Selu¶

Selu - 22¶

Version¶

name: Selu (GitHub)
domain: main
since_version: 22
function: True
support_level: SupportType.COMMON
shape inference: True

This version of the operator has been available since version 22.

Summary¶

Selu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the scaled exponential linear unit function, y = gamma * (alpha * e^x - alpha) for x <= 0, y = gamma * x for x > 0, is applied to the tensor elementwise.

Function Body¶

The function definition for this operator.

&lt;
  domain: &#34;&#34;,
  opset_import: [&#34;&#34; : 18]
&gt;
Selu &lt;gamma,alpha&gt;(X) =&gt; (Y)
{
   Alpha = Constant &lt;value_float: float = @alpha&gt; ()
   AlphaCast = CastLike (Alpha, X)
   Gamma = Constant &lt;value_float: float = @gamma&gt; ()
   GammaCast = CastLike (Gamma, X)
   Zero = Constant &lt;value: tensor = float {0}&gt; ()
   ZeroCast = CastLike (Zero, X)
   ExpX = Exp (X)
   AlphaMulExpX = Mul (AlphaCast, ExpX)
   AlphaMulExpXSubAlpha = Sub (AlphaMulExpX, AlphaCast)
   Neg = Mul (GammaCast, AlphaMulExpXSubAlpha)
   Pos = Mul (GammaCast, X)
   XLessThanZero = Less (X, ZeroCast)
   Y = Where (XLessThanZero, Neg, Pos)
}

Attributes¶

alpha - FLOAT (default is '1.67326'):

Coefficient of SELU default to 1.67326319217681884765625 (i.e., float32 approximation of 1.6732632423543772848170429916717).
gamma - FLOAT (default is '1.0507'):

Coefficient of SELU default to 1.05070102214813232421875 (i.e., float32 approximation of 1.0507009873554804934193349852946).

Inputs¶

X (heterogeneous) - T:

Input tensor

Outputs¶

Y (heterogeneous) - T:

Output tensor

Type Constraints¶

T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16) ):

Constrain input and output types to float tensors.

Selu - 6 vs 22

Selu - 6¶

Version¶

name: Selu (GitHub)
domain: main
since_version: 6
function: True
support_level: SupportType.COMMON
shape inference: True

This version of the operator has been available since version 6.

Summary¶

Function Body¶

The function definition for this operator.

&lt;
  domain: &#34;&#34;,
  opset_import: [&#34;&#34; : 18]
&gt;
Selu &lt;gamma,alpha&gt;(X) =&gt; (Y)
{
   Alpha = Constant &lt;value_float: float = @alpha&gt; ()
   AlphaCast = CastLike (Alpha, X)
   Gamma = Constant &lt;value_float: float = @gamma&gt; ()
   GammaCast = CastLike (Gamma, X)
   Zero = Constant &lt;value: tensor = float {0}&gt; ()
   ZeroCast = CastLike (Zero, X)
   ExpX = Exp (X)
   AlphaMulExpX = Mul (AlphaCast, ExpX)
   AlphaMulExpXSubAlpha = Sub (AlphaMulExpX, AlphaCast)
   Neg = Mul (GammaCast, AlphaMulExpXSubAlpha)
   Pos = Mul (GammaCast, X)
   XLessThanZero = Less (X, ZeroCast)
   Y = Where (XLessThanZero, Neg, Pos)
}

Attributes¶

alpha - FLOAT (default is '1.67326'):

Coefficient of SELU default to 1.67326319217681884765625 (i.e., float32 approximation of 1.6732632423543772848170429916717).
gamma - FLOAT (default is '1.0507'):

Coefficient of SELU default to 1.05070102214813232421875 (i.e., float32 approximation of 1.0507009873554804934193349852946).

Inputs¶

X (heterogeneous) - T:

Input tensor

Outputs¶

Y (heterogeneous) - T:

Output tensor

Type Constraints¶

T in ( tensor(double), tensor(float), tensor(float16) ):

Constrain input and output types to float tensors.

Selu - 1¶

Version¶

name: Selu (GitHub)
domain: main
since_version: 1
function: False
support_level: SupportType.COMMON
shape inference: False

This version of the operator has been available since version 1.

Summary¶

Attributes¶

alpha - FLOAT (default is '1.6732'):

Coefficient of SELU default to 1.6732.
consumed_inputs - INTS :

legacy optimization attribute.
gamma - FLOAT (default is '1.0507'):

Coefficient of SELU default to 1.0507.

Inputs¶

X (heterogeneous) - T:

Input tensor

Outputs¶

Y (heterogeneous) - T:

Output tensor

Type Constraints¶

T in ( tensor(double), tensor(float), tensor(float16) ):

Constrain input and output types to float tensors.