
import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




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

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          snake_case__    =					[
              "l",
              "o",
              "w",
              "e",
              "r",
              "s",
              "t",
              "i",
              "d",
              "n",
              "w</w>",
              "r</w>",
              "t</w>",
              "lo",
              "low",
              "er</w>",
              "low</w>",
              "lowest</w>",
              "newer</w>",
              "wider</w>",
              "<unk>",
          ]
          snake_case__    =					dict(zip(lowerCamelCase		,						range(len(lowerCamelCase			)			)			)			)
          snake_case__    =					["#version: 0.2", "l o", "lo w", "e r</w>", ""]

          snake_case__    =					os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["vocab_file"]			)
          snake_case__    =					os.path.join(self.tmpdirname		,						VOCAB_FILES_NAMES["merges_file"]			)
          with open(self.vocab_file		,						"w"			) as fp:
              fp.write(json.dumps(lowerCamelCase			)			)
          with open(self.merges_file		,						"w"			) as fp:
              fp.write("\n".join(lowerCamelCase			)			)
      def A_      (      self		,						lowerCamelCase			):
          return "lower newer", "lower newer"
      def A_      (      self			):
          snake_case__    =					OpenAIGPTTokenizer(self.vocab_file		,						self.merges_file			)

          snake_case__    =					"lower"
          snake_case__    =					["low", "er</w>"]
          snake_case__    =					tokenizer.tokenize(lowerCamelCase			)
          self.assertListEqual(lowerCamelCase		,						lowerCamelCase			)

          snake_case__    =					tokens + ["<unk>"]
          snake_case__    =					[14, 15, 20]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(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





@require_ftfy
@require_spacy
@require_tokenizers
class        _SCREAMING_SNAKE_CASE	(   __UpperCamelCase			):
      pass





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float(moles / volume				) * nfactor				)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float((moles * 0.0_821 * temperature) / (volume)				)				)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float((moles * 0.0_821 * temperature) / (pressure)				)				)





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase     ,		__lowerCAmelCase     ,		__lowerCAmelCase				):
    return round(float((pressure * volume) / (0.0_821 * moles)				)				)


if __name__ == "__main__":
     import doctest

     doctest.testmod()



