


"""simple docstring"""


import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 						_UpperCamelCase						(     UpperCamelCase__ ,unittest.TestCase	):
							'''simple docstring'''







							__UpperCAmelCase		:					Optional[int]          =RobertaTokenizer
							__UpperCAmelCase		:					Dict          =RobertaTokenizerFast
							__UpperCAmelCase		:					List[Any]          =True
							__UpperCAmelCase		:					Union[str, Any]          ={"""cls_token""": """<s>"""}

							def     snake_case       (  self			):
										super().setUp()

										# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
										__lowerCAmelCase       					=    [
										    "l",
										    "o",
										    "w",
										    "e",
										    "r",
										    "s",
										    "t",
										    "i",
										    "d",
										    "n",
										    "\u0120",
										    "\u0120l",
										    "\u0120n",
										    "\u0120lo",
										    "\u0120low",
										    "er",
										    "\u0120lowest",
										    "\u0120newer",
										    "\u0120wider",
										    "<unk>",
										]
										__lowerCAmelCase       					=    dict(zip(__A					,     range(len(__A			)			)			)			)
										__lowerCAmelCase       					=    ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
										__lowerCAmelCase       					=    {"unk_token": "<unk>"}

										__lowerCAmelCase       					=    os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["vocab_file"]			)
										__lowerCAmelCase       					=    os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["merges_file"]			)
										with open(self.vocab_file					,     "w"					,     encoding="utf-8"			) as fp:
													fp.write(json.dumps(__A			) + "\n"			)
										with open(self.merges_file					,     "w"					,     encoding="utf-8"			) as fp:
													fp.write("\n".join(__A			)			)

							def     snake_case       (  self					,     **__a			):
										kwargs.update(self.special_tokens_map			)
										return self.tokenizer_class.from_pretrained(self.tmpdirname					,     **__A			)

							def     snake_case       (  self					,     **__a			):
										kwargs.update(self.special_tokens_map			)
										return RobertaTokenizerFast.from_pretrained(self.tmpdirname					,     **__A			)

							def     snake_case       (  self					,     __a			):
										__lowerCAmelCase       					=    "lower newer"
										__lowerCAmelCase       					=    "lower newer"
										return input_text, output_text

							def     snake_case       (  self			):
										__lowerCAmelCase       					=    self.tokenizer_class(self.vocab_file					,     self.merges_file					,     **self.special_tokens_map			)
										__lowerCAmelCase       					=    "lower newer"
										__lowerCAmelCase       					=    ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
										__lowerCAmelCase       					=    tokenizer.tokenize(__A			)  # , add_prefix_space=True)
										self.assertListEqual(__A					,     __A			)

										__lowerCAmelCase       					=    tokens + [tokenizer.unk_token]
										__lowerCAmelCase       					=    [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(__A			)					,     __A			)

							def     snake_case       (  self			):
										__lowerCAmelCase       					=    self.get_tokenizer()

										self.assertListEqual(tokenizer.encode("Hello world!"					,     add_special_tokens=__A			)					,     [0, 3_14_14, 2_32, 3_28, 2]			)
										self.assertListEqual(
										    tokenizer.encode("Hello world! cécé herlolip 418"					,     add_special_tokens=__A			)					,     [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]					,     )

							@slow
							def     snake_case       (  self			):
										__lowerCAmelCase       					=    self.tokenizer_class.from_pretrained("roberta-base"			)

										__lowerCAmelCase       					=    tokenizer.encode("sequence builders"					,     add_special_tokens=__A			)
										__lowerCAmelCase       					=    tokenizer.encode("multi-sequence build"					,     add_special_tokens=__A			)

										__lowerCAmelCase       					=    tokenizer.encode(
										    "sequence builders"					,     add_special_tokens=__A					,     add_prefix_space=__A			)
										__lowerCAmelCase       					=    tokenizer.encode(
										    "sequence builders"					,     "multi-sequence build"					,     add_special_tokens=__A					,     add_prefix_space=__A			)

										__lowerCAmelCase       					=    tokenizer.build_inputs_with_special_tokens(__A			)
										__lowerCAmelCase       					=    tokenizer.build_inputs_with_special_tokens(__A					,     __A			)

										assert encoded_sentence == encoded_text_from_decode
										assert encoded_pair == encoded_pair_from_decode

							def     snake_case       (  self			):
										__lowerCAmelCase       					=    self.get_tokenizer()

										__lowerCAmelCase       					=    "Encode this sequence."
										__lowerCAmelCase       					=    tokenizer.byte_encoder[" ".encode("utf-8"			)[0]]

										# Testing encoder arguments
										__lowerCAmelCase       					=    tokenizer.encode(__A					,     add_special_tokens=__A					,     add_prefix_space=__A			)
										__lowerCAmelCase       					=    tokenizer.convert_ids_to_tokens(encoded[0]			)[0]
										self.assertNotEqual(__A					,     __A			)

										__lowerCAmelCase       					=    tokenizer.encode(__A					,     add_special_tokens=__A					,     add_prefix_space=__A			)
										__lowerCAmelCase       					=    tokenizer.convert_ids_to_tokens(encoded[0]			)[0]
										self.assertEqual(__A					,     __A			)

										tokenizer.add_special_tokens({"bos_token": "<s>"}			)
										__lowerCAmelCase       					=    tokenizer.encode(__A					,     add_special_tokens=__A			)
										__lowerCAmelCase       					=    tokenizer.convert_ids_to_tokens(encoded[1]			)[0]
										self.assertNotEqual(__A					,     __A			)

										# Testing spaces after special tokens
										__lowerCAmelCase       					=    "<mask>"
										tokenizer.add_special_tokens(
										    {"mask_token": AddedToken(__A					,     lstrip=__A					,     rstrip=__A			)}			)  # mask token has a left space
										__lowerCAmelCase       					=    tokenizer.convert_tokens_to_ids(__A			)

										__lowerCAmelCase       					=    "Encode <mask> sequence"
										__lowerCAmelCase       					=    "Encode <mask>sequence"

										__lowerCAmelCase       					=    tokenizer.encode(__A			)
										__lowerCAmelCase       					=    encoded.index(__A			)
										__lowerCAmelCase       					=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]			)[0]
										self.assertEqual(__A					,     __A			)

										__lowerCAmelCase       					=    tokenizer.encode(__A			)
										__lowerCAmelCase       					=    encoded.index(__A			)
										__lowerCAmelCase       					=    tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]			)[0]
										self.assertNotEqual(__A					,     __A			)

							def     snake_case       (  self			):
										pass

							def     snake_case       (  self			):



										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"			):
																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(__A					,     **__A			)
																__lowerCAmelCase       					=    self.tokenizer_class.from_pretrained(__A					,     **__A			)
																__lowerCAmelCase       					=    "A, <mask> AllenNLP sentence."
																__lowerCAmelCase       					=    tokenizer_r.encode_plus(__A					,     add_special_tokens=__A					,     return_token_type_ids=__A			)
																__lowerCAmelCase       					=    tokenizer_p.encode_plus(__A					,     add_special_tokens=__A					,     return_token_type_ids=__A			)

																# token_type_ids should put 0 everywhere
																self.assertEqual(sum(tokens_r["token_type_ids"]			)					,     sum(tokens_p["token_type_ids"]			)			)

																# attention_mask should put 1 everywhere, so sum over length should be 1
																self.assertEqual(
																    sum(tokens_r["attention_mask"]			) / len(tokens_r["attention_mask"]			)					,     sum(tokens_p["attention_mask"]			) / len(tokens_p["attention_mask"]			)					,     )

																__lowerCAmelCase       					=    tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]			)
																__lowerCAmelCase       					=    tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]			)

																# Rust correctly handles the space before the mask while python doesnt
																self.assertSequenceEqual(tokens_p["input_ids"]					,     [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]			)
																self.assertSequenceEqual(tokens_r["input_ids"]					,     [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]			)

																self.assertSequenceEqual(
																    __A					,     ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]			)
																self.assertSequenceEqual(
																    __A					,     ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]			)

							def     snake_case       (  self			):



										for trim_offsets, add_prefix_space in itertools.product([True, False]					,     repeat=2			):
													__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
													    self.tmpdirname					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)

													__lowerCAmelCase       					=    json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()			)
													__lowerCAmelCase       					=    json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()			)

													self.assertEqual(pre_tokenizer_state["add_prefix_space"]					,     __A			)

													self.assertEqual(post_processor_state["add_prefix_space"]					,     __A			)
													self.assertEqual(post_processor_state["trim_offsets"]					,     __A			)



							def     snake_case       (  self			):



										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"			):
																__lowerCAmelCase       					=    "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																__lowerCAmelCase       					=    f"{text_of_1_token} {text_of_1_token}"

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (0, len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (len(__A			) + 1, len(__A			) + 1 + len(__A			))					,     )

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (0, len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (len(__A			) + 1, len(__A			) + 1 + len(__A			))					,     )

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (0, len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (len(__A			), len(__A			) + 1 + len(__A			))					,     )

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (0, len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (len(__A			), len(__A			) + 1 + len(__A			))					,     )

																__lowerCAmelCase       					=    f" {text}"

																# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																# )
																# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																# self.assertEqual(
																#     encoding.offset_mapping[1],
																#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																# )

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (1, 1 + len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (1 + len(__A			) + 1, 1 + len(__A			) + 1 + len(__A			))					,     )

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (0, 1 + len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (1 + len(__A			), 1 + len(__A			) + 1 + len(__A			))					,     )

																__lowerCAmelCase       					=    self.rust_tokenizer_class.from_pretrained(
																    __A					,     use_fast=__A					,     add_prefix_space=__A					,     trim_offsets=__A			)
																__lowerCAmelCase       					=    tokenizer_r(__A					,     return_offsets_mapping=__A					,     add_special_tokens=__A			)
																self.assertEqual(encoding.offset_mapping[0]					,     (0, 1 + len(__A			))			)
																self.assertEqual(
																    encoding.offset_mapping[1]					,     (1 + len(__A			), 1 + len(__A			) + 1 + len(__A			))					,     )








"""simple docstring"""


def _lowerCamelCase			(	_UpperCamelCase					,				_UpperCamelCase   ):

			'''simple docstring'''




			__lowerCAmelCase       					=    len(_UpperCamelCase   )
			print("The following activities are selected:"   )

			# The first activity is always selected
			__lowerCAmelCase       					=    0
			print(_UpperCamelCase					,				end=","   )

			# Consider rest of the activities
			for j in range(_UpperCamelCase   ):
						# If this activity has start time greater than
						# or equal to the finish time of previously
						# selected activity, then select it
						if start[j] >= finish[i]:
									print(_UpperCamelCase					,				end=","   )
									__lowerCAmelCase       					=    j


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	A  :     Dict    					=    [1, 3, 0, 5, 8, 5]
	A  :     int    					=    [2, 4, 6, 7, 9, 9]
	print_max_activities(start, finish)




