





'''simple docstring'''






import math

import tensorflow as tf
from packaging import version



def        UpperCamelCase__		(						__magic_name__  :   Dict      )				->			List[Any]:
 '''simple docstring'''






 snake_case__     :					List[Any]    =  tf.convert_to_tensor(__magic_name__      )
 snake_case__     :					Tuple    =  0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0      )		,       x.dtype      )      ))

 return x * cdf



def        UpperCamelCase__		(						__magic_name__  :   Any      )				->			Tuple:
 '''simple docstring'''






 snake_case__     :					Tuple    =  tf.convert_to_tensor(__magic_name__      )
 snake_case__     :					Any    =  tf.cast(math.pi		,       x.dtype      )
 snake_case__     :					Any    =  tf.cast(0.04_4715		,       x.dtype      )
 snake_case__     :					Dict    =  0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi      ) * (x + coeff * tf.pow(__magic_name__		,       3      ))      ))

 return x * cdf



def        UpperCamelCase__		(						__magic_name__  :   Tuple      )				->			int:
 '''simple docstring'''






 snake_case__     :					Dict    =  tf.convert_to_tensor(__magic_name__      )

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



def        UpperCamelCase__		(						__magic_name__  :   Union[str, Any]      )				->			int:
 '''simple docstring'''






 snake_case__     :					Optional[Any]    =  tf.convert_to_tensor(__magic_name__      )
 snake_case__     :					int    =  tf.cast(0.04_4715		,       x.dtype      )
 snake_case__     :					Optional[int]    =  tf.cast(0.79_7884_5608		,       x.dtype      )

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



def        UpperCamelCase__		(						__magic_name__  :   int      )				->			Optional[Any]:
 '''simple docstring'''






 snake_case__     :					List[Any]    =  tf.convert_to_tensor(__magic_name__      )
 snake_case__     :					List[Any]    =  tf.cast(1.702		,       x.dtype      )
 return x * tf.math.sigmoid(coeff * x      )



def        UpperCamelCase__		(						__magic_name__  :   Tuple      )				->			List[Any]:
 '''simple docstring'''






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



def        UpperCamelCase__		(						__magic_name__  :   Any		,       __magic_name__  :   str=-1      )				->			Tuple:
 '''simple docstring'''






 snake_case__  ,							snake_case__     :					List[str]    =  tf.split(__magic_name__		,       2		,       axis=__magic_name__      )
 return a * tf.math.sigmoid(__magic_name__      )


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



    def        UpperCamelCase__		(						__magic_name__  :   Optional[Any]      )				->			Union[str, Any]:
     '''simple docstring'''






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

    A_		:  Optional[Any]		 =						tf.keras.activations.gelu





    A_		:  List[str]		 =						approximate_gelu_wrap
else:
    A_		:  Any		 =						_gelu
    A_		:  Optional[int]		 =						_gelu_new


A_		:  int		 =						{
    "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        UpperCamelCase__		(						__magic_name__  :   Tuple      )				->			List[Any]:
 '''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'''




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..utils import cached_file


# docstyle-ignore
lowercase     :							Tuple       						=     '\nHuman: <<task>>\n\nAssistant: '


lowercase     :							Union[str, Any]       						=     'huggingface-tools/default-prompts'
lowercase     :							int       						=     {'chat': 'chat_prompt_template.txt', 'run': 'run_prompt_template.txt'}







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__="run"		):




    '''simple docstring'''



    if prompt_or_repo_id is None:
        A			:  List[Any]   =		DEFAULT_PROMPTS_REPO

    # prompt is considered a repo ID when it does not contain any kind of space
    if re.search('''\\s'''						,							snake_case__		) is not None:
        return prompt_or_repo_id

    A			:  int   =		cached_file(
        snake_case__						,							PROMPT_FILES[mode]						,							repo_type='''dataset'''						,							user_agent={'''agent''': agent_name}		)
    with open(snake_case__						,							'''r'''						,							encoding='''utf-8'''		) as f:
        return f.read()




