
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      A__							(     __magic_name__						,   unittest.TestCase	):
				lowercase			    =  MarianTokenizer
				lowercase			    =  False
				lowercase			    =  True






				def 							_lowerCamelCase		(						self					:      Tuple   ):






							'''simple docstring'''







							super().setUp()
							lowerCAmelCase__      :      Any         =		["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
							lowerCAmelCase__      :      Optional[int]         =		dict(zip(a    ,     range(len(a   )   )   )   )
							lowerCAmelCase__      :      int         =		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']   )

							lowerCAmelCase__      :      Optional[Any]         =		MarianTokenizer.from_pretrained(self.tmpdirname   )
							tokenizer.save_pretrained(self.tmpdirname   )






				def 							_lowerCamelCase		(						self					:      List[Any]    ,     **a					:      List[Any]   ):






							'''simple docstring'''







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






				def 							_lowerCamelCase		(						self					:      Optional[Any]    ,     a					:      int   ):






							'''simple docstring'''







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






				def 							_lowerCamelCase		(						self					:      Dict   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[Any]         =		"""</s>"""
							lowerCAmelCase__      :      Tuple         =		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					:      Optional[Any]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      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					:      Any   ):






							'''simple docstring'''







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






				def 							_lowerCamelCase		(						self					:      Tuple   ):






							'''simple docstring'''







							lowerCAmelCase__      :      int         =		MarianTokenizer.from_pretrained(f'''{ORG_NAME}opus-mt-en-de'''   )
							lowerCAmelCase__      :      Optional[int]         =		en_de_tokenizer(['I am a small frog']    ,     return_tensors=a   )
							self.assertIsInstance(a    ,     a   )
							lowerCAmelCase__      :      Union[str, Any]         =		[38, 121, 14, 697, 38_848, 0]
							self.assertListEqual(a    ,     batch.input_ids[0]   )

							lowerCAmelCase__      :      List[str]         =		tempfile.mkdtemp()
							en_de_tokenizer.save_pretrained(a   )
							lowerCAmelCase__      :      Dict         =		[x.name for x in Path(a   ).glob('*'   )]
							self.assertIn('source.spm'    ,     a   )
							MarianTokenizer.from_pretrained(a   )






				def 							_lowerCamelCase		(						self					:      Optional[int]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Tuple         =		self.get_tokenizer()

							lowerCAmelCase__      :      Dict         =		tok(
							    ['I am a small frog' * 1_000, 'I am a small frog']    ,     padding=a    ,     truncation=a    ,     return_tensors=a   )
							self.assertIsInstance(a    ,     a   )
							self.assertEqual(batch.input_ids.shape    ,     (2, 512)   )






				def 							_lowerCamelCase		(						self					:      str   ):






							'''simple docstring'''







							lowerCAmelCase__      :      str         =		self.get_tokenizer()
							lowerCAmelCase__      :      int         =		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, 10)   )






				@slow
				def 							_lowerCamelCase		(						self					:      Union[str, Any]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      str         =		{"""input_ids""": [[43_495, 462, 20, 42_164, 1_369, 52, 464, 132, 1_703, 492, 13, 7_491, 38_999, 6, 8, 464, 132, 1_703, 492, 13, 4_669, 37_867, 13, 7_525, 27, 1_593, 988, 13, 33_972, 7_029, 6, 20, 8_251, 383, 2, 270, 5_866, 3_788, 2, 2_353, 8_251, 12_338, 2, 13_958, 387, 2, 3_629, 6_953, 188, 2_900, 2, 13_958, 8_011, 11_501, 23, 8_460, 4_073, 34_009, 20, 435, 11_439, 27, 8, 8_460, 4_073, 6_004, 20, 9_988, 375, 27, 33, 266, 1_945, 1_076, 1_350, 37_867, 3_288, 5, 577, 1_076, 4_374, 8, 5_082, 5, 26_453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10_767, 6, 316, 304, 4_239, 3, 0], [148, 15_722, 19, 1_839, 12, 1_350, 13, 22_327, 5_082, 5_418, 47_567, 35_938, 59, 318, 19_552, 108, 2_183, 54, 14_976, 4_835, 32, 547, 1_114, 8, 315, 2_417, 5, 92, 19_088, 3, 0, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100], [36, 6_395, 12_570, 39_147, 11_597, 6, 266, 4, 45_405, 7_296, 3, 0, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100, 58_100]], """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					:      int   ):






							'''simple docstring'''







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

							lowerCAmelCase__      :      int         =		"""Tämä on testi"""
							lowerCAmelCase__      :      Any         =		"""This is a test"""

							lowerCAmelCase__      :      str         =		[76, 7, 2_047, 2]
							lowerCAmelCase__      :      Tuple         =		[69, 12, 11, 940, 2]

							lowerCAmelCase__      :      Tuple         =		tokenizer(a   ).input_ids
							self.assertListEqual(a    ,     a   )

							lowerCAmelCase__      :      Any         =		tokenizer(text_target=a   ).input_ids
							self.assertListEqual(a    ,     a   )

							lowerCAmelCase__      :      List[str]         =		tokenizer.decode(a    ,     skip_special_tokens=a   )
							self.assertEqual(a    ,     a   )



"""simple docstring"""






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase    :     Union[str, Any]   						=		{'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase    :     int   						=		[
							    'MRA_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'MraForMaskedLM',
							    'MraForMultipleChoice',
							    'MraForQuestionAnswering',
							    'MraForSequenceClassification',
							    'MraForTokenClassification',
							    'MraLayer',
							    'MraModel',
							    'MraPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mra import (
														    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MraForMaskedLM,
														    MraForMultipleChoice,
														    MraForQuestionAnswering,
														    MraForSequenceClassification,
														    MraForTokenClassification,
														    MraLayer,
														    MraModel,
														    MraPreTrainedModel,
														)
else:
							import sys

							UpperCAmelCase    :     Tuple   						=		_LazyModule(__name__, globals()['__file__'], _import_structure)
