


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 					lowerCAmelCase_ (       _a			,unittest.TestCase):
						lowerCamelCase_         =     MvpTokenizer
						lowerCamelCase_         =     MvpTokenizerFast
						lowerCamelCase_         =     True
						lowerCamelCase_         =     filter_roberta_detectors




						def  _snake_case					(	self						:   Any						)      ->Tuple:






									"""simple docstring"""






									super().setUp()
									a__ :Optional[Any]						  =    [
									    "l",
									    "o",
									    "w",
									    "e",
									    "r",
									    "s",
									    "t",
									    "i",
									    "d",
									    "n",
									    "\u0120",
									    "\u0120l",
									    "\u0120n",
									    "\u0120lo",
									    "\u0120low",
									    "er",
									    "\u0120lowest",
									    "\u0120newer",
									    "\u0120wider",
									    "<unk>",
									]
									a__ :List[Any]						  =    dict(zip(__A   ,     range(len(__A						)						)						)						)
									a__ :Dict						  =    ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
									a__ :Optional[Any]						  =    {"unk_token": "<unk>"}

									a__ :List[str]						  =    os.path.join(self.tmpdirname   ,     VOCAB_FILES_NAMES["vocab_file"]						)
									a__ :List[str]						  =    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						:   str   ,     **__A						:   Optional[int]						)      ->Union[str, Any]:






									"""simple docstring"""






									kwargs.update(self.special_tokens_map						)
									return self.tokenizer_class.from_pretrained(self.tmpdirname   ,     **__A						)




						def  _snake_case					(	self						:   Optional[Any]   ,     **__A						:   Optional[Any]						)      ->Any:






									"""simple docstring"""






									kwargs.update(self.special_tokens_map						)
									return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,     **__A						)




						def  _snake_case					(	self						:   Any   ,     __A						:   Optional[int]						)      ->Tuple:






									"""simple docstring"""






									return "lower newer", "lower newer"




						@cached_property
						def  _snake_case					(	self						:   int						)      ->List[str]:






									"""simple docstring"""






									return MvpTokenizer.from_pretrained("RUCAIBox/mvp"						)




						@cached_property
						def  _snake_case					(	self						:   List[Any]						)      ->List[str]:






									"""simple docstring"""






									return MvpTokenizerFast.from_pretrained("RUCAIBox/mvp"						)




						@require_torch
						def  _snake_case					(	self						:   List[str]						)      ->str:






									"""simple docstring"""






									a__ :Optional[int]						  =    ["A long paragraph for summarization.", "Another paragraph for summarization."]
									a__ :Any						  =    [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

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

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




						@require_torch
						def  _snake_case					(	self						:   Tuple						)      ->Dict:






									"""simple docstring"""






									a__ :str						  =    ["A long paragraph for summarization.", "Another paragraph for summarization."]
									for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												a__ :int						  =    tokenizer(__A   ,     padding=__A   ,     return_tensors="pt"						)
												# check if input_ids are returned and no labels
												self.assertIn("input_ids"   ,     __A						)
												self.assertIn("attention_mask"   ,     __A						)
												self.assertNotIn("labels"   ,     __A						)
												self.assertNotIn("decoder_attention_mask"   ,     __A						)




						@require_torch
						def  _snake_case					(	self						:   str						)      ->Any:






									"""simple docstring"""






									a__ :List[Any]						  =    [
									    "Summary of the text.",
									    "Another summary.",
									]
									for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												a__ :Dict						  =    tokenizer(text_target=__A   ,     max_length=32   ,     padding="max_length"   ,     return_tensors="pt"						)
												self.assertEqual(32   ,     targets["input_ids"].shape[1]						)




						@require_torch
						def  _snake_case					(	self						:   List[Any]						)      ->Union[str, Any]:






									"""simple docstring"""






									for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												a__ :Union[str, Any]						  =    tokenizer(
												    ["I am a small frog" * 1024, "I am a small frog"]   ,     padding=__A   ,     truncation=__A   ,     return_tensors="pt"						)
												self.assertIsInstance(__A   ,     __A						)
												self.assertEqual(batch.input_ids.shape   ,     (2, 1024)						)




						@require_torch
						def  _snake_case					(	self						:   Any						)      ->Optional[int]:






									"""simple docstring"""






									a__ :List[Any]						  =    ["A long paragraph for summarization."]
									a__ :Union[str, Any]						  =    [
									    "Summary of the text.",
									]
									for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												a__ :str						  =    tokenizer(__A   ,     text_target=__A   ,     return_tensors="pt"						)
												a__ :int						  =    inputs["input_ids"]
												a__ :Any						  =    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  _snake_case					(	self						:   List[str]						)      ->Optional[Any]:






									"""simple docstring"""






									pass






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






									"""simple docstring"""






									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
															a__ :List[str]						  =    self.rust_tokenizer_class.from_pretrained(__A   ,     **__A						)
															a__ :Optional[Any]						  =    self.tokenizer_class.from_pretrained(__A   ,     **__A						)
															a__ :str						  =    "A, <mask> AllenNLP sentence."
															a__ :int						  =    tokenizer_r.encode_plus(__A   ,     add_special_tokens=__A   ,     return_token_type_ids=__A						)
															a__ :Union[str, Any]						  =    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"]						)   ,     )

															a__ :List[str]						  =    tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]						)
															a__ :Tuple						  =    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, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]						)
															self.assertSequenceEqual(tokens_r["input_ids"]   ,     [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]						)

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






class 					lowerCAmelCase_ :




						def __init__(	self						:   Optional[int]						)      ->Optional[Any]:






									"""simple docstring"""






									a__ :Tuple						  =    {}




						def  _snake_case					(	self						:   Tuple						)      ->None:






									"""simple docstring"""






									print(self.vertex						)
									for i in self.vertex:
												print(__A   ,     " -> "   ,     " -> ".join([str(__A						) for j in self.vertex[i]]						)						)




						def  _snake_case					(	self						:   Optional[int]   ,     __A						:   int   ,     __A						:   int						)      ->None:






									"""simple docstring"""






									if from_vertex in self.vertex:
												self.vertex[from_vertex].append(__A						)
									else:
												# else make a new vertex
												a__ :Any						  =    [to_vertex]




						def  _snake_case					(	self						:   Optional[int]						)      ->None:






									"""simple docstring"""






									a__ :List[Any]						  =    [False] * len(self.vertex						)

									# call the recursive helper function
									for i in range(len(self.vertex						)						):
												if not visited[i]:
															self.dfs_recursive(__A   ,     __A						)






						def  _snake_case					(	self						:   Union[str, Any]   ,     __A						:   int   ,     __A						:   list						)      ->None:






									"""simple docstring"""






									a__ :Dict						  =    True

									print(__A   ,     end=" "						)

									# Recur for all the vertices that are adjacent to this node
									for i in self.vertex:
												if not visited[i]:
															self.dfs_recursive(__A   ,     __A						)


if __name__ == "__main__":
		snake_case__			 =						Graph()
		g.add_edge(0, 1)
		g.add_edge(0, 2)
		g.add_edge(1, 2)
		g.add_edge(2, 0)
		g.add_edge(2, 3)
		g.add_edge(3, 3)

		g.print_graph()
		print('''DFS:''')
		g.dfs()

		# OUTPUT:
		# 0  ->  1 -> 2
		# 1  ->  2
		# 2  ->  0 -> 3
		# 3  ->  3
		# DFS:
		#  0 1 2 3


