

import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
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__		      =       get_tests_dir("""fixtures/test_sentencepiece.model""")

@require_sentencepiece
@require_tokenizers
class     a__  (    snake_case							,		unittest.TestCase	):
			"""simple docstring"""







			__lowerCamelCase       				=				ReformerTokenizer
			__lowerCamelCase       				=				ReformerTokenizerFast
			__lowerCamelCase       				=				True
			__lowerCamelCase       				=				False
			__lowerCamelCase       				=				True


			def    UpperCamelCase						(			self				)     ->  int:
							'''simple docstring'''






							super().setUp()

							A__						=	ReformerTokenizer(lowercase					,					keep_accents=lowercase				)
							tokenizer.save_pretrained(self.tmpdirname				)


			def    UpperCamelCase						(			self				)     ->  Tuple:
							'''simple docstring'''






							A__						=	"<s>"
							A__						=	1

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


			def    UpperCamelCase						(			self				)     ->  Tuple:
							'''simple docstring'''






							A__						=	list(self.get_tokenizer().get_vocab().keys()				)

							self.assertEqual(vocab_keys[0]					,					"<unk>"				)
							self.assertEqual(vocab_keys[1]					,					"<s>"				)
							self.assertEqual(vocab_keys[-1]					,					"j"				)
							self.assertEqual(len(lowercase				)					,					1000				)


			def    UpperCamelCase						(			self				)     ->  int:
							'''simple docstring'''






							self.assertEqual(self.get_tokenizer().vocab_size					,					1000				)


			def    UpperCamelCase						(			self				)     ->  Any:
							'''simple docstring'''






							if not self.test_rust_tokenizer:
											return

							A__						=	self.get_tokenizer()
							A__						=	self.get_rust_tokenizer()

							A__						=	"I was born in 92000, and this is falsé."

							A__						=	tokenizer.tokenize(lowercase				)
							A__						=	rust_tokenizer.tokenize(lowercase				)
							self.assertListEqual(lowercase					,					lowercase				)

							A__						=	tokenizer.encode(lowercase					,					add_special_tokens=lowercase				)
							A__						=	rust_tokenizer.encode(lowercase					,					add_special_tokens=lowercase				)
							self.assertListEqual(lowercase					,					lowercase				)

							A__						=	self.get_rust_tokenizer()
							A__						=	tokenizer.encode(lowercase				)
							A__						=	rust_tokenizer.encode(lowercase				)
							self.assertListEqual(lowercase					,					lowercase				)


			def    UpperCamelCase						(			self					,					lowercase=15				)     ->  Any:
							'''simple docstring'''






							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
															A__						=	self.rust_tokenizer_class.from_pretrained(lowercase					,					**lowercase				)

															# Simple input
															A__						=	"This is a simple input"
															A__						=	["This is a simple input 1", "This is a simple input 2"]
															A__						=	("This is a simple input", "This is a pair")
															A__						=	[
															    ("This is a simple input 1", "This is a simple input 2"),
															    ("This is a simple pair 1", "This is a simple pair 2"),
															]

															# Simple input tests
															self.assertRaises(lowercase					,					tokenizer_r.encode					,					lowercase					,					max_length=lowercase					,					padding="max_length"				)

															# Simple input
															self.assertRaises(lowercase					,					tokenizer_r.encode_plus					,					lowercase					,					max_length=lowercase					,					padding="max_length"				)

															# Simple input
															self.assertRaises(
															    lowercase					,					tokenizer_r.batch_encode_plus					,					lowercase					,					max_length=lowercase					,					padding="max_length"					,					)

															# Pair input
															self.assertRaises(lowercase					,					tokenizer_r.encode					,					lowercase					,					max_length=lowercase					,					padding="max_length"				)

															# Pair input
															self.assertRaises(lowercase					,					tokenizer_r.encode_plus					,					lowercase					,					max_length=lowercase					,					padding="max_length"				)

															# Pair input
															self.assertRaises(
															    lowercase					,					tokenizer_r.batch_encode_plus					,					lowercase					,					max_length=lowercase					,					padding="max_length"					,					)


			def    UpperCamelCase						(			self				)     ->  Tuple:
							'''simple docstring'''






							pass


			def    UpperCamelCase						(			self				)     ->  Dict:
							'''simple docstring'''






							A__						=	ReformerTokenizer(lowercase					,					keep_accents=lowercase				)

							A__						=	tokenizer.tokenize("This is a test"				)
							self.assertListEqual(lowercase					,					["▁This", "▁is", "▁a", "▁t", "est"]				)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(lowercase				)					,					[285, 46, 10, 170, 382]					,					)

							A__						=	tokenizer.tokenize("I was born in 92000, and this is falsé."				)
							self.assertListEqual(
							    lowercase					,					[
							        SPIECE_UNDERLINE + "I",
							        SPIECE_UNDERLINE + "was",
							        SPIECE_UNDERLINE + "b",
							        "or",
							        "n",
							        SPIECE_UNDERLINE + "in",
							        SPIECE_UNDERLINE + "",
							        "9",
							        "2",
							        "0",
							        "0",
							        "0",
							        ",",
							        SPIECE_UNDERLINE + "and",
							        SPIECE_UNDERLINE + "this",
							        SPIECE_UNDERLINE + "is",
							        SPIECE_UNDERLINE + "f",
							        "al",
							        "s",
							        "é",
							        ".",
							    ]					,					)
							A__						=	tokenizer.convert_tokens_to_ids(lowercase				)
							self.assertListEqual(
							    lowercase					,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]					,					)

							A__						=	tokenizer.convert_ids_to_tokens(lowercase				)
							self.assertListEqual(
							    lowercase					,					[
							        SPIECE_UNDERLINE + "I",
							        SPIECE_UNDERLINE + "was",
							        SPIECE_UNDERLINE + "b",
							        "or",
							        "n",
							        SPIECE_UNDERLINE + "in",
							        SPIECE_UNDERLINE + "",
							        "<unk>",
							        "2",
							        "0",
							        "0",
							        "0",
							        ",",
							        SPIECE_UNDERLINE + "and",
							        SPIECE_UNDERLINE + "this",
							        SPIECE_UNDERLINE + "is",
							        SPIECE_UNDERLINE + "f",
							        "al",
							        "s",
							        "<unk>",
							        ".",
							    ]					,					)


			@cached_property
			def    UpperCamelCase						(			self				)     ->  List[Any]:
							'''simple docstring'''






							return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment"				)


			@slow
			def    UpperCamelCase						(			self				)     ->  Optional[Any]:
							'''simple docstring'''






							A__						=	"Hello World!"
							A__						=	[126, 32, 262, 152, 38, 72, 287]

							self.assertListEqual(lowercase					,					self.big_tokenizer.encode(lowercase				)				)


			@slow
			def    UpperCamelCase						(			self				)     ->  Union[str, Any]:
							'''simple docstring'''






							A__						=	(
							    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
							    " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
							)
							A__						=	[
							    108,
							    265,
							    24,
							    111,
							    4,
							    258,
							    156,
							    35,
							    28,
							    275,
							    3,
							    259,
							    297,
							    260,
							    84,
							    4,
							    35,
							    110,
							    44,
							    8,
							    259,
							    91,
							    268,
							    21,
							    11,
							    209,
							    274,
							    109,
							    266,
							    277,
							    117,
							    86,
							    93,
							    315,
							    258,
							    278,
							    258,
							    277,
							    258,
							    0,
							    258,
							    288,
							    258,
							    319,
							    258,
							    0,
							    258,
							    0,
							    258,
							    0,
							    258,
							    0,
							    258,
							    287,
							    258,
							    315,
							    258,
							    289,
							    258,
							    278,
							    99,
							    269,
							    266,
							    262,
							    8,
							    259,
							    241,
							    4,
							    217,
							    230,
							    268,
							    266,
							    55,
							    168,
							    106,
							    75,
							    193,
							    266,
							    223,
							    27,
							    49,
							    26,
							    282,
							    25,
							    264,
							    299,
							    19,
							    26,
							    0,
							    258,
							    277,
							    117,
							    86,
							    93,
							    176,
							    183,
							    270,
							    11,
							    262,
							    42,
							    61,
							    265,
							]

							self.assertListEqual(lowercase					,					self.big_tokenizer.encode(lowercase				)				)


			@require_torch
			@slow
			def    UpperCamelCase						(			self				)     ->  Optional[int]:
							'''simple docstring'''






							import torch

							from transformers import ReformerConfig, ReformerModel

							# Build sequence
							A__						=	list(self.big_tokenizer.get_vocab().keys()				)[:10]
							A__						=	" ".join(lowercase				)
							A__						=	self.big_tokenizer.encode_plus(lowercase					,					return_tensors="pt"				)
							A__						=	self.big_tokenizer.batch_encode_plus([sequence, sequence]					,					return_tensors="pt"				)

							A__						=	ReformerConfig()
							# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
							A__						=	encoded_sequence["input_ids"].shape
							A__						=	ReformerModel(lowercase				)

							# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
							assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

							with torch.no_grad():
											model(**lowercase				)
											model(**lowercase				)


			@slow
			def    UpperCamelCase						(			self				)     ->  Union[str, Any]:
							'''simple docstring'''






							A__						=	{"input_ids": [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], "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]]}  # noqa: E501
							# fmt: on

							# This tokenizer does not know some characters like ")".
							# That is the reason why we use very simple texts here.
							# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
							A__						=	[
							    "This is a very simple sentence.",
							    "The quick brown fox jumps over the lazy dog.",
							]

							self.tokenizer_integration_test_util(
							    expected_encoding=lowercase					,					model_name="google/reformer-crime-and-punishment"					,					revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"					,					padding=lowercase					,					sequences=lowercase					,					)



from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass

@dataclass
class __snake_case		:
    _a		:						int
    _a		:						TreeNode | None=				None
    _a		:						TreeNode | None=				None






lowercase  :					Dict						    =							namedtuple("""CoinsDistribResult""", """moves excess""")







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    int:

       if root is None:
              return 0

       # Validation
       def count_nodes(SCREAMING_SNAKE_CASE__				) -> int:
              if node is None:
                     return 0

              return count_nodes(node.left				) + count_nodes(node.right				) + 1

       def count_coins(SCREAMING_SNAKE_CASE__				) -> int:
              if node is None:
                     return 0

              return count_coins(node.left				) + count_coins(node.right				) + node.data

       if count_nodes(SCREAMING_SNAKE_CASE__				) != count_coins(SCREAMING_SNAKE_CASE__				):
              raise ValueError("""The nodes number should be same as the number of coins"""				)

       # Main calculation
       def get_distrib(SCREAMING_SNAKE_CASE__				) -> CoinsDistribResult:

              if node is None:
                     return CoinsDistribResult(0					,	1				)

              lowercase	,			lowercase							:     int       	=      get_distrib(node.left				)
              lowercase	,			lowercase							:     List[Any]       	=      get_distrib(node.right				)

              lowercase							:     Optional[Any]       	=      1 - left_distrib_excess
              lowercase							:     Union[str, Any]       	=      1 - right_distrib_excess

              lowercase							:     List[Any]       	=      (
                  left_distrib_moves
                  + right_distrib_moves
                  + abs(SCREAMING_SNAKE_CASE__				)
                  + abs(SCREAMING_SNAKE_CASE__				)
              )
              lowercase							:     Any       	=      node.data - coins_to_left - coins_to_right

              return CoinsDistribResult(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)

       return get_distrib(SCREAMING_SNAKE_CASE__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()
