






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


a_     :   Optional[Any]							=    get_tests_dir('''fixtures/test_sentencepiece.model''')

a_     :   Any							=    {'''target_lang''': '''fi''', '''source_lang''': '''en'''}
a_     :   List[str]							=    '''>>zh<<'''
a_     :   List[Any]							=    '''Helsinki-NLP/'''

if is_torch_available():
	a_     :   Optional[int]							=    '''pt'''
elif is_tf_available():
	a_     :   Optional[int]							=    '''tf'''
else:
	a_     :   Any							=    '''jax'''


@require_sentencepiece
class      lowercase__     (			_UpperCAmelCase,					unittest.TestCase	):
	a_         =MarianTokenizer
	a_         =False
	a_         =True

	def 		UpperCAmelCase  (							self       )->					Tuple:







							'''simple docstring'''





							super().setUp()
							lowerCAmelCase__       =						["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
							lowerCAmelCase__       =						dict(zip(lowercase__		,    range(len(lowercase__       )       )       )       )
							lowerCAmelCase__       =						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"]       )

							lowerCAmelCase__       =						MarianTokenizer.from_pretrained(self.tmpdirname       )
							tokenizer.save_pretrained(self.tmpdirname       )

	def 		UpperCAmelCase  (							self		,    **__UpperCAmelCase       )->					Any:







							'''simple docstring'''





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

	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					Any:







							'''simple docstring'''





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

	def 		UpperCAmelCase  (							self       )->					int:







							'''simple docstring'''





							lowerCAmelCase__       =						"""</s>"""
							lowerCAmelCase__       =						0

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

	def 		UpperCAmelCase  (							self       )->					Any:







							'''simple docstring'''





							lowerCAmelCase__       =						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 		UpperCAmelCase  (							self       )->					List[Any]:







							'''simple docstring'''





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

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







							'''simple docstring'''





							lowerCAmelCase__       =						MarianTokenizer.from_pretrained(F"{ORG_NAME}opus-mt-en-de"       )
							lowerCAmelCase__       =						en_de_tokenizer(["I am a small frog"]		,    return_tensors=lowercase__       )
							self.assertIsInstance(lowercase__		,    lowercase__       )
							lowerCAmelCase__       =						[38, 121, 14, 697, 38848, 0]
							self.assertListEqual(lowercase__		,    batch.input_ids[0]       )

							lowerCAmelCase__       =						tempfile.mkdtemp()
							en_de_tokenizer.save_pretrained(lowercase__       )
							lowerCAmelCase__       =						[x.name for x in Path(lowercase__       ).glob("*"       )]
							self.assertIn("source.spm"		,    lowercase__       )
							MarianTokenizer.from_pretrained(lowercase__       )

	def 		UpperCAmelCase  (							self       )->					str:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_tokenizer()

							lowerCAmelCase__       =						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 		UpperCAmelCase  (							self       )->					List[Any]:







							'''simple docstring'''





							lowerCAmelCase__       =						self.get_tokenizer()
							lowerCAmelCase__       =						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 		UpperCAmelCase  (							self       )->					Any:







							'''simple docstring'''





							lowerCAmelCase__       =						{"""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 		UpperCAmelCase  (							self       )->					Union[str, Any]:







							'''simple docstring'''





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

							lowerCAmelCase__       =						"""Tämä on testi"""
							lowerCAmelCase__       =						"""This is a test"""

							lowerCAmelCase__       =						[76, 7, 2047, 2]
							lowerCAmelCase__       =						[69, 12, 11, 940, 2]

							lowerCAmelCase__       =						tokenizer(lowercase__       ).input_ids
							self.assertListEqual(lowercase__		,    lowercase__       )

							lowerCAmelCase__       =						tokenizer(text_target=lowercase__       ).input_ids
							self.assertListEqual(lowercase__		,    lowercase__       )

							lowerCAmelCase__       =						tokenizer.decode(lowercase__		,    skip_special_tokens=lowercase__       )
							self.assertEqual(lowercase__		,    lowercase__       )














import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

a_							=    logging.getLogger()


def        _a  (     UpperCamelCase_					:				Union[str, Any]   ) ->   Dict:
						"""simple docstring"""







						lowerCAmelCase__       =						{}
						lowerCAmelCase__       =						os.path.join(UpperCamelCase_    ,   "all_results.json"   )
						if os.path.exists(UpperCamelCase_   ):
												with open(UpperCamelCase_    ,   "r"   ) as f:
																		lowerCAmelCase__       =						json.load(UpperCamelCase_   )
						else:
												raise ValueError(F"can't find {path}"   )
						return results


a_							=    logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





@require_torch_tpu
class      lowercase__     (			_UpperCAmelCase	):

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						self.get_auto_remove_tmp_dir()
							lowerCAmelCase__       =						F"\n            ./examples/pytorch/text-classification/run_glue.py\n            --num_cores=8\n            ./examples/pytorch/text-classification/run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --do_train\n            --do_eval\n            --debug tpu_metrics_debug\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --max_steps=10\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

							with patch.object(__UpperCAmelCase		,    "argv"		,    __UpperCAmelCase       ):
													lowerCAmelCase__       =						time()
													xla_spawn.main()
													lowerCAmelCase__       =						time()

													lowerCAmelCase__       =						get_results(__UpperCAmelCase       )
													self.assertGreaterEqual(result["eval_accuracy"]		,    0.75       )

													# Assert that the script takes less than 500 seconds to make sure it doesn't hang.
													self.assertLess(end - start		,    500       )


	def 		UpperCAmelCase  (							self       )->					Dict:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						"\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            ".split()
							with patch.object(__UpperCAmelCase		,    "argv"		,    __UpperCAmelCase       ):
													xla_spawn.main()






