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

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
	from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase            =		get_tests_dir("""fixtures/test_sentencepiece.model""")

_UpperCAmelCase            =		{"""target_lang""": """fi""", """source_lang""": """en"""}
_UpperCAmelCase            =		""">>zh<<"""
_UpperCAmelCase            =		"""Helsinki-NLP/"""

if is_torch_available():
	_UpperCAmelCase            =		"""pt"""
elif is_tf_available():
	_UpperCAmelCase            =		"""tf"""
else:
	_UpperCAmelCase            =		"""jax"""





@require_sentencepiece
class UpperCAmelCase						( __lowercase ,	unittest.TestCase  ):


				'''simple docstring'''






				lowerCamelCase_    = MarianTokenizer
				lowerCamelCase_    = False
				lowerCamelCase_    = True
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						super().setUp()
						A_		:    List[str]         =				['''</s>''', '''<unk>''', '''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''', '''\u0120''', '''<pad>''']
						A_		:    Optional[Any]         =				dict(zip(_a		,     range(len(_a ) ) ) )
						A_		:    Dict         =				Path(self.tmpdirname )
						save_json(_a		,     save_dir / VOCAB_FILES_NAMES['vocab'] )
						save_json(_a		,     save_dir / VOCAB_FILES_NAMES['tokenizer_config_file'] )
						if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
								copyfile(_a		,     save_dir / VOCAB_FILES_NAMES['source_spm'] )
								copyfile(_a		,     save_dir / VOCAB_FILES_NAMES['target_spm'] )

						A_		:    List[str]         =				MarianTokenizer.from_pretrained(self.tmpdirname )
						tokenizer.save_pretrained(self.tmpdirname )
				def   lowerCAmelCase_       (						self		,     **lowercase ):



						"""simple docstring"""





						return MarianTokenizer.from_pretrained(self.tmpdirname		,     **_a )
				def   lowerCAmelCase_       (						self		,     lowercase ):



						"""simple docstring"""





						return (
						    "This is a test",
						    "This is a test",
						)
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Tuple         =				'''</s>'''
						A_		:    Union[str, Any]         =				0

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(_a )		,     _a )
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(_a )		,     _a )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    str         =				list(self.get_tokenizer().get_vocab().keys() )

						self.assertEqual(vocab_keys[0]		,     '</s>' )
						self.assertEqual(vocab_keys[1]		,     '<unk>' )
						self.assertEqual(vocab_keys[-1]		,     '<pad>' )
						self.assertEqual(len(_a )		,     9 )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						self.assertEqual(self.get_tokenizer().vocab_size		,     9 )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Union[str, Any]         =				MarianTokenizer.from_pretrained(F'''{ORG_NAME}opus-mt-en-de''' )
						A_		:    List[str]         =				en_de_tokenizer(['I am a small frog']		,     return_tensors=_a )
						self.assertIsInstance(_a		,     _a )
						A_		:    str         =				[3_8, 1_2_1, 1_4, 6_9_7, 3_8_8_4_8, 0]
						self.assertListEqual(_a		,     batch.input_ids[0] )

						A_		:    Tuple         =				tempfile.mkdtemp()
						en_de_tokenizer.save_pretrained(_a )
						A_		:    Optional[Any]         =				[x.name for x in Path(_a ).glob('*' )]
						self.assertIn('source.spm'		,     _a )
						MarianTokenizer.from_pretrained(_a )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Union[str, Any]         =				self.get_tokenizer()

						A_		:    List[str]         =				tok(
						    ['I am a small frog' * 1_0_0_0, 'I am a small frog']		,     padding=_a		,     truncation=_a		,     return_tensors=_a )
						self.assertIsInstance(_a		,     _a )
						self.assertEqual(batch.input_ids.shape		,     (2, 5_1_2) )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Dict         =				self.get_tokenizer()
						A_		:    List[Any]         =				tok(['I am a tiny frog', 'I am a small frog']		,     padding=_a		,     return_tensors=_a )
						self.assertIsInstance(_a		,     _a )
						self.assertEqual(batch_smaller.input_ids.shape		,     (2, 1_0) )
				@slow
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    List[str]         =				{'''input_ids''': [[4_3_4_9_5, 4_6_2, 2_0, 4_2_1_6_4, 1_3_6_9, 5_2, 4_6_4, 1_3_2, 1_7_0_3, 4_9_2, 1_3, 7_4_9_1, 3_8_9_9_9, 6, 8, 4_6_4, 1_3_2, 1_7_0_3, 4_9_2, 1_3, 4_6_6_9, 3_7_8_6_7, 1_3, 7_5_2_5, 2_7, 1_5_9_3, 9_8_8, 1_3, 3_3_9_7_2, 7_0_2_9, 6, 2_0, 8_2_5_1, 3_8_3, 2, 2_7_0, 5_8_6_6, 3_7_8_8, 2, 2_3_5_3, 8_2_5_1, 1_2_3_3_8, 2, 1_3_9_5_8, 3_8_7, 2, 3_6_2_9, 6_9_5_3, 1_8_8, 2_9_0_0, 2, 1_3_9_5_8, 8_0_1_1, 1_1_5_0_1, 2_3, 8_4_6_0, 4_0_7_3, 3_4_0_0_9, 2_0, 4_3_5, 1_1_4_3_9, 2_7, 8, 8_4_6_0, 4_0_7_3, 6_0_0_4, 2_0, 9_9_8_8, 3_7_5, 2_7, 3_3, 2_6_6, 1_9_4_5, 1_0_7_6, 1_3_5_0, 3_7_8_6_7, 3_2_8_8, 5, 5_7_7, 1_0_7_6, 4_3_7_4, 8, 5_0_8_2, 5, 2_6_4_5_3, 2_5_7, 5_5_6, 4_0_3, 2, 2_4_2, 1_3_2, 3_8_3, 3_1_6, 4_9_2, 8, 1_0_7_6_7, 6, 3_1_6, 3_0_4, 4_2_3_9, 3, 0], [1_4_8, 1_5_7_2_2, 1_9, 1_8_3_9, 1_2, 1_3_5_0, 1_3, 2_2_3_2_7, 5_0_8_2, 5_4_1_8, 4_7_5_6_7, 3_5_9_3_8, 5_9, 3_1_8, 1_9_5_5_2, 1_0_8, 2_1_8_3, 5_4, 1_4_9_7_6, 4_8_3_5, 3_2, 5_4_7, 1_1_1_4, 8, 3_1_5, 2_4_1_7, 5, 9_2, 1_9_0_8_8, 3, 0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0], [3_6, 6_3_9_5, 1_2_5_7_0, 3_9_1_4_7, 1_1_5_9_7, 6, 2_6_6, 4, 4_5_4_0_5, 7_2_9_6, 3, 0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0, 5_8_1_0_0]], '''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, 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], [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]]}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=_a		,     model_name='Helsinki-NLP/opus-mt-en-de'		,     revision='1a8c2263da11e68e50938f97e10cd57820bd504c'		,     decode_kwargs={'use_source_tokenizer': True}		,     )







				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Optional[int]         =				MarianTokenizer.from_pretrained('hf-internal-testing/test-marian-two-vocabs' )

						A_		:    Any         =				'''Tämä on testi'''
						A_		:    List[Any]         =				'''This is a test'''

						A_		:    Tuple         =				[7_6, 7, 2_0_4_7, 2]
						A_		:    Union[str, Any]         =				[6_9, 1_2, 1_1, 9_4_0, 2]

						A_		:    str         =				tokenizer(_a ).input_ids
						self.assertListEqual(_a		,     _a )

						A_		:    str         =				tokenizer(text_target=_a ).input_ids
						self.assertListEqual(_a		,     _a )

						A_		:    List[str]         =				tokenizer.decode(_a		,     skip_special_tokens=_a )
						self.assertEqual(_a		,     _a )







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase            =		{
    """configuration_instructblip""": [
        """INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """InstructBlipConfig""",
        """InstructBlipQFormerConfig""",
        """InstructBlipVisionConfig""",
    ],
    """processing_instructblip""": ["""InstructBlipProcessor"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase            =		[
	    """INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """InstructBlipQFormerModel""",
	    """InstructBlipPreTrainedModel""",
	    """InstructBlipForConditionalGeneration""",
	    """InstructBlipVisionModel""",
	]

if TYPE_CHECKING:
	from .configuration_instructblip import (
	    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    InstructBlipConfig,
	    InstructBlipQFormerConfig,
	    InstructBlipVisionConfig,
	)
	from .processing_instructblip import InstructBlipProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_instructblip import (
		    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    InstructBlipForConditionalGeneration,
		    InstructBlipPreTrainedModel,
		    InstructBlipQFormerModel,
		    InstructBlipVisionModel,
		)

else:
	import sys

	_UpperCAmelCase            =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






