


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 							UpperCamelCase					(		A_						,      unittest.TestCase     ):


   '''simple docstring'''







   lowercase					:	Optional[Any]									=OpenAIGPTTokenizer
   lowercase					:	Optional[Any]									=OpenAIGPTTokenizerFast
   lowercase					:	str									=True
   lowercase					:	Any									=False
   def 		UpperCamelCase  (     self		):
        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        lowercase_       :Optional[Any]     =       [
            """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>""",
        ]
        lowercase_       :Any     =       dict(zip(UpperCamelCase_   ,							range(len(UpperCamelCase_		)		)		)		)
        lowercase_       :Union[str, Any]     =       ["""#version: 0.2""", """l o""", """lo w""", """e r</w>""", """"""]

        lowercase_       :Any     =       os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES['''vocab_file''']		)
        lowercase_       :Union[str, Any]     =       os.path.join(self.tmpdirname   ,							VOCAB_FILES_NAMES['''merges_file''']		)
        with open(self.vocab_file   ,							'''w'''		) as fp:
             fp.write(json.dumps(UpperCamelCase_		)		)
        with open(self.merges_file   ,							'''w'''		) as fp:
             fp.write('''\n'''.join(UpperCamelCase_		)		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_		):
        return "lower newer", "lower newer"
   def 		UpperCamelCase  (     self		):
        lowercase_       :str     =       OpenAIGPTTokenizer(self.vocab_file   ,							self.merges_file		)

        lowercase_       :int     =       """lower"""
        lowercase_       :Optional[Any]     =       ["""low""", """er</w>"""]
        lowercase_       :int     =       tokenizer.tokenize(UpperCamelCase_		)
        self.assertListEqual(UpperCamelCase_   ,							UpperCamelCase_		)

        lowercase_       :Dict     =       tokens + ["""<unk>"""]
        lowercase_       :Dict     =       [14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase_		)   ,							UpperCamelCase_		)
   def 		UpperCamelCase  (     self   ,							UpperCamelCase_=15		):
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"		):
                  lowercase_       :Optional[int]     =       self.rust_tokenizer_class.from_pretrained(UpperCamelCase_   ,							**UpperCamelCase_		)

                  # Simple input
                  lowercase_       :Tuple     =       """This is a simple input"""
                  lowercase_       :Optional[Any]     =       ["""This is a simple input 1""", """This is a simple input 2"""]
                  lowercase_       :List[str]     =       ("""This is a simple input""", """This is a pair""")
                  lowercase_       :Any     =       [
                      ("""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(UpperCamelCase_   ,							tokenizer_r.encode   ,							UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							padding='''max_length'''		)

                  # Simple input
                  self.assertRaises(UpperCamelCase_   ,							tokenizer_r.encode_plus   ,							UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							padding='''max_length'''		)

                  # Simple input
                  self.assertRaises(
                      UpperCamelCase_   ,							tokenizer_r.batch_encode_plus   ,							UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							padding='''max_length'''   ,							)

                  # Pair input
                  self.assertRaises(UpperCamelCase_   ,							tokenizer_r.encode   ,							UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							padding='''max_length'''		)

                  # Pair input
                  self.assertRaises(UpperCamelCase_   ,							tokenizer_r.encode_plus   ,							UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							padding='''max_length'''		)

                  # Pair input
                  self.assertRaises(
                      UpperCamelCase_   ,							tokenizer_r.batch_encode_plus   ,							UpperCamelCase_   ,							max_length=UpperCamelCase_   ,							padding='''max_length'''   ,							)




   def 		UpperCamelCase  (     self		):
        pass






@require_ftfy
@require_spacy
@require_tokenizers
class 							UpperCamelCase					(		A_     ):


   '''simple docstring'''







   pass





from torch import nn




def     UpperCamelCase    (      _a		)					->							str:
     '''simple docstring'''





     if act_fn in ["swish", "silu"]:
          return nn.SiLU()
     elif act_fn == "mish":
          return nn.Mish()
     elif act_fn == "gelu":
          return nn.GELU()
     else:
          raise ValueError(f"Unsupported activation function: {act_fn}"		)

