



"""simple docstring"""

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


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

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

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




@require_sentencepiece
class SCREAMING_SNAKE_CASE__					(		__snake_case     ,					unittest.TestCase      ):
						_lowerCAmelCase							=					MarianTokenizer
						_lowerCAmelCase							=					False
						_lowerCAmelCase							=					True



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

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

													__a		:		Any									=       MarianTokenizer.from_pretrained(self.tmpdirname							)
													tokenizer.save_pretrained(self.tmpdirname							)



						def     lowerCAmelCase__(self						,     **_lowercase							):





													'''simple docstring'''

													return MarianTokenizer.from_pretrained(self.tmpdirname						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													return (
													    "This is a test",
													    "This is a test",
													)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Dict									=       """</s>"""
													__a		:		List[str]									=       0

													self.assertEqual(self.get_tokenizer()._convert_token_to_id(_lowercase							)						,     _lowercase							)
													self.assertEqual(self.get_tokenizer()._convert_id_to_token(_lowercase							)						,     _lowercase							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		int									=       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(_lowercase							)						,     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		:		Optional[Any]									=       en_de_tokenizer(["""I am a small frog"""]						,     return_tensors=_lowercase							)
													self.assertIsInstance(_lowercase						,     _lowercase							)
													__a		:		Optional[int]									=       [38, 121, 14, 697, 38848, 0]
													self.assertListEqual(_lowercase						,     batch.input_ids[0]							)

													__a		:		str									=       tempfile.mkdtemp()
													en_de_tokenizer.save_pretrained(_lowercase							)
													__a		:		Any									=       [x.name for x in Path(_lowercase							).glob("""*"""							)]
													self.assertIn("""source.spm"""						,     _lowercase							)
													MarianTokenizer.from_pretrained(_lowercase							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		List[Any]									=       self.get_tokenizer()

													__a		:		Optional[int]									=       tok(
													    ["""I am a small frog""" * 1000, """I am a small frog"""]						,     padding=_lowercase						,     truncation=_lowercase						,     return_tensors=_lowercase							)
													self.assertIsInstance(_lowercase						,     _lowercase							)
													self.assertEqual(batch.input_ids.shape						,     (2, 512)							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		List[str]									=       self.get_tokenizer()
													__a		:		Dict									=       tok(["""I am a tiny frog""", """I am a small frog"""]						,     padding=_lowercase						,     return_tensors=_lowercase							)
													self.assertIsInstance(_lowercase						,     _lowercase							)
													self.assertEqual(batch_smaller.input_ids.shape						,     (2, 10)							)



						@slow
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		int									=       {"""input_ids""": [[43495, 462, 20, 42164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 38999, 6, 8, 464, 132, 1703, 492, 13, 4669, 37867, 13, 7525, 27, 1593, 988, 13, 33972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 12338, 2, 13958, 387, 2, 3629, 6953, 188, 2900, 2, 13958, 8011, 11501, 23, 8460, 4073, 34009, 20, 435, 11439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 37867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 26453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10767, 6, 316, 304, 4239, 3, 0], [148, 15722, 19, 1839, 12, 1350, 13, 22327, 5082, 5418, 47567, 35938, 59, 318, 19552, 108, 2183, 54, 14976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 19088, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100], [36, 6395, 12570, 39147, 11597, 6, 266, 4, 45405, 7296, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100]], """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=_lowercase						,     model_name="""Helsinki-NLP/opus-mt-en-de"""						,     revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""						,     decode_kwargs={"""use_source_tokenizer""": True}						,     )





						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Dict									=       MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs"""							)

													__a		:		Optional[int]									=       """Tämä on testi"""
													__a		:		Tuple									=       """This is a test"""

													__a		:		List[Any]									=       [76, 7, 2047, 2]
													__a		:		List[Any]									=       [69, 12, 11, 940, 2]

													__a		:		Union[str, Any]									=       tokenizer(_lowercase							).input_ids
													self.assertListEqual(_lowercase						,     _lowercase							)

													__a		:		Optional[int]									=       tokenizer(text_target=_lowercase							).input_ids
													self.assertListEqual(_lowercase						,     _lowercase							)

													__a		:		Tuple									=       tokenizer.decode(_lowercase						,     skip_special_tokens=_lowercase							)
													self.assertEqual(_lowercase						,     _lowercase							)






"""simple docstring"""

import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class SCREAMING_SNAKE_CASE__					(		__snake_case     ,					unittest.TestCase      ):
						_lowerCAmelCase							=					LEDTokenizer
						_lowerCAmelCase							=					LEDTokenizerFast
						_lowerCAmelCase							=					True



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													super().setUp()
													__a		:		str									=       [
													    """l""",
													    """o""",
													    """w""",
													    """e""",
													    """r""",
													    """s""",
													    """t""",
													    """i""",
													    """d""",
													    """n""",
													    """\u0120""",
													    """\u0120l""",
													    """\u0120n""",
													    """\u0120lo""",
													    """\u0120low""",
													    """er""",
													    """\u0120lowest""",
													    """\u0120newer""",
													    """\u0120wider""",
													    """<unk>""",
													]
													__a		:		int									=       dict(zip(_lowercase						,     range(len(_lowercase							)							)							)							)
													__a		:		Optional[int]									=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
													__a		:		List[Any]									=       {"""unk_token""": """<unk>"""}

													__a		:		Union[str, Any]									=       os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES["""vocab_file"""]							)
													__a		:		Union[str, Any]									=       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(_lowercase							) + """\n"""							)
													with open(self.merges_file						,     """w"""						,     encoding="""utf-8"""							) as fp:
																				fp.write("""\n""".join(_lowercase							)							)



						def     lowerCAmelCase__(self						,     **_lowercase							):





													'''simple docstring'''

													kwargs.update(self.special_tokens_map							)
													return self.tokenizer_class.from_pretrained(self.tmpdirname						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     **_lowercase							):





													'''simple docstring'''

													kwargs.update(self.special_tokens_map							)
													return self.rust_tokenizer_class.from_pretrained(self.tmpdirname						,     **_lowercase							)



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													return "lower newer", "lower newer"



						@cached_property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""							)



						@cached_property
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Any									=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
													__a		:		List[str]									=       [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Optional[int]									=       tokenizer(_lowercase						,     max_length=len(_lowercase							)						,     padding=_lowercase						,     return_tensors="""pt"""							)
																				self.assertIsInstance(_lowercase						,     _lowercase							)

																				self.assertEqual((2, 9)						,     batch.input_ids.shape							)
																				self.assertEqual((2, 9)						,     batch.attention_mask.shape							)
																				__a		:		Dict									=       batch.input_ids.tolist()[0]
																				self.assertListEqual(_lowercase						,     _lowercase							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Union[str, Any]									=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Tuple									=       tokenizer(_lowercase						,     padding=_lowercase						,     return_tensors="""pt"""							)
																				self.assertIn("""input_ids"""						,     _lowercase							)
																				self.assertIn("""attention_mask"""						,     _lowercase							)
																				self.assertNotIn("""labels"""						,     _lowercase							)
																				self.assertNotIn("""decoder_attention_mask"""						,     _lowercase							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Optional[Any]									=       [
													    """Summary of the text.""",
													    """Another summary.""",
													]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Dict									=       tokenizer(text_target=_lowercase						,     max_length=32						,     padding="""max_length"""						,     return_tensors="""pt"""							)
																				self.assertEqual(32						,     targets["""input_ids"""].shape[1]							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Optional[int]									=       tokenizer(
																				    ["""I am a small frog""" * 1024, """I am a small frog"""]						,     padding=_lowercase						,     truncation=_lowercase						,     return_tensors="""pt"""							)
																				self.assertIsInstance(_lowercase						,     _lowercase							)
																				self.assertEqual(batch.input_ids.shape						,     (2, 5122)							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Tuple									=       ["""A long paragraph for summarization."""]
													__a		:		Dict									=       [
													    """Summary of the text.""",
													]
													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		int									=       tokenizer(_lowercase						,     return_tensors="""pt"""							)
																				__a		:		Dict									=       tokenizer(text_target=_lowercase						,     return_tensors="""pt"""							)
																				__a		:		List[str]									=       inputs["""input_ids"""]
																				__a		:		List[Any]									=       targets["""input_ids"""]
																				self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()							)
																				self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()							)
																				self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()							)
																				self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()							)



						@require_torch
						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																				__a		:		Optional[Any]									=       ["""Summary of the text.""", """Another summary."""]
																				__a		:		List[Any]									=       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

																				__a		:		Union[str, Any]									=       tokenizer(_lowercase						,     padding=_lowercase							)
																				__a		:		Tuple									=       [[0] * len(_lowercase							) for x in encoded_output["""input_ids"""]]
																				__a		:		Union[str, Any]									=       tokenizer.pad(_lowercase							)
																				self.assertSequenceEqual(outputs["""global_attention_mask"""]						,     _lowercase							)



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													pass





						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																				with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
																											__a		:		Dict									=       self.rust_tokenizer_class.from_pretrained(_lowercase						,     **_lowercase							)
																											__a		:		Union[str, Any]									=       self.tokenizer_class.from_pretrained(_lowercase						,     **_lowercase							)
																											__a		:		Union[str, Any]									=       """A, <mask> AllenNLP sentence."""
																											__a		:		Dict									=       tokenizer_r.encode_plus(_lowercase						,     add_special_tokens=_lowercase						,     return_token_type_ids=_lowercase							)
																											__a		:		Tuple									=       tokenizer_p.encode_plus(_lowercase						,     add_special_tokens=_lowercase						,     return_token_type_ids=_lowercase							)
																											self.assertEqual(sum(tokens_r["""token_type_ids"""]							)						,     sum(tokens_p["""token_type_ids"""]							)							)
																											self.assertEqual(
																											    sum(tokens_r["""attention_mask"""]							) / len(tokens_r["""attention_mask"""]							)						,     sum(tokens_p["""attention_mask"""]							) / len(tokens_p["""attention_mask"""]							)						,     )

																											__a		:		Tuple									=       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]							)
																											__a		:		Any									=       tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]							)
																											self.assertSequenceEqual(tokens_p["""input_ids"""]						,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)
																											self.assertSequenceEqual(tokens_r["""input_ids"""]						,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)

																											self.assertSequenceEqual(
																											    _lowercase						,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]							)
																											self.assertSequenceEqual(
																											    _lowercase						,     ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]							)

