



# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__lowerCamelCase         =			'''2.13.1'''

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('''3.7'''):
   raise ImportWarning(
       '''To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'''
   )

if version.parse(pyarrow.__version__).major < 8:
   raise ImportWarning(
       '''To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'''
       '''If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'''
   )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

__lowerCamelCase         =			concatenate_datasets
__lowerCamelCase         =			DownloadConfig
__lowerCamelCase         =			DownloadManager
__lowerCamelCase         =			DownloadMode
__lowerCamelCase         =			DownloadConfig
__lowerCamelCase         =			DownloadMode
__lowerCamelCase         =			DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager





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


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

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

if is_torch_available():
   __lowerCamelCase         =			'''pt'''
elif is_tf_available():
   __lowerCamelCase         =			'''tf'''
else:
   __lowerCamelCase         =			'''jax'''


@require_sentencepiece
class   snake_case_ (lowercase__ , unittest.TestCase  ):




       """simple docstring"""






       _lowerCamelCase			    =				MarianTokenizer
       _lowerCamelCase			    =				False
       _lowerCamelCase			    =				True



       def  A_   (     self):

             """simple docstring"""





             super().setUp()
             UpperCAmelCase_  :	Union[str, Any]				      =		["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
             UpperCAmelCase_  :	Union[str, Any]				      =		dict(zip(lowercase     ,range(len(lowercase))))
             UpperCAmelCase_  :	int				      =		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"])

             UpperCAmelCase_  :	str				      =		MarianTokenizer.from_pretrained(self.tmpdirname)
             tokenizer.save_pretrained(self.tmpdirname)



       def  A_   (     self     ,**lowercase):

             """simple docstring"""





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



       def  A_   (     self     ,lowercase):

             """simple docstring"""





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



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Union[str, Any]				      =		"</s>"
             UpperCAmelCase_  :	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  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[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(lowercase)     ,9)



       def  A_   (     self):

             """simple docstring"""





             self.assertEqual(self.get_tokenizer().vocab_size     ,9)



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[str]				      =		MarianTokenizer.from_pretrained(F"""{ORG_NAME}opus-mt-en-de""")
             UpperCAmelCase_  :	Optional[int]				      =		en_de_tokenizer(["I am a small frog"]     ,return_tensors=lowercase)
             self.assertIsInstance(lowercase     ,lowercase)
             UpperCAmelCase_  :	Union[str, Any]				      =		[38, 121, 14, 697, 38848, 0]
             self.assertListEqual(lowercase     ,batch.input_ids[0])

             UpperCAmelCase_  :	Optional[int]				      =		tempfile.mkdtemp()
             en_de_tokenizer.save_pretrained(lowercase)
             UpperCAmelCase_  :	Any				      =		[x.name for x in Path(lowercase).glob("*")]
             self.assertIn("source.spm"     ,lowercase)
             MarianTokenizer.from_pretrained(lowercase)



       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Any				      =		self.get_tokenizer()

             UpperCAmelCase_  :	List[Any]				      =		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  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[Any]				      =		self.get_tokenizer()
             UpperCAmelCase_  :	Optional[int]				      =		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  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Dict				      =		{"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  A_   (     self):

             """simple docstring"""





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

             UpperCAmelCase_  :	Any				      =		"Tämä on testi"
             UpperCAmelCase_  :	List[str]				      =		"This is a test"

             UpperCAmelCase_  :	int				      =		[76, 7, 2047, 2]
             UpperCAmelCase_  :	Any				      =		[69, 12, 11, 940, 2]

             UpperCAmelCase_  :	Any				      =		tokenizer(lowercase).input_ids
             self.assertListEqual(lowercase     ,lowercase)

             UpperCAmelCase_  :	Any				      =		tokenizer(text_target=lowercase).input_ids
             self.assertListEqual(lowercase     ,lowercase)

             UpperCAmelCase_  :	List[Any]				      =		tokenizer.decode(lowercase     ,skip_special_tokens=lowercase)
             self.assertEqual(lowercase     ,lowercase)
