
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


__magic_name__            =  get_tests_dir('''fixtures/test_sentencepiece.model''')




@require_sentencepiece
@require_tokenizers
class 					_SCREAMING_SNAKE_CASE  (      __UpperCamelCase       ,					unittest.TestCase ):
      _A						:		Optional[Any]    	=     ReformerTokenizer
      _A						:		str    	=     ReformerTokenizerFast
      _A						:		List[str]    	=     True
      _A						:		Tuple    	=     False
      _A						:		str    	=     True
      def A_			(			self ):
          super().setUp()

          snake_case__						=				ReformerTokenizer(lowerCamelCase		,	keep_accents=lowerCamelCase )
          tokenizer.save_pretrained(self.tmpdirname )
      def A_			(			self ):
          snake_case__						=				"<s>"
          snake_case__						=				1

          self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase )		,	lowerCamelCase )
          self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase )		,	lowerCamelCase )
      def A_			(			self ):
          snake_case__						=				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(lowerCamelCase )		,	10_00 )
      def A_			(			self ):
          self.assertEqual(self.get_tokenizer().vocab_size		,	10_00 )
      def A_			(			self ):
          if not self.test_rust_tokenizer:
              return

          snake_case__						=				self.get_tokenizer()
          snake_case__						=				self.get_rust_tokenizer()

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

          snake_case__						=				tokenizer.tokenize(lowerCamelCase )
          snake_case__						=				rust_tokenizer.tokenize(lowerCamelCase )
          self.assertListEqual(lowerCamelCase		,	lowerCamelCase )

          snake_case__						=				tokenizer.encode(lowerCamelCase		,	add_special_tokens=lowerCamelCase )
          snake_case__						=				rust_tokenizer.encode(lowerCamelCase		,	add_special_tokens=lowerCamelCase )
          self.assertListEqual(lowerCamelCase		,	lowerCamelCase )

          snake_case__						=				self.get_rust_tokenizer()
          snake_case__						=				tokenizer.encode(lowerCamelCase )
          snake_case__						=				rust_tokenizer.encode(lowerCamelCase )
          self.assertListEqual(lowerCamelCase		,	lowerCamelCase )
      def A_			(			self		,	lowerCamelCase=15 ):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
                  snake_case__						=				self.rust_tokenizer_class.from_pretrained(lowerCamelCase		,	**lowerCamelCase )

                  # Simple input
                  snake_case__						=				"This is a simple input"
                  snake_case__						=				["This is a simple input 1", "This is a simple input 2"]
                  snake_case__						=				("This is a simple input", "This is a pair")
                  snake_case__						=				[
                      ("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(lowerCamelCase		,	tokenizer_r.encode		,	lowerCamelCase		,	max_length=lowerCamelCase		,	padding="max_length" )

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

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

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

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

                  # Pair input
                  self.assertRaises(
                      lowerCamelCase		,	tokenizer_r.batch_encode_plus		,	lowerCamelCase		,	max_length=lowerCamelCase		,	padding="max_length"		,	)
      def A_			(			self ):
          pass
      def A_			(			self ):
          snake_case__						=				ReformerTokenizer(lowerCamelCase		,	keep_accents=lowerCamelCase )

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

          self.assertListEqual(
              tokenizer.convert_tokens_to_ids(lowerCamelCase )		,	[2_85, 46, 10, 1_70, 3_82]		,	)

          snake_case__						=				tokenizer.tokenize("I was born in 92000, and this is falsé." )
          self.assertListEqual(
              lowerCamelCase		,	[
                  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",
                  ".",
              ]		,	)
          snake_case__						=				tokenizer.convert_tokens_to_ids(lowerCamelCase )
          self.assertListEqual(
              lowerCamelCase		,	[8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]		,	)

          snake_case__						=				tokenizer.convert_ids_to_tokens(lowerCamelCase )
          self.assertListEqual(
              lowerCamelCase		,	[
                  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 A_			(			self ):
          return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment" )
      @slow
      def A_			(			self ):
          snake_case__						=				"Hello World!"
          snake_case__						=				[1_26, 32, 2_62, 1_52, 38, 72, 2_87]

          self.assertListEqual(lowerCamelCase		,	self.big_tokenizer.encode(lowerCamelCase ) )
      @slow
      def A_			(			self ):
          snake_case__						=				(
              "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"
          )
          snake_case__						=				[
              1_08,
              2_65,
              24,
              1_11,
              4,
              2_58,
              1_56,
              35,
              28,
              2_75,
              3,
              2_59,
              2_97,
              2_60,
              84,
              4,
              35,
              1_10,
              44,
              8,
              2_59,
              91,
              2_68,
              21,
              11,
              2_09,
              2_74,
              1_09,
              2_66,
              2_77,
              1_17,
              86,
              93,
              3_15,
              2_58,
              2_78,
              2_58,
              2_77,
              2_58,
              0,
              2_58,
              2_88,
              2_58,
              3_19,
              2_58,
              0,
              2_58,
              0,
              2_58,
              0,
              2_58,
              0,
              2_58,
              2_87,
              2_58,
              3_15,
              2_58,
              2_89,
              2_58,
              2_78,
              99,
              2_69,
              2_66,
              2_62,
              8,
              2_59,
              2_41,
              4,
              2_17,
              2_30,
              2_68,
              2_66,
              55,
              1_68,
              1_06,
              75,
              1_93,
              2_66,
              2_23,
              27,
              49,
              26,
              2_82,
              25,
              2_64,
              2_99,
              19,
              26,
              0,
              2_58,
              2_77,
              1_17,
              86,
              93,
              1_76,
              1_83,
              2_70,
              11,
              2_62,
              42,
              61,
              2_65,
          ]

          self.assertListEqual(lowerCamelCase		,	self.big_tokenizer.encode(lowerCamelCase ) )
      @require_torch
      @slow
      def A_			(			self ):
          import torch

          from transformers import ReformerConfig, ReformerModel

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

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

          # 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(**lowerCamelCase )
              model(**lowerCamelCase )



      @slow
      def A_			(			self ):
          # fmt: off
          snake_case__						=				{"input_ids": [[1_08, 2_65, 24, 1_11, 4, 2_58, 1_56, 7, 51, 2_79, 58, 7, 76, 25, 69, 2_78], [1_40, 2_43, 2_64, 1_34, 17, 2_67, 77, 2_63, 22, 2_62, 2_97, 2_58, 3_04, 1_77, 2_79, 2_66, 14, 89, 13, 35, 2_61, 2_99, 2_72, 1_37, 2_75, 2_78]], "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
          snake_case__						=				[
              "This is a very simple sentence.",
              "The quick brown fox jumps over the lazy dog.",
          ]

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





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase							):
    return price * (1 + tax_rate)


if __name__ == "__main__":
     print(F'''{price_plus_tax(100, 0.2_5) = }''')
     print(F'''{price_plus_tax(1_2_5.5_0, 0.0_5) = }''')



