






import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


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


@require_sentencepiece
class    _lowerCAmelCase			(		lowercase_     ,      unittest.TestCase      ):



			"""simple docstring"""



			_lowercase				:   Optional[int]      =  XLMProphetNetTokenizer
			_lowercase				:   Optional[Any]      =  False
			_lowercase				:   Optional[Any]      =  True



			def 					__magic_name__							(      self    :    Tuple):






										'''simple docstring'''







										super().setUp()

										# We have a SentencePiece fixture for testing
										snake_case__	  =       XLMProphetNetTokenizer(UpperCamelCase__			,		keep_accents=UpperCamelCase__)
										tokenizer.save_pretrained(self.tmpdirname)



			def 					__magic_name__							(      self    :    Dict):






										'''simple docstring'''







										snake_case__	  =       """[PAD]"""
										snake_case__	  =       0

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



			def 					__magic_name__							(      self    :    Any):






										'''simple docstring'''







										snake_case__	  =       list(self.get_tokenizer().get_vocab().keys())

										self.assertEqual(vocab_keys[0]			,		"""[PAD]""")
										self.assertEqual(vocab_keys[1]			,		"""[CLS]""")
										self.assertEqual(vocab_keys[-1]			,		"""j""")
										self.assertEqual(len(UpperCamelCase__)			,		1_0_1_2)



			def 					__magic_name__							(      self    :    Optional[Any]):






										'''simple docstring'''







										self.assertEqual(self.get_tokenizer().vocab_size			,		1_0_1_2)



			def 					__magic_name__							(      self    :    Any):






										'''simple docstring'''







										snake_case__	  =       XLMProphetNetTokenizer(UpperCamelCase__			,		keep_accents=UpperCamelCase__)

										snake_case__	  =       tokenizer.tokenize("""This is a test""")
										self.assertListEqual(UpperCamelCase__			,		["""▁This""", """▁is""", """▁a""", """▁t""", """est"""])

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(UpperCamelCase__)			,		[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]			,		)

										snake_case__	  =       tokenizer.tokenize("""I was born in 92000, and this is falsé.""")
										self.assertListEqual(
										    UpperCamelCase__			,		[
										        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""",
										        """.""",
										    ]			,		)
										snake_case__	  =       tokenizer.convert_tokens_to_ids(UpperCamelCase__)
										self.assertListEqual(
										    UpperCamelCase__			,		[
										        value + tokenizer.fairseq_offset
										        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, -9, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, -9, 4]
										    ]			,		)

										snake_case__	  =       tokenizer.convert_ids_to_tokens(UpperCamelCase__)
										self.assertListEqual(
										    UpperCamelCase__			,		[
										        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]""",
										        """.""",
										    ]			,		)



			@cached_property
			def 					__magic_name__							(      self    :    Union[str, Any]):






										'''simple docstring'''







										return XLMProphetNetTokenizer.from_pretrained("""microsoft/xprophetnet-large-wiki100-cased""")



			@slow
			def 					__magic_name__							(      self    :    Dict):






										'''simple docstring'''







										snake_case__	  =       """Hello World!"""
										snake_case__	  =       [3_5_3_8_9, 6_6_7_2, 4_9, 2]
										self.assertListEqual(UpperCamelCase__			,		self.big_tokenizer.encode(UpperCamelCase__))



			@slow
			def 					__magic_name__							(      self    :    Dict):






										'''simple docstring'''







										snake_case__	  =       {"""input_ids""": [[1_1_0_7_3, 8_2_7_8_3, 1_8, 2_6, 8_2_7_8_3, 5_4_9, 5_1_5_4_0, 2_4_8, 1_7_2_0_9, 1_3_0_1, 2_1_7, 2_0, 2_1_5_1_8_6, 1_3_2_5, 1_4_7, 1_7_2_0_9, 1_3_0_1, 2_1_7, 2_0, 5_6_3_7_0, 5_3, 1_2_2_0_2_0, 2_0, 1_6_4_7_7, 2_7, 8_7_3_5_5, 4_5_4_8, 2_0, 4_7_2_8, 7_8_3_9_2, 1_7, 1_5_9_9_6_9, 1_8, 2_6, 2_4_4_9_1, 6_2_9, 1_5, 5_3_8, 2_2_7_0_4, 5_4_3_9, 1_5, 2_7_8_8, 2_4_4_9_1, 9_8_8_5, 1_5, 4_3_5_3_4, 6_0_5, 1_5, 8_1_4, 1_8_4_0_3, 3_3_2_0_0, 2_9, 1_5, 4_3_5_3_4, 2_4_4_5_8, 1_2_4_1_0, 1_1_1, 2_4_9_6_6, 8_3_6_6_9, 9_6_3_7, 1_4_4_0_6_8, 2_6, 8_5_0, 2_2_3_4_6, 2_7, 1_4_7, 2_4_9_6_6, 8_3_6_6_9, 8_3_4_9_0, 2_6, 3_9_1_1_3, 7_3_5, 2_7, 6_8_9, 6_5_6, 2_8_0_0, 1_3_3_9, 4_6_0_0, 5_3, 1_2_2_0_2_0, 1_1_5_7_8_5, 3_4, 8_1_6, 1_3_3_9, 4_6_8_8_7, 1_8, 1_4_7, 5_3_9_0_5, 1_9_5_1, 4_2_2_3_8, 4_1_1_7_0, 1_7_7_3_2, 8_3_4, 4_3_6, 1_5, 2_7_5_2_3, 9_8_7_3_3, 2_1_7, 1_4_7, 5_5_4_2, 4_9_8_1, 9_3_0, 1_7_3_4_7, 1_6, 2], [2_0_0_9_1, 6_2_9, 9_4, 8_2_7_8_6, 5_8, 4_9_0, 2_0, 1_5_2_8, 8_4, 5_3_9_0_5, 3_4_4, 8_0_5_9_2, 1_1_0_1_2_8, 1_8_8_2_2, 5_2_6_7, 1_3_0_6, 6_2, 1_5_2_5_3_7, 3_0_8, 7_9_9_7, 4_0_1, 1_2_4_4_2_7, 5_4_9, 3_5_4_4_2, 2_2_5, 1_0_9, 1_5_0_5_5, 2_5_7_4_8, 1_4_7, 7_1_1_9, 4_3_7_1_2, 3_4, 7_6_7, 1_3_5_3_6_6, 1_8, 1_6, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_9_2, 6_3_7_8_4, 1_1_9_4_6_6, 1_7, 1_4_7_8_0_8, 8_8_2_1_4, 1_8, 6_5_6, 8_1, 3_2, 3_2_9_6, 1_0_2_8_0, 1_6, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """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, 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], [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, 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=UpperCamelCase__			,		model_name="""microsoft/xprophetnet-large-wiki100-cased"""			,		revision="""1acad1643ddd54a44df6a1b797ada8373685d90e"""			,		)








import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

a__       =     logging.getLogger()

def _UpperCAmelCase   (	):
							snake_case__	  =       argparse.ArgumentParser()
							parser.add_argument("""-f""" )
							snake_case__	  =       parser.parse_args()
							return args.f



class    _lowerCAmelCase			(		lowercase_      ):



				"""simple docstring"""



				def 					__magic_name__							(      self    :    int):






											'''simple docstring'''







											snake_case__	  =       logging.StreamHandler(sys.stdout)
											logger.addHandler(UpperCamelCase__)



				def 					__magic_name__							(      self    :    Union[str, Any]			,		UpperCamelCase__    :    List[str]):






											'''simple docstring'''







											snake_case__	  =       get_gpu_count()

											if n_gpu > 1:
																		pass
																		# XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
																		# script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
																		# distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
																		# cmd = [sys.executable] + distributed_args + args
																		# execute_subprocess_async(cmd, env=self.get_env())
																		# XXX: test the results - need to save them first into .json file
											else:
																		args.insert(0			,		"""run_glue_deebert.py""")
																		with patch.object(UpperCamelCase__			,		"""argv"""			,		UpperCamelCase__):
																									snake_case__	  =       run_glue_deebert.main()
																									for value in result.values():
																																self.assertGreaterEqual(UpperCamelCase__			,		0.6_66)



				@slow
				@require_torch_non_multi_gpu
				def 					__magic_name__							(      self    :    str):






											'''simple docstring'''







											snake_case__	  =       """
            --model_type roberta
            --model_name_or_path roberta-base
            --task_name MRPC
            --do_train
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --max_seq_length 128
            --per_gpu_eval_batch_size=1
            --per_gpu_train_batch_size=8
            --learning_rate 2e-4
            --num_train_epochs 3
            --overwrite_output_dir
            --seed 42
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --save_steps 0
            --overwrite_cache
            --eval_after_first_stage
            """.split()
											self.run_and_check(UpperCamelCase__)

											snake_case__	  =       """
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --eval_each_highway
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
											self.run_and_check(UpperCamelCase__)

											snake_case__	  =       """
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --early_exit_entropy 0.1
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            """.split()
											self.run_and_check(UpperCamelCase__)
