



'''simple docstring'''





import math

import tensorflow as tf
from packaging import version




def 							lowerCamelCase	(					_snake_case	:    List[Any]							):





    '''simple docstring'''


    lowercase__									=    tf.convert_to_tensor(_snake_case							)
    lowercase__									=    0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0							)  ,x.dtype							)							))

    return x * cdf




def 							lowerCamelCase	(					_snake_case	:    Tuple							):





    '''simple docstring'''


    lowercase__									=    tf.convert_to_tensor(_snake_case							)
    lowercase__									=    tf.cast(math.pi  ,x.dtype							)
    lowercase__									=    tf.cast(0.044_715  ,x.dtype							)
    lowercase__									=    0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi							) * (x + coeff * tf.pow(_snake_case  ,3							))							))

    return x * cdf




def 							lowerCamelCase	(					_snake_case	:    Optional[Any]							):





    '''simple docstring'''


    lowercase__									=    tf.convert_to_tensor(_snake_case							)

    return x * tf.tanh(tf.math.softplus(_snake_case							)							)




def 							lowerCamelCase	(					_snake_case	:    Optional[Any]							):





    '''simple docstring'''


    lowercase__									=    tf.convert_to_tensor(_snake_case							)
    lowercase__									=    tf.cast(0.044_715  ,x.dtype							)
    lowercase__									=    tf.cast(0.7_978_845_608  ,x.dtype							)

    return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)							))




def 							lowerCamelCase	(					_snake_case	:    Any							):





    '''simple docstring'''


    lowercase__									=    tf.convert_to_tensor(_snake_case							)
    lowercase__									=    tf.cast(1.702  ,x.dtype							)
    return x * tf.math.sigmoid(coeff * x							)




def 							lowerCamelCase	(					_snake_case	:    str							):





    '''simple docstring'''


    return tf.clip_by_value(_gelu(_snake_case							)  ,-10  ,10							)




def 							lowerCamelCase	(					_snake_case	:    Union[str, Any]  ,_snake_case	:    Dict=-1							):





    '''simple docstring'''


    lowercase__							,							lowercase__									=    tf.split(_snake_case  ,2  ,axis=_snake_case							)
    return a * tf.math.sigmoid(_snake_case							)


if version.parse(tf.version.VERSION) >= version.parse("2.4"):




 def 							lowerCamelCase	(					_snake_case	:    Tuple							):





     '''simple docstring'''


     return tf.keras.activations.gelu(_snake_case  ,approximate=_snake_case							)

 SCREAMING_SNAKE_CASE__          =  tf.keras.activations.gelu



 SCREAMING_SNAKE_CASE__          =  approximate_gelu_wrap
else:
 SCREAMING_SNAKE_CASE__          =  _gelu
 SCREAMING_SNAKE_CASE__          =  _gelu_new


SCREAMING_SNAKE_CASE__          =  {
    "gelu": gelu,
    "gelu_10": gelu_aa,
    "gelu_fast": gelu_fast,
    "gelu_new": gelu_new,
    "glu": glu,
    "mish": mish,
    "quick_gelu": quick_gelu,
    "relu": tf.keras.activations.relu,
    "sigmoid": tf.keras.activations.sigmoid,
    "silu": tf.keras.activations.swish,
    "swish": tf.keras.activations.swish,
    "tanh": tf.keras.activations.tanh,
}




def 							lowerCamelCase	(					_snake_case	:    str							):





    '''simple docstring'''


    if activation_string in ACTaFN:
        return ACTaFN[activation_string]
    else:
        raise KeyError(f'''function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()							)}'''							)









'''simple docstring'''





import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 					snake_case			(UpperCamelCase		,   unittest.TestCase ):
       lowerCAmelCase__	:str     =       MgpstrTokenizer
       lowerCAmelCase__	:Tuple     =       False
       lowerCAmelCase__	:Any     =       {}
       lowerCAmelCase__	:List[Any]     =       False



       def 				_a   (					self   )	->				Union[str, Any]:
           super().setUp()

           # fmt: off
           lowercase__									=    ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
           # fmt: on
           lowercase__									=    dict(zip(UpperCAmelCase_  ,range(len(UpperCAmelCase_   )   )   )   )

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



       def 				_a   (					self  ,**UpperCAmelCase_   )	->				Any:
           return MgpstrTokenizer.from_pretrained(self.tmpdirname  ,**UpperCAmelCase_   )



       def 				_a   (					self  ,UpperCAmelCase_   )	->				Dict:
           lowercase__									=    "tester"
           lowercase__									=    "tester"
           return input_text, output_text



       @unittest.skip("MGP-STR always lower cases letters."   )
       def 				_a   (					self   )	->				Dict:
           pass



       def 				_a   (					self   )	->				Optional[Any]:
           lowercase__									=    self.get_tokenizers(do_lower_case=UpperCAmelCase_   )
           for tokenizer in tokenizers:
               with self.subTest(F'''{tokenizer.__class__.__name__}'''   ):
                   lowercase__									=    "[SPECIAL_TOKEN]"

                   tokenizer.add_special_tokens({"cls_token": special_token}   )
                   lowercase__									=    tokenizer.encode([special_token]  ,add_special_tokens=UpperCAmelCase_   )
                   self.assertEqual(len(UpperCAmelCase_   )  ,1   )

                   lowercase__									=    tokenizer.decode(UpperCAmelCase_  ,skip_special_tokens=UpperCAmelCase_   )
                   self.assertTrue(special_token not in decoded   )



       def 				_a   (					self   )	->				str:
           lowercase__									=    self.get_tokenizers()
           for tokenizer in tokenizers:
               with self.subTest(F'''{tokenizer.__class__.__name__}'''   ):
                   lowercase__							,							lowercase__									=    self.get_input_output_texts(UpperCAmelCase_   )

                   lowercase__									=    tokenizer.tokenize(UpperCAmelCase_   )
                   lowercase__									=    tokenizer.convert_tokens_to_ids(UpperCAmelCase_   )
                   lowercase__									=    tokenizer.encode(UpperCAmelCase_  ,add_special_tokens=UpperCAmelCase_   )
                   self.assertListEqual(UpperCAmelCase_  ,UpperCAmelCase_   )

                   lowercase__									=    tokenizer.convert_ids_to_tokens(UpperCAmelCase_   )
                   self.assertNotEqual(len(UpperCAmelCase_   )  ,0   )
                   lowercase__									=    tokenizer.decode(UpperCAmelCase_   )
                   self.assertIsInstance(UpperCAmelCase_  ,UpperCAmelCase_   )

                   self.assertEqual(text_a.replace(" "  ,""   )  ,UpperCAmelCase_   )



       @unittest.skip("MGP-STR tokenizer only handles one sequence."   )
       def 				_a   (					self   )	->				Optional[int]:
           pass







       @unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"   )
       def 				_a   (					self   )	->				Any:
           pass




