public final class MPSCNNNeuronType
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
static int |
Absolute
< f(x) = fabs(x)
|
static int |
Count
< holds the number of MPSCNNNeuronTypes
|
static int |
ELU
< f(x) = x >= 0 ? x : a * (exp(x) - 1); exponential linear unit
|
static int |
Exponential
< f(x) = c ^ (a * x + b)
|
static int |
GeLU
< f(x) = (1.0 + erf(x * sqrt(0.5))) * 0.5 * x
|
static int |
HardSigmoid
< f(x) = clamp((x * a) + b, 0, 1)
|
static int |
Linear
< f(x) = a * x + b
|
static int |
Logarithm
< f(x) = log_c(a * x + b)
|
static int |
None
< f(x) = x
|
static int |
Power
< f(x) = (a * x + b) ^ c
|
static int |
PReLU
< Same as ReLU except parameter a is per channel; parameterized rectified linear unit
|
static int |
ReLU
< f(x) = x >= 0 ? x : a * x; rectified linear unit
|
static int |
ReLUN
< f(x) = min((x >= 0 ? x : a * x), b); clamped rectified liniear unit
|
static int |
Sigmoid
< f(x) = 1 / (1 + e^-x)
|
static int |
SoftPlus
< f(x) = a * log(1 + e^(b * x))
|
static int |
SoftSign
< f(x) = x / (1 + abs(x))
|
static int |
TanH
< f(x) = a * tanh(b * x)
|
public static final int None
public static final int ReLU
public static final int Linear
public static final int Sigmoid
public static final int HardSigmoid
public static final int TanH
public static final int Absolute
public static final int SoftPlus
public static final int SoftSign
public static final int ELU
public static final int PReLU
public static final int ReLUN
public static final int Count
public static final int Power
public static final int Exponential
public static final int Logarithm
public static final int GeLU