



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


SCREAMING_SNAKE_CASE__       =      get_tests_dir('''fixtures/test_sentencepiece.model''')


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

SCREAMING_SNAKE_CASE__       =      5_0_0_0_3
SCREAMING_SNAKE_CASE__       =      5_0_0_0_2


@require_sentencepiece
@require_tokenizers
class      __lowerCAmelCase     (		UpperCAmelCase_							,     unittest.TestCase      ):
					"""simple docstring"""






					A__				:		Union[str, Any]			       =    PLBartTokenizer
					A__				:		Optional[Any]			       =    None
					A__				:		Tuple			       =    False



					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


								super().setUp()

								# We have a SentencePiece fixture for testing
								A__       =    PLBartTokenizer(_snake_case				,					language_codes='base'				,					keep_accents=_snake_case					)
								tokenizer.save_pretrained(self.tmpdirname					)



					def     _a							(     self					:       int					):






								"""simple docstring"""


								A__       =    PLBartTokenizer(_snake_case				,					language_codes='base'				,					keep_accents=_snake_case					)

								A__       =    tokenizer.tokenize('This is a test'					)
								self.assertListEqual(_snake_case				,					['▁This', '▁is', '▁a', '▁t', 'est']					)

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(_snake_case					)				,					[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]				,					)

								A__       =    tokenizer.tokenize('I was born in 92000, and this is falsé.'					)
								self.assertListEqual(
								    _snake_case				,					[
								        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',
								        '.',
								    ]				,					)
								A__       =    tokenizer.convert_tokens_to_ids(_snake_case					)
								self.assertListEqual(
								    _snake_case				,					[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]				,					)

								A__       =    tokenizer.convert_ids_to_tokens(_snake_case					)
								self.assertListEqual(
								    _snake_case				,					[
								        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>',
								        '.',
								    ]				,					)

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

								self.assertListEqual(_snake_case				,					['__java__', '__python__', '__en_XX__', '<mask>']					)

								A__       =    'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
								A__       =    tokenizer(_snake_case					).input_ids
								self.assertEqual(
								    tokenizer.decode(_snake_case				,					skip_special_tokens=_snake_case				,					clean_up_tokenization_spaces=_snake_case					)				,					_snake_case				,					)



					def     _a							(     self					:       List[Any]					):






								"""simple docstring"""


								A__       =    PLBartTokenizer(_snake_case				,					language_codes='multi'				,					keep_accents=_snake_case					)

								A__       =    tokenizer.tokenize('This is a test'					)
								self.assertListEqual(_snake_case				,					['▁This', '▁is', '▁a', '▁t', 'est']					)

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(_snake_case					)				,					[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]				,					)

								A__       =    tokenizer.tokenize('I was born in 92000, and this is falsé.'					)
								self.assertListEqual(
								    _snake_case				,					[
								        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',
								        '.',
								    ]				,					)
								A__       =    tokenizer.convert_tokens_to_ids(_snake_case					)
								self.assertListEqual(
								    _snake_case				,					[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]				,					)

								A__       =    tokenizer.convert_ids_to_tokens(_snake_case					)
								self.assertListEqual(
								    _snake_case				,					[
								        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>',
								        '.',
								    ]				,					)
								A__       =    tokenizer.vocab_size
								A__       =    [tokenizer.convert_ids_to_tokens(_snake_case					) for x in range(end - 7				,					_snake_case					)]

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







@require_torch
@require_sentencepiece
@require_tokenizers
class      __lowerCAmelCase     (		unittest.TestCase      ):
					"""simple docstring"""






					A__				:		List[str]			       =    "uclanlp/plbart-python-en_XX"
					A__				:		Optional[Any]			       =    [
					    "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__				:		Dict			       =    [
					    "Returns the maximum value of a b c.",
					    "Sums the values of a b c.",
					]
					A__				:		Tuple			       =    [
					    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     _a							(     cls					:       Dict					):






								"""simple docstring"""


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



					def     _a							(     self					:       Optional[Any]					):






								"""simple docstring"""


								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__java__']				,					5_00_01					)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__python__']				,					5_00_02					)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__en_XX__']				,					5_00_03					)



					def     _a							(     self					:       Optional[Any]					):






								"""simple docstring"""


								A__       =    self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
								self.assertListEqual(self.expected_src_tokens				,					_snake_case					)



					def     _a							(     self					:       str					):






								"""simple docstring"""


								self.assertIn(_snake_case				,					self.tokenizer.all_special_ids					)
								A__       =    [EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
								A__       =    self.tokenizer.decode(_snake_case				,					skip_special_tokens=_snake_case					)
								A__       =    self.tokenizer.decode(generated_ids[1:]				,					skip_special_tokens=_snake_case					)
								self.assertEqual(_snake_case				,					_snake_case					)
								self.assertNotIn(self.tokenizer.eos_token				,					_snake_case					)



					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


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



					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', '__java__']					)				,					[5_00_04, 5_00_01]					)



					def     _a							(     self					:       Union[str, Any]					):






								"""simple docstring"""


								A__       =    tempfile.mkdtemp()
								A__       =    self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(_snake_case					)
								A__       =    PLBartTokenizer.from_pretrained(_snake_case					)
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,					_snake_case					)



					@require_torch
					def     _a							(     self					:       Dict					):






								"""simple docstring"""


								A__       =    self.tokenizer(self.src_text				,					text_target=self.tgt_text				,					padding=_snake_case				,					return_tensors='pt'					)
								A__       =    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]				,					_snake_case					)
								self.assertEqual(batch.decoder_input_ids[1][-1]				,					2					)
								self.assertEqual(batch.labels[1][-2:].tolist()				,					[2, EN_CODE]					)



					@require_torch
					def     _a							(     self					:       str					):






								"""simple docstring"""


								A__       =    self.tokenizer(
								    self.src_text				,					text_target=self.tgt_text				,					padding=_snake_case				,					truncation=_snake_case				,					max_length=len(self.expected_src_tokens					)				,					return_tensors='pt'				,					)
								A__       =    shift_tokens_right(batch['labels']				,					self.tokenizer.pad_token_id					)

								self.assertIsInstance(_snake_case				,					_snake_case					)

								self.assertEqual((2, 26)				,					batch.input_ids.shape					)
								self.assertEqual((2, 26)				,					batch.attention_mask.shape					)
								A__       =    batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens				,					_snake_case					)
								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     _a							(     self					:       List[str]					):






								"""simple docstring"""


								A__       =    self.tokenizer(self.src_text				,					padding=_snake_case				,					truncation=_snake_case				,					max_length=3				,					return_tensors='pt'					)
								A__       =    self.tokenizer(
								    text_target=self.tgt_text				,					padding=_snake_case				,					truncation=_snake_case				,					max_length=10				,					return_tensors='pt'					)
								A__       =    targets['input_ids']
								A__       =    shift_tokens_right(_snake_case				,					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     _a							(     self					:       Dict					):






								"""simple docstring"""


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

								self.assertEqual(
								    nested_simplify(_snake_case					)				,					{
								        # A, test, EOS, en_XX
								        'input_ids': [[1_50, 2_42, 2, 5_00_03]],
								        'attention_mask': [[1, 1, 1, 1]],
								        # java
								        'forced_bos_token_id': 5_00_01,
								    }				,					)









import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


SCREAMING_SNAKE_CASE__       =      '''sshleifer/bart-tiny-random'''
SCREAMING_SNAKE_CASE__       =      '''patrickvonplaten/t5-tiny-random'''


@require_torch
class      __lowerCAmelCase     (		unittest.TestCase      ):
					"""simple docstring"""






					@cached_property
					def     _a							(     self					:       Optional[int]					):






								"""simple docstring"""


								return AutoConfig.from_pretrained(_snake_case					)



					def     _a							(     self					:       Optional[Any]					):






								"""simple docstring"""


								A__     , *A__       =    create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=1				,					d=1					)
								self.assertEqual(student.config.num_hidden_layers				,					1					)



					def     _a							(     self					:       Optional[int]					):






								"""simple docstring"""


								A__     , *A__       =    create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=1				,					d=_snake_case					)



					def     _a							(     self					:       int					):






								"""simple docstring"""


								A__     , *A__       =    create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=1				,					d=_snake_case					)
								self.assertEqual(student.config.encoder_layers				,					1					)
								self.assertEqual(student.config.decoder_layers				,					self.teacher_config.encoder_layers					)



					def     _a							(     self					:       str					):






								"""simple docstring"""


								A__     , *A__       =    create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=1				,					d=1					)
								self.assertEqual(student.config.encoder_layers				,					1					)
								self.assertEqual(student.config.decoder_layers				,					1					)



					def     _a							(     self					:       str					):






								"""simple docstring"""


								with self.assertRaises(_snake_case					):
											create_student_by_copying_alternating_layers(_snake_case				,					tempfile.mkdtemp()				,					e=_snake_case				,					d=_snake_case					)




