LeakyRelu¶
LeakyRelu - 16¶
Version¶
name: LeakyRelu (GitHub)
domain:
main
since_version:
16
function:
True
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 16.
Summary¶
LeakyRelu takes input data (Tensorf(x) = alpha * x for x < 0
,
f(x) = x for x >= 0
, is applied to the data tensor elementwise.
Function Body¶
The function definition for this operator.
<
domain: "",
opset_import: ["" : 16]
>
LeakyRelu <alpha>(X) => (Y)
{
Alpha = Constant <value_float: float = @alpha> ()
AlphaCast = CastLike (Alpha, X)
Zero = Constant <value: tensor = float {0}> ()
ZeroCast = CastLike (Zero, X)
XLessThanZero = Less (X, ZeroCast)
AlphaMulX = Mul (AlphaCast, X)
Y = Where (XLessThanZero, AlphaMulX, X)
}
Attributes¶
alpha - FLOAT (default is
'0.01'
):Coefficient of leakage.
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.
LeakyRelu - 6¶
Version¶
name: LeakyRelu (GitHub)
domain:
main
since_version:
6
function:
False
support_level:
SupportType.COMMON
shape inference:
True
This version of the operator has been available since version 6.
Summary¶
LeakyRelu takes input data (Tensorf(x) = alpha * x for x < 0
,
f(x) = x for x >= 0
, is applied to the data tensor elementwise.
Attributes¶
alpha - FLOAT (default is
'0.01'
):Coefficient of leakage.
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.
LeakyRelu - 1¶
Version¶
name: LeakyRelu (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¶
LeakyRelu takes input data (Tensorf(x) = alpha * x for x < 0
,
f(x) = x for x >= 0
, is applied to the data tensor elementwise.
Attributes¶
alpha - FLOAT (default is
'0.01'
):Coefficient of leakage default to 0.01.
consumed_inputs - INTS :
legacy optimization attribute.
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.