


"""simple docstring"""







import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors




@require_tokenizers
class 			UpperCamelCase_     (			UpperCamelCase      ,  unittest.TestCase):

	"""simple docstring"""





	snake_case__    :  List[Any]    =      MvpTokenizer
	snake_case__    :  Any    =      MvpTokenizerFast
	snake_case__    :  List[Any]    =      True
	snake_case__    :  Tuple    =      filter_roberta_detectors




	def   UpperCAmelCase_				(			self      :    Union[str, Any]       )	->     Any:
						super().setUp()
						__SCREAMING_SNAKE_CASE						       =    [
						    "l",
						    "o",
						    "w",
						    "e",
						    "r",
						    "s",
						    "t",
						    "i",
						    "d",
						    "n",
						    "\u0120",
						    "\u0120l",
						    "\u0120n",
						    "\u0120lo",
						    "\u0120low",
						    "er",
						    "\u0120lowest",
						    "\u0120newer",
						    "\u0120wider",
						    "<unk>",
						]
						__SCREAMING_SNAKE_CASE						       =    dict(zip(UpperCAmelCase__      ,      range(len(UpperCAmelCase__       )       )       )       )
						__SCREAMING_SNAKE_CASE						       =    ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
						__SCREAMING_SNAKE_CASE						       =    {"unk_token": "<unk>"}

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




	def   UpperCAmelCase_				(			self      :    List[Any]      ,      **UpperCAmelCase__      :    List[Any]       )	->     int:
						kwargs.update(self.special_tokens_map       )
						return self.tokenizer_class.from_pretrained(self.tmpdirname      ,      **UpperCAmelCase__       )




	def   UpperCAmelCase_				(			self      :    Union[str, Any]      ,      **UpperCAmelCase__      :    Tuple       )	->     Tuple:
						kwargs.update(self.special_tokens_map       )
						return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,      **UpperCAmelCase__       )




	def   UpperCAmelCase_				(			self      :    Tuple      ,      UpperCAmelCase__      :    Optional[int]       )	->     Union[str, Any]:
						return "lower newer", "lower newer"




	@cached_property
	def   UpperCAmelCase_				(			self      :    Union[str, Any]       )	->     str:
						return MvpTokenizer.from_pretrained("RUCAIBox/mvp"       )




	@cached_property
	def   UpperCAmelCase_				(			self      :    List[Any]       )	->     str:
						return MvpTokenizerFast.from_pretrained("RUCAIBox/mvp"       )




	@require_torch
	def   UpperCAmelCase_				(			self      :    Dict       )	->     Any:
						__SCREAMING_SNAKE_CASE						       =    ["A long paragraph for summarization.", "Another paragraph for summarization."]
						__SCREAMING_SNAKE_CASE						       =    [0, 2_5_0, 2_5_1, 1_7_8_1_8, 1_3, 3_9_1_8_6, 1_9_3_8, 4, 2]

						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
											__SCREAMING_SNAKE_CASE						       =    tokenizer(UpperCAmelCase__      ,      max_length=len(UpperCAmelCase__       )      ,      padding=UpperCAmelCase__      ,      return_tensors="pt"       )
											self.assertIsInstance(UpperCAmelCase__      ,      UpperCAmelCase__       )

											self.assertEqual((2, 9)      ,      batch.input_ids.shape       )
											self.assertEqual((2, 9)      ,      batch.attention_mask.shape       )
											__SCREAMING_SNAKE_CASE						       =    batch.input_ids.tolist()[0]
											self.assertListEqual(UpperCAmelCase__      ,      UpperCAmelCase__       )
											# Test that special tokens are reset




	@require_torch
	def   UpperCAmelCase_				(			self      :    Tuple       )	->     Optional[int]:
						__SCREAMING_SNAKE_CASE						       =    ["A long paragraph for summarization.", "Another paragraph for summarization."]
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
											__SCREAMING_SNAKE_CASE						       =    tokenizer(UpperCAmelCase__      ,      padding=UpperCAmelCase__      ,      return_tensors="pt"       )
											# check if input_ids are returned and no labels
											self.assertIn("input_ids"      ,      UpperCAmelCase__       )
											self.assertIn("attention_mask"      ,      UpperCAmelCase__       )
											self.assertNotIn("labels"      ,      UpperCAmelCase__       )
											self.assertNotIn("decoder_attention_mask"      ,      UpperCAmelCase__       )




	@require_torch
	def   UpperCAmelCase_				(			self      :    Optional[int]       )	->     List[Any]:
						__SCREAMING_SNAKE_CASE						       =    [
						    "Summary of the text.",
						    "Another summary.",
						]
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
											__SCREAMING_SNAKE_CASE						       =    tokenizer(text_target=UpperCAmelCase__      ,      max_length=3_2      ,      padding="max_length"      ,      return_tensors="pt"       )
											self.assertEqual(3_2      ,      targets["input_ids"].shape[1]       )




	@require_torch
	def   UpperCAmelCase_				(			self      :    Any       )	->     Optional[int]:
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
											__SCREAMING_SNAKE_CASE						       =    tokenizer(
											    ["I am a small frog" * 1_0_2_4, "I am a small frog"]      ,      padding=UpperCAmelCase__      ,      truncation=UpperCAmelCase__      ,      return_tensors="pt"       )
											self.assertIsInstance(UpperCAmelCase__      ,      UpperCAmelCase__       )
											self.assertEqual(batch.input_ids.shape      ,      (2, 1_0_2_4)       )




	@require_torch
	def   UpperCAmelCase_				(			self      :    str       )	->     int:
						__SCREAMING_SNAKE_CASE						       =    ["A long paragraph for summarization."]
						__SCREAMING_SNAKE_CASE						       =    [
						    "Summary of the text.",
						]
						for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
											__SCREAMING_SNAKE_CASE						       =    tokenizer(UpperCAmelCase__      ,      text_target=UpperCAmelCase__      ,      return_tensors="pt"       )
											__SCREAMING_SNAKE_CASE						       =    inputs["input_ids"]
											__SCREAMING_SNAKE_CASE						       =    inputs["labels"]
											self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()       )
											self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()       )
											self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()       )
											self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()       )




	def   UpperCAmelCase_				(			self      :    List[Any]       )	->     Optional[int]:
						pass




	def   UpperCAmelCase_				(			self      :    Tuple       )	->     Union[str, Any]:
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
																__SCREAMING_SNAKE_CASE						       =    self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__      ,      **UpperCAmelCase__       )
																__SCREAMING_SNAKE_CASE						       =    self.tokenizer_class.from_pretrained(UpperCAmelCase__      ,      **UpperCAmelCase__       )
																__SCREAMING_SNAKE_CASE						       =    "A, <mask> AllenNLP sentence."
																__SCREAMING_SNAKE_CASE						       =    tokenizer_r.encode_plus(UpperCAmelCase__      ,      add_special_tokens=UpperCAmelCase__      ,      return_token_type_ids=UpperCAmelCase__       )
																__SCREAMING_SNAKE_CASE						       =    tokenizer_p.encode_plus(UpperCAmelCase__      ,      add_special_tokens=UpperCAmelCase__      ,      return_token_type_ids=UpperCAmelCase__       )

																# 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"]       )      ,      )

																__SCREAMING_SNAKE_CASE						       =    tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]       )
																__SCREAMING_SNAKE_CASE						       =    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_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]       )
																self.assertSequenceEqual(tokens_r["input_ids"]      ,      [0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]       )

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




"""simple docstring"""







def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					if digit_amount > 0:
										return round(number - int(lowerCAmelCase_       )  ,						lowerCAmelCase_       )
					return number - int(lowerCAmelCase_       )


if __name__ == "__main__":
		print(decimal_isolate(1.53, 0))
		print(decimal_isolate(35.3_45, 1))
		print(decimal_isolate(35.3_45, 2))
		print(decimal_isolate(35.3_45, 3))
		print(decimal_isolate(-14.7_89, 3))
		print(decimal_isolate(0, 2))
		print(decimal_isolate(-14.1_23, 1))
		print(decimal_isolate(-14.1_23, 2))
		print(decimal_isolate(-14.1_23, 3))
