercase__						:					Dict											=   True
	def       __magic_name__    (    self			)							->				Dict:
							super().setUp()

							__magic_name__      :       Any       						= ["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
							__magic_name__      :       int       						= dict(zip(lowerCAmelCase__      ,       range(len(lowerCAmelCase__			)			)			)			)
							__magic_name__      :       Optional[Any]       						= Path(self.tmpdirname			)
							save_json(lowerCAmelCase__      ,       save_dir / VOCAB_FILES_NAMES["""vocab_file"""]			)
							if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
													copyfile(lowerCAmelCase__      ,       save_dir / VOCAB_FILES_NAMES["""spm_file"""]			)

							__magic_name__      :       int       						= MaMaaaTokenizer.from_pretrained(self.tmpdirname			)
							tokenizer.save_pretrained(self.tmpdirname			)
	def       __magic_name__    (    self      ,       **lowerCAmelCase__			)							->				Any:
							return MaMaaaTokenizer.from_pretrained(self.tmpdirname      ,       **lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       lowerCAmelCase__			)							->				Dict:
							return (
							    "This is a test",
							    "This is a test",
							)
	def       __magic_name__    (    self			)							->				Dict:
							__magic_name__      :       int       						= """</s>"""
							__magic_name__      :       Union[str, Any]       						= 0

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase__			)      ,       lowerCAmelCase__			)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase__			)      ,       lowerCAmelCase__			)
	def       __magic_name__    (    self			)							->				List[Any]:
							__magic_name__      :       Dict       						= self.get_tokenizer()
							__magic_name__      :       str       						= list(tokenizer.get_vocab().keys()			)

							self.assertEqual(vocab_keys[0]      ,       """</s>"""			)
							self.assertEqual(vocab_keys[1]      ,       """<unk>"""			)
							self.assertEqual(vocab_keys[-1]      ,       """<s>"""			)
							self.assertEqual(len(lowerCAmelCase__			)      ,       tokenizer.vocab_size + len(tokenizer.get_added_vocab()			)			)
	@unittest.skip("""Skip this test while all models are still to be uploaded."""			)
	def       __magic_name__    (    self			)							->				List[str]:
							pass
	def       __magic_name__    (    self			)							->				List[Any]:
							__magic_name__      :       Optional[Any]       						= self.get_tokenizer()

							__magic_name__      :       Optional[int]       						= tokenizer.tokenize("""This is a test"""			)
							self.assertListEqual(lowerCAmelCase__      ,       ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]			)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(lowerCAmelCase__			)      ,       [2, 3, 4, 5, 6]      ,       )

							__magic_name__      :       Optional[int]       						= tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]			)
							self.assertListEqual(lowerCAmelCase__      ,       ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]			)

							__magic_name__      :       Optional[int]       						= tokenizer.convert_tokens_to_string(lowerCAmelCase__			)
							self.assertEqual(lowerCAmelCase__      ,       """This is a test"""			)







	@slow
	def       __magic_name__    (    self			)							->				Dict:
							# fmt: off
							__magic_name__      :       Any       						= {"""input_ids""": [[12_80_22, 11_01_08, 3_97, 11, 3_82_72, 22_47, 12_48_11, 2_85, 1_81_05, 15_86, 2_07, 7, 3_95_34, 44_28, 3_97, 10_19, 1_81_05, 15_86, 2_07, 7, 4_13_37, 1_67_86, 2_41, 7, 2_02_14, 17, 12_56_90, 1_03_98, 7, 4_43_78, 5_80_69, 6_83_42, 77_98, 73_43, 11, 2_99, 3_33_10, 4, 1_58, 3_73_50, 9_40_77, 45_69, 2_99, 3_33_10, 90, 4, 5_28_40, 2_90, 4, 3_12_70, 1_12, 2_99, 6_82, 4, 5_28_40, 3_99_53, 1_40_79, 1_93, 5_25_19, 9_08_94, 1_78_94, 12_06_97, 11, 4_04_45, 5_51, 17, 10_19, 5_25_19, 9_08_94, 1_77_56, 9_63, 11, 4_04_45, 4_80, 17, 97_92, 11_20, 51_73, 13_93, 62_40, 1_67_86, 2_41, 12_09_96, 28, 12_45, 13_93, 11_82_40, 1_11_23, 10_19, 9_36_12, 26_91, 1_06_18, 9_80_58, 12_04_09, 19_28, 2_79, 4, 4_06_83, 3_67, 1_78, 2_07, 10_19, 1_03, 10_31_21, 5_06, 6_52_96, 5, 2], [12_80_22, 2_12_17, 3_67, 1_17, 12_54_50, 1_28, 7_19, 7, 73_08, 40, 9_36_12, 1_26_69, 11_16, 1_67_04, 71, 1_77_85, 36_99, 1_55_92, 35, 1_44, 95_84, 2_41, 1_19_43, 7_13, 9_50, 7_99, 22_47, 8_84_27, 1_50, 1_49, 11_88_13, 12_07_06, 10_19, 10_69_06, 8_15_18, 28, 12_24, 2_27_99, 3_97, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [12_80_22, 16_58, 12_33_11, 51_55, 55_78, 47_22, 2_79, 1_49_47, 23_66, 11_20, 11_97, 14, 13_48, 92_32, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=lowerCAmelCase__      ,       model_name="""facebook/m2m100_418M"""      ,       revision="""c168bae485c864188cf9aa0e4108b0b6934dc91e"""      ,       )





@require_torch
@require_sentencepiece
@require_tokenizers
class 	snake_case__ (							unittest.TestCase				):
	lowercase__						:					Dict											=   '''facebook/m2m100_418M'''
	lowercase__						:					Optional[int]											=   [
	    '''In my opinion, there are two levels of response from the French government.''',
	    '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
	]
	lowercase__						:					Dict											=   [
	    '''Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.''',
	    '''L\'affaire NSA souligne l\'absence totale de débat sur le renseignement''',
	]

	# fmt: off
	lowercase__						:					Optional[int]											=   [EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]
	@classmethod
	def       __magic_name__    (    cls			)							->				Union[str, Any]:
							__magic_name__      :       MaMaaaTokenizer       						= MaMaaaTokenizer.from_pretrained(
							    cls.checkpoint_name      ,       src_lang="""en"""      ,       tgt_lang="""fr"""			)
							__magic_name__      :       Optional[int]       						= 1
							return cls
	def       __magic_name__    (    self			)							->				List[str]:
							self.assertEqual(self.tokenizer.get_lang_id("""ar"""			)      ,       12_80_06			)
							self.assertEqual(self.tokenizer.get_lang_id("""en"""			)      ,       12_80_22			)
							self.assertEqual(self.tokenizer.get_lang_id("""ro"""			)      ,       12_80_76			)
							self.assertEqual(self.tokenizer.get_lang_id("""mr"""			)      ,       12_80_63			)
	def       __magic_name__    (    self			)							->				List[Any]:
							__magic_name__      :       str       						= self.tokenizer.get_vocab()
							self.assertEqual(len(lowerCAmelCase__			)      ,       self.tokenizer.vocab_size			)
							self.assertEqual(vocab["""<unk>"""]      ,       3			)
							self.assertIn(self.tokenizer.get_lang_token("""en"""			)      ,       lowerCAmelCase__			)
	def       __magic_name__    (    self			)							->				List[str]:
							__magic_name__      :       Tuple       						= """en"""
							__magic_name__      :       List[str]       						= self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
							self.assertListEqual(self.expected_src_tokens      ,       lowerCAmelCase__			)
	def       __magic_name__    (    self			)							->				Tuple:
							self.assertIn(lowerCAmelCase__      ,       self.tokenizer.all_special_ids			)
							# fmt: off
							__magic_name__      :       Tuple       						= [FR_CODE, 53_64, 82, 86_42, 4, 2_94, 47, 8, 1_40_28, 1_36, 32_86, 97_06, 6, 9_07_97, 6, 14_40_12, 1_62, 8_81_28, 3_00_61, 5, 2]
							# fmt: on
							__magic_name__      :       Tuple       						= self.tokenizer.decode(lowerCAmelCase__      ,       skip_special_tokens=lowerCAmelCase__			)
							__magic_name__      :       str       						= self.tokenizer.decode(generated_ids[1:]      ,       skip_special_tokens=lowerCAmelCase__			)
							self.assertEqual(lowerCAmelCase__      ,       lowerCAmelCase__			)
							self.assertNotIn(self.tokenizer.eos_token      ,       lowerCAmelCase__			)
	def       __magic_name__    (    self			)							->				Dict:
							__magic_name__      :       List[Any]       						= tempfile.mkdtemp()
							__magic_name__      :       List[Any]       						= self.tokenizer.lang_token_to_id
							self.tokenizer.save_pretrained(lowerCAmelCase__			)
							__magic_name__      :       List[str]       						= MaMaaaTokenizer.from_pretrained(lowerCAmelCase__			)
							self.assertDictEqual(new_tok.lang_token_to_id      ,       lowerCAmelCase__			)
	@require_torch
	def       __magic_name__    (    self			)							->				Any:
							__magic_name__      :       Optional[int]       						= """en"""
							__magic_name__      :       int       						= """fr"""

							__magic_name__      :       List[Any]       						= self.tokenizer(self.src_text      ,       text_target=self.tgt_text      ,       padding=lowerCAmelCase__      ,       return_tensors="""pt"""			)

							__magic_name__      :       Dict       						= shift_tokens_right(
							    batch["""labels"""]      ,       self.tokenizer.pad_token_id      ,       self.tokenizer.eos_token_id			)

							for k in batch:
													__magic_name__      :       Dict       						= batch[k].tolist()
							# batch = {k: v.tolist() for k,v in batch.items()}
							# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
							# batch.decoder_inputs_ids[0][0] ==
							assert batch.input_ids[1][0] == EN_CODE
							assert batch.input_ids[1][-1] == 2
							assert batch.labels[1][0] == FR_CODE
							assert batch.labels[1][-1] == 2
							assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]
	@require_torch
	def       __magic_name__    (    self			)							->				Union[str, Any]:
							__magic_name__      :       List[Any]       						= """mr"""
							self.assertListEqual(self.tokenizer.prefix_tokens      ,       [self.tokenizer.get_lang_id("""mr"""			)]			)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,       [self.tokenizer.eos_token_id]			)

							__magic_name__      :       List[Any]       						= """zh"""
							self.assertListEqual(self.tokenizer.prefix_tokens      ,       [self.tokenizer.get_lang_id("""zh"""			)]			)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,       [self.tokenizer.eos_token_id]			)
	@require_torch
	def       __magic_name__    (    self			)							->				Any:
							__magic_name__      :       Any       						= """mr"""
							self.tokenizer._switch_to_target_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,       [self.tokenizer.get_lang_id("""mr"""			)]			)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,       [self.tokenizer.eos_token_id]			)
							self.tokenizer._switch_to_input_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,       [self.tokenizer.get_lang_id(self.tokenizer.src_lang			)]			)

							__magic_name__      :       Optional[Any]       						= """zh"""
							self.tokenizer._switch_to_target_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,       [self.tokenizer.get_lang_id("""zh"""			)]			)
							self.assertListEqual(self.tokenizer.suffix_tokens      ,       [self.tokenizer.eos_token_id]			)
							self.tokenizer._switch_to_input_mode()
							self.assertListEqual(self.tokenizer.prefix_tokens      ,       [self.tokenizer.get_lang_id(self.tokenizer.src_lang			)]			)







	@require_torch
	def       __magic_name__    (    self			)							->				Any:
							__magic_name__      :       Any       						= self.tokenizer._build_translation_inputs("""A test"""      ,       return_tensors="""pt"""      ,       src_lang="""en"""      ,       tgt_lang="""ar"""			)

							self.assertEqual(
							    nested_simplify(lowerCAmelCase__			)      ,       {
							        # en_XX, A, test, EOS
							        """input_ids""": [[12_80_22, 58, 41_83, 2]],
							        """attention_mask""": [[1, 1, 1, 1]],
							        # ar_AR
							        """forced_bos_token_id""": 12_80_06,
							    }      ,       )








import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip 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 OwlViTImageProcessor, OwlViTProcessor





@require_vision
class 	snake_case__ (							unittest.TestCase				):
	def       __magic_name__    (    self			)							->				int:
							__magic_name__      :       List[str]       						= tempfile.mkdtemp()

							# fmt: off
							__magic_name__      :       Union[str, Any]       						= ["""""", """l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
							# fmt: on
							__magic_name__      :       Any       						= dict(zip(lowerCAmelCase__      ,       range(len(lowerCAmelCase__			)			)			)			)
							__magic_name__      :       int       						= ["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
							__magic_name__      :       Any       						= {"""unk_token""": """<unk>"""}

							__magic_name__      :       Optional[Any]       						= os.path.join(self.tmpdirname      ,       VOCAB_FILES_NAMES["""vocab_file"""]			)
							__magic_name__      :       Optional[int]       						= 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(lowerCAmelCase__			) + """\n"""			)
							with open(self.merges_file      ,       """w"""      ,       encoding="""utf-8"""			) as fp:
													fp.write("""\n""".join(lowerCAmelCase__			)			)

							__magic_name__      :       int       						= {
							    """do_resize""": True,
							    """size""": 20,
							    """do_center_crop""": True,
							    """crop_size""": 18,
							    """do_normalize""": True,
							    """image_mean""": [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
							    """image_std""": [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
							}
							__magic_name__      :       List[str]       						= os.path.join(self.tmpdirname      ,       lowerCAmelCase__			)
							with open(self.image_processor_file      ,       """w"""      ,       encoding="""utf-8"""			) as fp:
													json.dump(lowerCAmelCase__      ,       lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       **lowerCAmelCase__			)							->				List[str]:
							return CLIPTokenizer.from_pretrained(self.tmpdirname      ,       pad_token="""!"""      ,       **lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       **lowerCAmelCase__			)							->				Any:
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname      ,       pad_token="""!"""      ,       **lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       **lowerCAmelCase__			)							->				Optional[Any]:
							return OwlViTImageProcessor.from_pretrained(self.tmpdirname      ,       **lowerCAmelCase__			)
	def       __magic_name__    (    self			)							->				int:
							shutil.rmtree(self.tmpdirname			)
	def       __magic_name__    (    self			)							->				int:
							__magic_name__      :       str       						= [np.random.randint(2_55      ,       size=(3, 30, 4_00)      ,       dtype=np.uinta			)]

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

							return image_inputs
	def       __magic_name__    (    self			)							->				Union[str, Any]:
							__magic_name__      :       Any       						= self.get_tokenizer()
							__magic_name__      :       str       						= self.get_rust_tokenizer()
							__magic_name__      :       Tuple       						= self.get_image_processor()

							__magic_name__      :       List[str]       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)
							processor_slow.save_pretrained(self.tmpdirname			)
							__magic_name__      :       Optional[int]       						= OwlViTProcessor.from_pretrained(self.tmpdirname      ,       use_fast=lowerCAmelCase__			)

							__magic_name__      :       int       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)
							processor_fast.save_pretrained(self.tmpdirname			)
							__magic_name__      :       List[Any]       						= OwlViTProcessor.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      ,       lowerCAmelCase__			)
							self.assertIsInstance(processor_fast.tokenizer      ,       lowerCAmelCase__			)

							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      ,       lowerCAmelCase__			)
							self.assertIsInstance(processor_fast.image_processor      ,       lowerCAmelCase__			)
	def       __magic_name__    (    self			)							->				Optional[int]:
							__magic_name__      :       Optional[Any]       						= OwlViTProcessor(tokenizer=self.get_tokenizer()      ,       image_processor=self.get_image_processor()			)
							processor.save_pretrained(self.tmpdirname			)

							__magic_name__      :       str       						= self.get_tokenizer(bos_token="""(BOS)"""      ,       eos_token="""(EOS)"""			)
							__magic_name__      :       Any       						= self.get_image_processor(do_normalize=lowerCAmelCase__			)

							__magic_name__      :       Tuple       						= OwlViTProcessor.from_pretrained(
							    self.tmpdirname      ,       bos_token="""(BOS)"""      ,       eos_token="""(EOS)"""      ,       do_normalize=lowerCAmelCase__			)

							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       __magic_name__    (    self			)							->				Dict:
							__magic_name__      :       int       						= self.get_image_processor()
							__magic_name__      :       int       						= self.get_tokenizer()

							__magic_name__      :       Union[str, Any]       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)

							__magic_name__      :       Dict       						= self.prepare_image_inputs()

							__magic_name__      :       Any       						= image_processor(lowerCAmelCase__      ,       return_tensors="""np"""			)
							__magic_name__      :       str       						= processor(images=lowerCAmelCase__      ,       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       __magic_name__    (    self			)							->				Tuple:
							__magic_name__      :       Union[str, Any]       						= self.get_image_processor()
							__magic_name__      :       int       						= self.get_tokenizer()

							__magic_name__      :       int       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)

							__magic_name__      :       Optional[int]       						= """lower newer"""

							__magic_name__      :       Tuple       						= processor(text=lowerCAmelCase__      ,       return_tensors="""np"""			)

							__magic_name__      :       Optional[int]       						= tokenizer(lowerCAmelCase__      ,       return_tensors="""np"""			)

							for key in encoded_tok.keys():
													self.assertListEqual(encoded_tok[key][0].tolist()      ,       encoded_processor[key][0].tolist()			)
	def       __magic_name__    (    self			)							->				Tuple:
							__magic_name__      :       Tuple       						= self.get_image_processor()
							__magic_name__      :       Union[str, Any]       						= self.get_tokenizer()

							__magic_name__      :       List[str]       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)

							__magic_name__      :       Any       						= """lower newer"""
							__magic_name__      :       Union[str, Any]       						= self.prepare_image_inputs()

							__magic_name__      :       int       						= processor(text=lowerCAmelCase__      ,       images=lowerCAmelCase__			)

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

							# test if it raises when no input is passed
							with pytest.raises(lowerCAmelCase__			):
													processor()
	def       __magic_name__    (    self			)							->				Optional[Any]:
							__magic_name__      :       Dict       						= """google/owlvit-base-patch32"""
							__magic_name__      :       int       						= OwlViTProcessor.from_pretrained(lowerCAmelCase__			)

							__magic_name__      :       List[Any]       						= ["""cat""", """nasa badge"""]
							__magic_name__      :       Any       						= processor(text=lowerCAmelCase__			)

							__magic_name__      :       Dict       						= 16
							self.assertListEqual(list(inputs.keys()			)      ,       ["""input_ids""", """attention_mask"""]			)
							self.assertEqual(inputs["""input_ids"""].shape      ,       (2, seq_length)			)

							# test if it raises when no input is passed
							with pytest.raises(lowerCAmelCase__			):
													processor()
	def       __magic_name__    (    self			)							->				List[Any]:
							__magic_name__      :       List[str]       						= """google/owlvit-base-patch32"""
							__magic_name__      :       Optional[Any]       						= OwlViTProcessor.from_pretrained(lowerCAmelCase__			)

							__magic_name__      :       Tuple       						= [["""cat""", """nasa badge"""], ["""person"""]]
							__magic_name__      :       Tuple       						= processor(text=lowerCAmelCase__			)

							__magic_name__      :       str       						= 16
							__magic_name__      :       str       						= len(lowerCAmelCase__			)
							__magic_name__      :       int       						= max([len(lowerCAmelCase__			) for texts in input_texts]			)

							self.assertListEqual(list(inputs.keys()			)      ,       ["""input_ids""", """attention_mask"""]			)
							self.assertEqual(inputs["""input_ids"""].shape      ,       (batch_size * num_max_text_queries, seq_length)			)

							# test if it raises when no input is passed
							with pytest.raises(lowerCAmelCase__			):
													processor()
	def       __magic_name__    (    self			)							->				Any:
							__magic_name__      :       Optional[int]       						= """google/owlvit-base-patch32"""
							__magic_name__      :       Any       						= OwlViTProcessor.from_pretrained(lowerCAmelCase__			)

							__magic_name__      :       str       						= ["""cat""", """nasa badge"""]
							__magic_name__      :       List[str]       						= processor(text=lowerCAmelCase__			)

							__magic_name__      :       List[Any]       						= 16
							__magic_name__      :       Any       						= inputs["""input_ids"""]
							__magic_name__      :       Optional[Any]       						= [
							    [4_94_06, 23_68, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
							    [4_94_06, 68_41, 1_13_01, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
							]

							self.assertListEqual(list(inputs.keys()			)      ,       ["""input_ids""", """attention_mask"""]			)
							self.assertEqual(inputs["""input_ids"""].shape      ,       (2, seq_length)			)
							self.assertListEqual(list(input_ids[0]			)      ,       predicted_ids[0]			)
							self.assertListEqual(list(input_ids[1]			)      ,       predicted_ids[1]			)
	def       __magic_name__    (    self			)							->				Tuple:
							__magic_name__      :       List[str]       						= self.get_image_processor()
							__magic_name__      :       Dict       						= self.get_tokenizer()

							__magic_name__      :       Tuple       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)

							__magic_name__      :       Tuple       						= self.prepare_image_inputs()
							__magic_name__      :       List[Any]       						= self.prepare_image_inputs()

							__magic_name__      :       List[str]       						= processor(images=lowerCAmelCase__      ,       query_images=lowerCAmelCase__			)

							self.assertListEqual(list(inputs.keys()			)      ,       ["""query_pixel_values""", """pixel_values"""]			)

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







	def       __magic_name__    (    self			)							->				Any:
							__magic_name__      :       Optional[Any]       						= self.get_image_processor()
							__magic_name__      :       List[Any]       						= self.get_tokenizer()

							__magic_name__      :       Tuple       						= OwlViTProcessor(tokenizer=lowerCAmelCase__      ,       image_processor=lowerCAmelCase__			)

							__magic_name__      :       Union[str, Any]       						= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							__magic_name__      :       Optional[Any]       						= processor.batch_decode(lowerCAmelCase__			)
							__magic_name__      :       Optional[int]       						= tokenizer.batch_decode(lowerCAmelCase__			)

							self.assertListEqual(lowerCAmelCase__      ,       lowerCAmelCase__			)
