


import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


A	:		Dict    =       get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
	from transformers.models.plbart.modeling_plbart import shift_tokens_right

A	:		str    =       5_0_0_0_3
A	:		Union[str, Any]    =       5_0_0_0_2



@require_sentencepiece
@require_tokenizers
class 							A   (	UpperCAmelCase__			,  unittest.TestCase							):
					'''simple docstring'''






					A__      =			PLBartTokenizer
					A__      =			None
					A__      =			False

					def   lowerCamelCase__					(self   :						Optional[int]		)						->       Optional[int]:




							"""simple docstring"""


							super().setUp()

							# We have a SentencePiece fixture for testing
							lowercase__					      =		PLBartTokenizer(_UpperCAmelCase				, language_codes="""base"""				, keep_accents=_UpperCAmelCase		)
							tokenizer.save_pretrained(self.tmpdirname		)

					def   lowerCamelCase__					(self   :						List[str]		)						->       Optional[int]:




							"""simple docstring"""


							lowercase__					      =		PLBartTokenizer(_UpperCAmelCase				, language_codes="""base"""				, keep_accents=_UpperCAmelCase		)

							lowercase__					      =		tokenizer.tokenize("""This is a test"""		)
							self.assertListEqual(_UpperCAmelCase				, ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(_UpperCAmelCase		)				, [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]				, )

							lowercase__					      =		tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
							self.assertListEqual(
							    _UpperCAmelCase				, [
							        SPIECE_UNDERLINE + """I""",
							        SPIECE_UNDERLINE + """was""",
							        SPIECE_UNDERLINE + """b""",
							        """or""",
							        """n""",
							        SPIECE_UNDERLINE + """in""",
							        SPIECE_UNDERLINE + """""",
							        """9""",
							        """2""",
							        """0""",
							        """0""",
							        """0""",
							        """,""",
							        SPIECE_UNDERLINE + """and""",
							        SPIECE_UNDERLINE + """this""",
							        SPIECE_UNDERLINE + """is""",
							        SPIECE_UNDERLINE + """f""",
							        """al""",
							        """s""",
							        """é""",
							        """.""",
							    ]				, )
							lowercase__					      =		tokenizer.convert_tokens_to_ids(_UpperCAmelCase		)
							self.assertListEqual(
							    _UpperCAmelCase				, [
							        value + tokenizer.fairseq_offset
							        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
							    ]				, )

							lowercase__					      =		tokenizer.convert_ids_to_tokens(_UpperCAmelCase		)
							self.assertListEqual(
							    _UpperCAmelCase				, [
							        SPIECE_UNDERLINE + """I""",
							        SPIECE_UNDERLINE + """was""",
							        SPIECE_UNDERLINE + """b""",
							        """or""",
							        """n""",
							        SPIECE_UNDERLINE + """in""",
							        SPIECE_UNDERLINE + """""",
							        """<unk>""",
							        """2""",
							        """0""",
							        """0""",
							        """0""",
							        """,""",
							        SPIECE_UNDERLINE + """and""",
							        SPIECE_UNDERLINE + """this""",
							        SPIECE_UNDERLINE + """is""",
							        SPIECE_UNDERLINE + """f""",
							        """al""",
							        """s""",
							        """<unk>""",
							        """.""",
							    ]				, )

							lowercase__					      =		tokenizer.vocab_size
							lowercase__					      =		[tokenizer.convert_ids_to_tokens(_UpperCAmelCase		) for x in range(end - 4				, _UpperCAmelCase		)]

							self.assertListEqual(_UpperCAmelCase				, ["""__java__""", """__python__""", """__en_XX__""", """<mask>"""]		)

							lowercase__					      =		"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
							lowercase__					      =		tokenizer(_UpperCAmelCase		).input_ids
							self.assertEqual(
							    tokenizer.decode(_UpperCAmelCase				, skip_special_tokens=_UpperCAmelCase				, clean_up_tokenization_spaces=_UpperCAmelCase		)				, _UpperCAmelCase				, )


					def   lowerCamelCase__					(self   :						int		)						->       Optional[int]:




							"""simple docstring"""


							lowercase__					      =		PLBartTokenizer(_UpperCAmelCase				, language_codes="""multi"""				, keep_accents=_UpperCAmelCase		)

							lowercase__					      =		tokenizer.tokenize("""This is a test"""		)
							self.assertListEqual(_UpperCAmelCase				, ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(_UpperCAmelCase		)				, [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]				, )

							lowercase__					      =		tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
							self.assertListEqual(
							    _UpperCAmelCase				, [
							        SPIECE_UNDERLINE + """I""",
							        SPIECE_UNDERLINE + """was""",
							        SPIECE_UNDERLINE + """b""",
							        """or""",
							        """n""",
							        SPIECE_UNDERLINE + """in""",
							        SPIECE_UNDERLINE + """""",
							        """9""",
							        """2""",
							        """0""",
							        """0""",
							        """0""",
							        """,""",
							        SPIECE_UNDERLINE + """and""",
							        SPIECE_UNDERLINE + """this""",
							        SPIECE_UNDERLINE + """is""",
							        SPIECE_UNDERLINE + """f""",
							        """al""",
							        """s""",
							        """é""",
							        """.""",
							    ]				, )
							lowercase__					      =		tokenizer.convert_tokens_to_ids(_UpperCAmelCase		)
							self.assertListEqual(
							    _UpperCAmelCase				, [
							        value + tokenizer.fairseq_offset
							        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
							    ]				, )

							lowercase__					      =		tokenizer.convert_ids_to_tokens(_UpperCAmelCase		)
							self.assertListEqual(
							    _UpperCAmelCase				, [
							        SPIECE_UNDERLINE + """I""",
							        SPIECE_UNDERLINE + """was""",
							        SPIECE_UNDERLINE + """b""",
							        """or""",
							        """n""",
							        SPIECE_UNDERLINE + """in""",
							        SPIECE_UNDERLINE + """""",
							        """<unk>""",
							        """2""",
							        """0""",
							        """0""",
							        """0""",
							        """,""",
							        SPIECE_UNDERLINE + """and""",
							        SPIECE_UNDERLINE + """this""",
							        SPIECE_UNDERLINE + """is""",
							        SPIECE_UNDERLINE + """f""",
							        """al""",
							        """s""",
							        """<unk>""",
							        """.""",
							    ]				, )
							lowercase__					      =		tokenizer.vocab_size
							lowercase__					      =		[tokenizer.convert_ids_to_tokens(_UpperCAmelCase		) for x in range(end - 7				, _UpperCAmelCase		)]

							self.assertListEqual(
							    _UpperCAmelCase				, ["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]		)
							lowercase__					      =		"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
							lowercase__					      =		tokenizer(_UpperCAmelCase		).input_ids
							self.assertEqual(
							    tokenizer.decode(_UpperCAmelCase				, skip_special_tokens=_UpperCAmelCase				, clean_up_tokenization_spaces=_UpperCAmelCase		)				, _UpperCAmelCase				, )






@require_torch
@require_sentencepiece
@require_tokenizers
class 							A   (	unittest.TestCase							):
					'''simple docstring'''






					A__      =			'''uclanlp/plbart-python-en_XX'''
					A__      =			[
					    '''def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])''',
					    '''def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])''',
					]
					A__      =			[
					    '''Returns the maximum value of a b c.''',
					    '''Sums the values of a b c.''',
					]
					A__      =			[
					    1_34,
					    54_52,
					    3_34_60,
					    3_34_41,
					    3_34_63,
					    3_34_65,
					    3_34_63,
					    3_34_49,
					    9_88,
					    20,
					    3_34_56,
					    19,
					    3_34_56,
					    7_71,
					    39,
					    42_58,
					    8_89,
					    33_18,
					    3_34_41,
					    3_34_63,
					    3_34_65,
					    3_34_63,
					    3_34_49,
					    24_71,
					    2,
					    PYTHON_CODE,
					]

					@classmethod
					def   lowerCamelCase__					(cls   :						List[str]		)						->       str:




							"""simple docstring"""


							lowercase__					      =		PLBartTokenizer.from_pretrained(
							    cls.checkpoint_name				, language_codes="""base"""				, src_lang="""python"""				, tgt_lang="""en_XX"""		)
							lowercase__					      =		1
							return cls

					def   lowerCamelCase__					(self   :						Union[str, Any]		)						->       List[Any]:




							"""simple docstring"""


							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__java__"""]				, 5_0001		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__python__"""]				, 5_0002		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__en_XX__"""]				, 5_0003		)

					def   lowerCamelCase__					(self   :						Union[str, Any]		)						->       Optional[Any]:




							"""simple docstring"""


							lowercase__					      =		self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
							self.assertListEqual(self.expected_src_tokens				, _UpperCAmelCase		)

					def   lowerCamelCase__					(self   :						Tuple		)						->       Optional[Any]:




							"""simple docstring"""


							self.assertIn(_UpperCAmelCase				, self.tokenizer.all_special_ids		)
							lowercase__					      =		[EN_CODE, 9037, 3_3442, 57, 752, 153, 14, 56, 18, 9, 2]
							lowercase__					      =		self.tokenizer.decode(_UpperCAmelCase				, skip_special_tokens=_UpperCAmelCase		)
							lowercase__					      =		self.tokenizer.decode(generated_ids[1:]				, skip_special_tokens=_UpperCAmelCase		)
							self.assertEqual(_UpperCAmelCase				, _UpperCAmelCase		)
							self.assertNotIn(self.tokenizer.eos_token				, _UpperCAmelCase		)

					def   lowerCamelCase__					(self   :						Optional[Any]		)						->       List[str]:




							"""simple docstring"""


							lowercase__					      =		["""def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""" * 20]
							self.assertIsInstance(src_text[0]				, _UpperCAmelCase		)
							lowercase__					      =		10
							lowercase__					      =		self.tokenizer(_UpperCAmelCase				, max_length=_UpperCAmelCase				, truncation=_UpperCAmelCase		).input_ids[0]
							self.assertEqual(ids[-2]				, 2		)
							self.assertEqual(ids[-1]				, _UpperCAmelCase		)
							self.assertEqual(len(_UpperCAmelCase		)				, _UpperCAmelCase		)

					def   lowerCamelCase__					(self   :						Union[str, Any]		)						->       int:




							"""simple docstring"""


							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]		)				, [5_0004, 5_0001]		)

					def   lowerCamelCase__					(self   :						Dict		)						->       List[str]:




							"""simple docstring"""


							lowercase__					      =		tempfile.mkdtemp()
							lowercase__					      =		self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(_UpperCAmelCase		)
							lowercase__					      =		PLBartTokenizer.from_pretrained(_UpperCAmelCase		)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids				, _UpperCAmelCase		)

					@require_torch
					def   lowerCamelCase__					(self   :						List[str]		)						->       Any:




							"""simple docstring"""


							lowercase__					      =		self.tokenizer(self.src_text				, text_target=self.tgt_text				, padding=_UpperCAmelCase				, return_tensors="""pt"""		)
							lowercase__					      =		shift_tokens_right(batch["""labels"""]				, self.tokenizer.pad_token_id		)

							# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
							self.assertEqual(batch.input_ids[1][-2:].tolist()				, [2, PYTHON_CODE]		)
							self.assertEqual(batch.decoder_input_ids[1][0]				, _UpperCAmelCase		)
							self.assertEqual(batch.decoder_input_ids[1][-1]				, 2		)
							self.assertEqual(batch.labels[1][-2:].tolist()				, [2, EN_CODE]		)

					@require_torch
					def   lowerCamelCase__					(self   :						Optional[int]		)						->       List[Any]:




							"""simple docstring"""


							lowercase__					      =		self.tokenizer(
							    self.src_text				, text_target=self.tgt_text				, padding=_UpperCAmelCase				, truncation=_UpperCAmelCase				, max_length=len(self.expected_src_tokens		)				, return_tensors="""pt"""				, )
							lowercase__					      =		shift_tokens_right(batch["""labels"""]				, self.tokenizer.pad_token_id		)

							self.assertIsInstance(_UpperCAmelCase				, _UpperCAmelCase		)

							self.assertEqual((2, 26)				, batch.input_ids.shape		)
							self.assertEqual((2, 26)				, batch.attention_mask.shape		)
							lowercase__					      =		batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens				, _UpperCAmelCase		)
							self.assertEqual(2				, batch.decoder_input_ids[0, -1]		)  # EOS
							# Test that special tokens are reset
							self.assertEqual(self.tokenizer.prefix_tokens				, []		)
							self.assertEqual(self.tokenizer.suffix_tokens				, [self.tokenizer.eos_token_id, PYTHON_CODE]		)

					def   lowerCamelCase__					(self   :						Dict		)						->       Optional[Any]:




							"""simple docstring"""


							lowercase__					      =		self.tokenizer(self.src_text				, padding=_UpperCAmelCase				, truncation=_UpperCAmelCase				, max_length=3				, return_tensors="""pt"""		)
							lowercase__					      =		self.tokenizer(
							    text_target=self.tgt_text				, padding=_UpperCAmelCase				, truncation=_UpperCAmelCase				, max_length=10				, return_tensors="""pt"""		)
							lowercase__					      =		targets["""input_ids"""]
							lowercase__					      =		shift_tokens_right(_UpperCAmelCase				, self.tokenizer.pad_token_id		)

							self.assertEqual(batch.input_ids.shape[1]				, 3		)
							self.assertEqual(batch.decoder_input_ids.shape[1]				, 10		)


					@require_torch
					def   lowerCamelCase__					(self   :						Optional[int]		)						->       str:




							"""simple docstring"""


							lowercase__					      =		self.tokenizer._build_translation_inputs(
							    """A test"""				, return_tensors="""pt"""				, src_lang="""en_XX"""				, tgt_lang="""java"""		)

							self.assertEqual(
							    nested_simplify(_UpperCAmelCase		)				, {
							        # A, test, EOS, en_XX
							        """input_ids""": [[150, 242, 2, 5_0003]],
							        """attention_mask""": [[1, 1, 1, 1]],
							        # java
							        """forced_bos_token_id""": 5_0001,
							    }				, )





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A	:		Dict    =       {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:		Tuple    =       ['GLPNFeatureExtractor']
	A	:		List[str]    =       ['GLPNImageProcessor']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:		Optional[int]    =       [
	    'GLPN_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'GLPNForDepthEstimation',
	    'GLPNLayer',
	    'GLPNModel',
	    'GLPNPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_glpn import GLPNFeatureExtractor
		from .image_processing_glpn import GLPNImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_glpn import (
		    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GLPNForDepthEstimation,
		    GLPNLayer,
		    GLPNModel,
		    GLPNPreTrainedModel,
		)


else:
	import sys

	A	:		Tuple    =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

