



import math
from collections import OrderedDict

import torch
from packaging import version
from torch import Tensor, nn

from .utils import logging


__snake_case		:Dict 						=	logging.get_logger(__name__)

class        _A			(      nn.Module       ):



       def __init__(						self				:	Union[str, Any]):


           '''simple docstring'''

           super().__init__()
           if version.parse(torch.__version__) < version.parse('''1.12.0'''):
               raise ImportError(
                   F'You are using torch=={torch.__version__}, but torch>=1.12.0 is required to use '
                   '''PytorchGELUTanh. Please upgrade torch.''')





       def 						_lowerCamelCase     (						self				:	Any	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return nn.functional.gelu(__SCREAMING_SNAKE_CASE	,						approximate='''tanh''')


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	Dict	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi) * (input + 0.04_47_15 * torch.pow(__SCREAMING_SNAKE_CASE	,						3.0))))


class        _A			(      nn.Module       ):



       def __init__(						self				:	Optional[int]	,						__SCREAMING_SNAKE_CASE				:	bool = False):


           '''simple docstring'''

           super().__init__()
           if use_gelu_python:
               __a					=							self._gelu_python
           else:
               __a					=							nn.functional.gelu



       def 						_lowerCamelCase     (						self				:	Optional[int]	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return input * 0.5 * (1.0 + torch.erf(input / math.sqrt(2.0)))





       def 						_lowerCamelCase     (						self				:	Optional[Any]	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return self.act(__SCREAMING_SNAKE_CASE)


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	Tuple	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return 0.5 * input * (1.0 + torch.tanh(input * 0.79_78_84_56_08 * (1.0 + 0.04_47_15 * input * input)))


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	Optional[Any]	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return input * torch.sigmoid(1.7_02 * input)


class        _A			(      nn.Module       ):



       def __init__(						self				:	List[str]	,						__SCREAMING_SNAKE_CASE				:	float	,						__SCREAMING_SNAKE_CASE				:	float):


           '''simple docstring'''

           if min > max:
               raise ValueError(F'min should be < max (got min: {min}, max: {max})')

           super().__init__()
           __a					=							min
           __a					=							max





       def 						_lowerCamelCase     (						self				:	str	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return torch.clip(gelu(__SCREAMING_SNAKE_CASE)	,						self.min	,						self.max)


class        _A			(      nn.Module       ):



       def __init__(						self				:	Any):


           '''simple docstring'''

           super().__init__()
           __a					=							math.sqrt(2 / math.pi)





       def 						_lowerCamelCase     (						self				:	List[str]	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return 0.5 * input * (1 + torch.tanh(self.precomputed_constant * (input + 0.04_47_15 * torch.pow(__SCREAMING_SNAKE_CASE	,						3))))


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	Tuple	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return nn.functional.silu(__SCREAMING_SNAKE_CASE)


class        _A			(      nn.Module       ):



       def __init__(						self				:	Any):


           '''simple docstring'''

           super().__init__()
           if version.parse(torch.__version__) < version.parse('''1.9.0'''):
               __a					=							self._mish_python
           else:
               __a					=							nn.functional.mish



       def 						_lowerCamelCase     (						self				:	str	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return input * torch.tanh(nn.functional.softplus(__SCREAMING_SNAKE_CASE))





       def 						_lowerCamelCase     (						self				:	List[Any]	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return self.act(__SCREAMING_SNAKE_CASE)


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	List[Any]	,						__SCREAMING_SNAKE_CASE				:	Tensor):


           '''simple docstring'''

           return input


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	Optional[int]	,						__SCREAMING_SNAKE_CASE				:	Any	,						__SCREAMING_SNAKE_CASE				:	Optional[Any]=0.70_71_07	,						__SCREAMING_SNAKE_CASE				:	Optional[int]=0.28_20_95):


           '''simple docstring'''

           __a					=							(input - mu).div(sigma * math.sqrt(2.0))
           return 0.5 * (1.0 + torch.erf(__SCREAMING_SNAKE_CASE))


class        _A			(      nn.Module       ):



       def 						_lowerCamelCase     (						self				:	List[str]	,						__SCREAMING_SNAKE_CASE				:	Union[str, Any]):


           '''simple docstring'''

           __a					=							nn.functional.relu(__SCREAMING_SNAKE_CASE)
           __a					=							torch.square(__SCREAMING_SNAKE_CASE)
           return squared


class        _A			(      __UpperCAmelCase       ):



       def __getitem__(						self				:	Union[str, Any]	,						__SCREAMING_SNAKE_CASE				:	int):


           '''simple docstring'''

           __a					=							super().__getitem__(__SCREAMING_SNAKE_CASE)
           __a			,  __a					=							content if isinstance(__SCREAMING_SNAKE_CASE	,						__SCREAMING_SNAKE_CASE) else (content, {})
           return cls(**__SCREAMING_SNAKE_CASE)


__snake_case		:List[Any] 						=	{
    '''gelu''': GELUActivation,
    '''gelu_10''': (ClippedGELUActivation, {'''min''': -10, '''max''': 10}),
    '''gelu_fast''': FastGELUActivation,
    '''gelu_new''': NewGELUActivation,
    '''gelu_python''': (GELUActivation, {'''use_gelu_python''': True}),
    '''gelu_pytorch_tanh''': PytorchGELUTanh,
    '''gelu_accurate''': AccurateGELUActivation,
    '''laplace''': LaplaceActivation,
    '''linear''': LinearActivation,
    '''mish''': MishActivation,
    '''quick_gelu''': QuickGELUActivation,
    '''relu''': nn.ReLU,
    '''relu2''': ReLUSquaredActivation,
    '''relu6''': nn.ReLUa,
    '''sigmoid''': nn.Sigmoid,
    '''silu''': SiLUActivation,
    '''swish''': SiLUActivation,
    '''tanh''': nn.Tanh,
}
__snake_case		:List[Any] 						=	ClassInstantier(ACTaCLS)





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


# For backwards compatibility with: from activations import gelu_python
__snake_case		:List[str] 						=	get_activation('''gelu_python''')
__snake_case		:str 						=	get_activation('''gelu_new''')
__snake_case		:List[Any] 						=	get_activation('''gelu''')
__snake_case		:Any 						=	get_activation('''gelu_fast''')
__snake_case		:int 						=	get_activation('''quick_gelu''')
__snake_case		:List[str] 						=	get_activation('''silu''')
__snake_case		:Tuple 						=	get_activation('''mish''')
__snake_case		:Any 						=	get_activation('''linear''')










from __future__ import annotations

from typing import Generic, TypeVar

__snake_case		:str 						=	TypeVar('''T''')

class        _A			(      __UpperCAmelCase       ):
       pass


class        _A			(      __UpperCAmelCase       ):
       pass


class        _A			(      Generic[T]       ):



       def __init__(						self				:	List[Any]	,						__SCREAMING_SNAKE_CASE				:	int = 10):


           '''simple docstring'''

           __a					=							[]
           __a					=							limit



       def __bool__(						self				:	List[Any]):


           '''simple docstring'''

           return bool(self.stack)



       def __str__(						self				:	Any):


           '''simple docstring'''

           return str(self.stack)



       def 						_lowerCamelCase     (						self				:	List[Any]	,						__SCREAMING_SNAKE_CASE				:	T):


           '''simple docstring'''

           if len(self.stack) >= self.limit:
               raise StackOverflowError
           self.stack.append(__SCREAMING_SNAKE_CASE)



       def 						_lowerCamelCase     (						self				:	str):


           '''simple docstring'''

           if not self.stack:
               raise StackUnderflowError
           return self.stack.pop()



       def 						_lowerCamelCase     (						self				:	Optional[Any]):


           '''simple docstring'''

           if not self.stack:
               raise StackUnderflowError
           return self.stack[-1]



       def 						_lowerCamelCase     (						self				:	Union[str, Any]):


           '''simple docstring'''

           return not bool(self.stack)



       def 						_lowerCamelCase     (						self				:	Tuple):


           '''simple docstring'''

           return self.size() == self.limit



       def 						_lowerCamelCase     (						self				:	Union[str, Any]):


           '''simple docstring'''

           return len(self.stack)





       def __contains__(						self				:	int	,						__SCREAMING_SNAKE_CASE				:	T):


           '''simple docstring'''

           return item in self.stack





def 	__snake_case      (     ):
    __a					=							Stack(10							)
    assert bool(_UpperCAmelCase							) is False
    assert stack.is_empty() is True
    assert stack.is_full() is False
    assert str(_UpperCAmelCase							) == "[]"

    try:
        __a					=							stack.pop()
        raise AssertionError  # This should not happen
    except StackUnderflowError:
        assert True  # This should happen

    try:
        __a					=							stack.peek()
        raise AssertionError  # This should not happen
    except StackUnderflowError:
        assert True  # This should happen

    for i in range(10							):
        assert stack.size() == i
        stack.push(_UpperCAmelCase							)

    assert bool(_UpperCAmelCase							)
    assert not stack.is_empty()
    assert stack.is_full()
    assert str(_UpperCAmelCase							) == str(list(range(10							)							)							)
    assert stack.pop() == 9
    assert stack.peek() == 8

    stack.push(100							)
    assert str(_UpperCAmelCase							) == str([0, 1, 2, 3, 4, 5, 6, 7, 8, 100]							)

    try:
        stack.push(200							)
        raise AssertionError  # This should not happen
    except StackOverflowError:
        assert True  # This should happen

    assert not stack.is_empty()
    assert stack.size() == 10

    assert 5 in stack
    assert 55 not in stack


if __name__ == "__main__":
 test_stack()





