import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase					:	Any       =  get_tests_dir('''fixtures/test_sentencepiece_no_bos.model''')






@require_sentencepiece
@require_tokenizers
class 		a__						(					A__    ,		unittest.TestCase					):
					A	       =							PegasusTokenizer
					A	       =							PegasusTokenizerFast
					A	       =							True
					A	       =							True

					def 				__UpperCamelCase   (    self      :       Union[str, Any]    ):







							"""simple docstring"""






							super().setUp()

							# We have a SentencePiece fixture for testing
							SCREAMING_SNAKE_CASE_  :		Any				      =    PegasusTokenizer(_A    )
							tokenizer.save_pretrained(self.tmpdirname    )

					@cached_property
					def 				__UpperCamelCase   (    self      :       List[str]    ):







							"""simple docstring"""






							return PegasusTokenizer.from_pretrained("google/pegasus-large"    )

					def 				__UpperCamelCase   (    self      :       Union[str, Any],**_A      :       Optional[int]    ):







							"""simple docstring"""






							return PegasusTokenizer.from_pretrained(self.tmpdirname,**_A    )

					def 				__UpperCamelCase   (    self      :       List[Any],_A      :       Union[str, Any]    ):







							"""simple docstring"""






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

					def 				__UpperCamelCase   (    self      :       Tuple    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		int				      =    "</s>"
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    1

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

					def 				__UpperCamelCase   (    self      :       List[Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    list(self.get_tokenizer().get_vocab().keys()    )

							self.assertEqual(vocab_keys[0],"<pad>"    )
							self.assertEqual(vocab_keys[1],"</s>"    )
							self.assertEqual(vocab_keys[-1],"v"    )
							self.assertEqual(len(_A    ),1103    )

					def 				__UpperCamelCase   (    self      :       int    ):







							"""simple docstring"""






							self.assertEqual(self.get_tokenizer().vocab_size,1103    )

					def 				__UpperCamelCase   (    self      :       Tuple    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Tuple				      =    self.rust_tokenizer_class.from_pretrained(self.tmpdirname    )
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    self.tokenizer_class.from_pretrained(self.tmpdirname    )
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    (
							    "Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"
							    " </s> <pad> <pad> <pad>"
							)
							SCREAMING_SNAKE_CASE_  :		List[str]				      =    rust_tokenizer([raw_input_str],return_tensors=_A,add_special_tokens=_A    ).input_ids[0]
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    py_tokenizer([raw_input_str],return_tensors=_A,add_special_tokens=_A    ).input_ids[0]
							self.assertListEqual(_A,_A    )

					def 				__UpperCamelCase   (    self      :       int    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Any				      =    self._large_tokenizer
							# <mask_1> masks whole sentence while <mask_2> masks single word
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    "<mask_1> To ensure a <mask_2> flow of bank resolutions."
							SCREAMING_SNAKE_CASE_  :		List[str]				      =    [2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
							SCREAMING_SNAKE_CASE_  :		Dict				      =    tokenizer([raw_input_str],return_tensors=_A    ).input_ids[0]
							self.assertListEqual(_A,_A    )

					def 				__UpperCamelCase   (    self      :       str    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    self._large_tokenizer
							# The tracebacks for the following asserts are **better** without messages or self.assertEqual
							assert tokenizer.vocab_size == 9_6103
							assert tokenizer.pad_token_id == 0
							assert tokenizer.eos_token_id == 1
							assert tokenizer.offset == 103
							assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
							assert tokenizer.unk_token == "<unk>"
							assert tokenizer.model_max_length == 1024
							SCREAMING_SNAKE_CASE_  :		str				      =    "To ensure a smooth flow of bank resolutions."
							SCREAMING_SNAKE_CASE_  :		Dict				      =    [413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    tokenizer([raw_input_str],return_tensors=_A    ).input_ids[0]
							self.assertListEqual(_A,_A    )
							assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]    ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]

					@require_torch
					def 				__UpperCamelCase   (    self      :       List[Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]				      =    ["This is going to be way too long." * 150, "short example"]
							SCREAMING_SNAKE_CASE_  :		Any				      =    ["not super long but more than 5 tokens", "tiny"]
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    self._large_tokenizer(_A,padding=_A,truncation=_A,return_tensors="pt"    )
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    self._large_tokenizer(
							    text_target=_A,max_length=5,padding=_A,truncation=_A,return_tensors="pt"    )

							assert batch.input_ids.shape == (2, 1024)
							assert batch.attention_mask.shape == (2, 1024)
							assert targets["input_ids"].shape == (2, 5)
							assert len(_A    ) == 2  # input_ids, attention_mask.






					@slow
					def 				__UpperCamelCase   (    self      :       str    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Tuple				      =    {"input_ids": [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 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], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 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]], "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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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="google/bigbird-pegasus-large-arxiv",revision="ba85d0851d708441f91440d509690f1ab6353415",)







@require_sentencepiece
@require_tokenizers
class 		a__						(					A__    ,		unittest.TestCase					):
					A	       =							PegasusTokenizer
					A	       =							PegasusTokenizerFast
					A	       =							True
					A	       =							True

					def 				__UpperCamelCase   (    self      :       Union[str, Any]    ):







							"""simple docstring"""






							super().setUp()

							# We have a SentencePiece fixture for testing
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    PegasusTokenizer(_A,offset=0,mask_token_sent=_A,mask_token="[MASK]"    )
							tokenizer.save_pretrained(self.tmpdirname    )

					@cached_property
					def 				__UpperCamelCase   (    self      :       List[str]    ):







							"""simple docstring"""






							return PegasusTokenizer.from_pretrained("google/bigbird-pegasus-large-arxiv"    )

					def 				__UpperCamelCase   (    self      :       List[str],**_A      :       List[str]    ):







							"""simple docstring"""






							return PegasusTokenizer.from_pretrained(self.tmpdirname,**_A    )

					def 				__UpperCamelCase   (    self      :       List[str],_A      :       str    ):







							"""simple docstring"""






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

					def 				__UpperCamelCase   (    self      :       Dict    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    self.rust_tokenizer_class.from_pretrained(self.tmpdirname    )
							SCREAMING_SNAKE_CASE_  :		Dict				      =    self.tokenizer_class.from_pretrained(self.tmpdirname    )
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    (
							    "Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"
							    " <pad> <pad> <pad>"
							)
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    rust_tokenizer([raw_input_str],return_tensors=_A,add_special_tokens=_A    ).input_ids[0]
							SCREAMING_SNAKE_CASE_  :		Dict				      =    py_tokenizer([raw_input_str],return_tensors=_A,add_special_tokens=_A    ).input_ids[0]
							self.assertListEqual(_A,_A    )

					@require_torch
					def 				__UpperCamelCase   (    self      :       List[Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Dict				      =    ["This is going to be way too long." * 1000, "short example"]
							SCREAMING_SNAKE_CASE_  :		Dict				      =    ["not super long but more than 5 tokens", "tiny"]
							SCREAMING_SNAKE_CASE_  :		int				      =    self._large_tokenizer(_A,padding=_A,truncation=_A,return_tensors="pt"    )
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    self._large_tokenizer(
							    text_target=_A,max_length=5,padding=_A,truncation=_A,return_tensors="pt"    )

							assert batch.input_ids.shape == (2, 4096)
							assert batch.attention_mask.shape == (2, 4096)
							assert targets["input_ids"].shape == (2, 5)
							assert len(_A    ) == 2  # input_ids, attention_mask.






					def 				__UpperCamelCase   (    self      :       Tuple    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    (
							    "This is an example string that is used to test the original TF implementation against the HF"
							    " implementation"
							)

							SCREAMING_SNAKE_CASE_  :		Any				      =    self._large_tokenizer(_A    ).input_ids

							self.assertListEqual(
							    _A,[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1],)

# Copyright 2021 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 argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser




def       _snake_case	(   ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		int				      =    ArgumentParser("Accelerate CLI tool"   , usage="accelerate <command> [<args>]"   , allow_abbrev=lowerCAmelCase	)
		SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    parser.add_subparsers(help="accelerate command helpers"	)

		# Register commands
		get_config_parser(subparsers=lowerCAmelCase	)
		env_command_parser(subparsers=lowerCAmelCase	)
		launch_command_parser(subparsers=lowerCAmelCase	)
		tpu_command_parser(subparsers=lowerCAmelCase	)
		test_command_parser(subparsers=lowerCAmelCase	)

		# Let's go
		SCREAMING_SNAKE_CASE_  :		Dict				      =    parser.parse_args()

		if not hasattr(lowerCAmelCase   , "func"	):
				parser.print_help()
				exit(1	)

		# Run
		args.func(lowerCAmelCase	)


if __name__ == "__main__":
		main()
