| Package | Description |
|---|---|
| org.bytedeco.pytorch | |
| org.bytedeco.pytorch.global |
| Modifier and Type | Method and Description |
|---|---|
Nonlinearity |
Nonlinearity.put(kConv1D value) |
Nonlinearity |
Nonlinearity.put(kConv2D value) |
Nonlinearity |
Nonlinearity.put(kConv3D value) |
Nonlinearity |
Nonlinearity.put(kConvTranspose1D value) |
Nonlinearity |
Nonlinearity.put(kConvTranspose2D value) |
Nonlinearity |
Nonlinearity.put(kConvTranspose3D value) |
Nonlinearity |
Nonlinearity.put(kLeakyReLU value) |
Nonlinearity |
Nonlinearity.put(kLinear value) |
Nonlinearity |
Nonlinearity.put(kReLU value) |
Nonlinearity |
Nonlinearity.put(kSigmoid value) |
Nonlinearity |
Nonlinearity.put(kTanh value) |
Nonlinearity |
Nonlinearity.put(Nonlinearity x) |
Nonlinearity |
Warning.type() |
| Modifier and Type | Method and Description |
|---|---|
static kLinear |
Nonlinearity.get0(Nonlinearity container) |
static kConv1D |
Nonlinearity.get1(Nonlinearity container) |
static kLeakyReLU |
Nonlinearity.get10(Nonlinearity container) |
static kConv2D |
Nonlinearity.get2(Nonlinearity container) |
static kConv3D |
Nonlinearity.get3(Nonlinearity container) |
static kConvTranspose1D |
Nonlinearity.get4(Nonlinearity container) |
static kConvTranspose2D |
Nonlinearity.get5(Nonlinearity container) |
static kConvTranspose3D |
Nonlinearity.get6(Nonlinearity container) |
static kSigmoid |
Nonlinearity.get7(Nonlinearity container) |
static kTanh |
Nonlinearity.get8(Nonlinearity container) |
static kReLU |
Nonlinearity.get9(Nonlinearity container) |
Nonlinearity |
Nonlinearity.put(Nonlinearity x) |
| Constructor and Description |
|---|
Warning(Nonlinearity type,
SourceLocation source_location,
BytePointer msg,
boolean verbatim) |
Warning(Nonlinearity type,
SourceLocation source_location,
CompileTimeEmptyString msg,
boolean verbatim) |
Warning(Nonlinearity type,
SourceLocation source_location,
String msg,
boolean verbatim) |
| Modifier and Type | Method and Description |
|---|---|
static double |
torch.calculate_gain(Nonlinearity nonlinearity) |
static double |
torch.calculate_gain(Nonlinearity nonlinearity,
double param)
Return the recommended gain value for the given nonlinearity function.
|
static Tensor |
torch.kaiming_normal_(Tensor tensor,
double a,
FanModeType mode,
Nonlinearity nonlinearity)
Fills the input
Tensor with values according to the method
described in "Delving deep into rectifiers: Surpassing human-level
performance on ImageNet classification" - He, K. |
static Tensor |
torch.kaiming_uniform_(Tensor tensor,
double a,
FanModeType mode,
Nonlinearity nonlinearity)
Fills the input
Tensor with values according to the method
described in "Delving deep into rectifiers: Surpassing human-level
performance on ImageNet classification" - He, K. |
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