





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        __SCREAMING_SNAKE_CASE					(     _a   ,		unittest.TestCase       ):
							snake_case     :      Tuple						     =       MvpTokenizer
							snake_case     :      Optional[Any]						     =       MvpTokenizerFast
							snake_case     :      Tuple						     =       True
							snake_case     :      List[str]						     =       filter_roberta_detectors






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

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






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														kwargs.update(self.special_tokens_map  )
														return self.tokenizer_class.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														kwargs.update(self.special_tokens_map  )
														return self.rust_tokenizer_class.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														return "lower newer", "lower newer"






							@cached_property
							def 				_lowerCamelCase		(						self  ):
														return MvpTokenizer.from_pretrained("""RUCAIBox/mvp"""  )






							@cached_property
							def 				_lowerCamelCase		(						self  ):
														return MvpTokenizerFast.from_pretrained("""RUCAIBox/mvp"""  )






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
														UpperCamelCase__				     =			[0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

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

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






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
														for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																					UpperCamelCase__				     =			tokenizer(__lowerCAmelCase  , padding=__lowerCAmelCase  , return_tensors="""pt"""  )
																					# check if input_ids are returned and no labels
																					self.assertIn("""input_ids"""  , __lowerCAmelCase  )
																					self.assertIn("""attention_mask"""  , __lowerCAmelCase  )
																					self.assertNotIn("""labels"""  , __lowerCAmelCase  )
																					self.assertNotIn("""decoder_attention_mask"""  , __lowerCAmelCase  )






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			[
														    """Summary of the text.""",
														    """Another summary.""",
														]
														for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																					UpperCamelCase__				     =			tokenizer(text_target=__lowerCAmelCase  , max_length=32  , padding="""max_length"""  , return_tensors="""pt"""  )
																					self.assertEqual(32  , targets["""input_ids"""].shape[1]  )






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																					UpperCamelCase__				     =			tokenizer(
																					    ["""I am a small frog""" * 1024, """I am a small frog"""]  , padding=__lowerCAmelCase  , truncation=__lowerCAmelCase  , return_tensors="""pt"""  )
																					self.assertIsInstance(__lowerCAmelCase  , __lowerCAmelCase  )
																					self.assertEqual(batch.input_ids.shape  , (2, 1024)  )






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			["""A long paragraph for summarization."""]
														UpperCamelCase__				     =			[
														    """Summary of the text.""",
														]
														for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																					UpperCamelCase__				     =			tokenizer(__lowerCAmelCase  , text_target=__lowerCAmelCase  , return_tensors="""pt"""  )
																					UpperCamelCase__				     =			inputs["""input_ids"""]
																					UpperCamelCase__				     =			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 				_lowerCamelCase		(						self  ):
														pass







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

																												# 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"""]  )  , )

																												UpperCamelCase__				     =			tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]  )
																												UpperCamelCase__				     =			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(
																												    __lowerCAmelCase  , ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]  )
																												self.assertSequenceEqual(
																												    __lowerCAmelCase  , ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]  )











from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any

@dataclass
class        __SCREAMING_SNAKE_CASE					:
							snake_case     :      int
							snake_case     :      Node | None						     =       None
							snake_case     :      Node | None						     =       None






def     _UpperCamelCase     ():






							"""simple docstring"""





							UpperCamelCase__				     =			Node(1       )
							UpperCamelCase__				     =			Node(2       )
							UpperCamelCase__				     =			Node(3       )
							UpperCamelCase__				     =			Node(4       )
							UpperCamelCase__				     =			Node(5       )
							return tree





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return [root.data, *preorder(root.left       ), *preorder(root.right       )] if root else []





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return postorder(root.left       ) + postorder(root.right       ) + [root.data] if root else []





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return [*inorder(root.left       ), root.data, *inorder(root.right       )] if root else []





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return (max(height(root.left       )   ,			height(root.right       )       ) + 1) if root else 0





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							if root is None:
														return output

							UpperCamelCase__				     =			deque([root]       )

							while process_queue:
														UpperCamelCase__				     =			process_queue.popleft()
														output.append(node.data       )

														if node.left:
																					process_queue.append(node.left       )
														if node.right:
																					process_queue.append(node.right       )
							return output





def     _UpperCamelCase     (a__   :Node | None   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							def populate_output(a__   :Node | None   ,			a__   :int       ) -> None:
														if not root:
																					return
														if level == 1:
																					output.append(root.data       )
														elif level > 1:
																					populate_output(root.left   ,			level - 1       )
																					populate_output(root.right   ,			level - 1       )

							populate_output(a__   ,			a__       )
							return output





def     _UpperCamelCase     (a__   :Node | None   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							def populate_output(a__   :Node | None   ,			a__   :int       ) -> None:
														if root is None:
																					return
														if level == 1:
																					output.append(root.data       )
														elif level > 1:
																					populate_output(root.right   ,			level - 1       )
																					populate_output(root.left   ,			level - 1       )

							populate_output(a__   ,			a__       )
							return output





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							if root is None:
														return []

							UpperCamelCase__				     =			[]

							UpperCamelCase__				     =			0
							UpperCamelCase__				     =			height(a__       )

							for h in range(1   ,			height_tree + 1       ):
														if not flag:
																					output.append(get_nodes_from_left_to_right(a__   ,			a__       )       )
																					UpperCamelCase__				     =			1
														else:
																					output.append(get_nodes_from_right_to_left(a__   ,			a__       )       )
																					UpperCamelCase__				     =			0

							return output





def     _UpperCamelCase     ():  # Main function for testing.






							"""simple docstring"""





							UpperCamelCase__				     =			make_tree()
							print(f"""In-order Traversal: {inorder(a__       )}"""       )
							print(f"""Pre-order Traversal: {preorder(a__       )}"""       )
							print(f"""Post-order Traversal: {postorder(a__       )}"""   ,			"""\n"""       )

							print(f"""Height of Tree: {height(a__       )}"""   ,			"""\n"""       )

							print("""Complete Level Order Traversal: """       )
							print(level_order(a__       )   ,			"""\n"""       )

							print("""Level-wise order Traversal: """       )

							for level in range(1   ,			height(a__       ) + 1       ):
														print(f"""Level {level}:"""   ,			get_nodes_from_left_to_right(a__   ,			level=a__       )       )

							print("""\nZigZag order Traversal: """       )
							print(zigzag(a__       )       )


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()




