@Namespace(value="torch::nn") @NoOffset @Properties(inherit=torch.class) public class TripletMarginLossImpl extends TripletMarginLossImplCloneable
x1, :math:x2, :math:x3 and a margin with a value greater
than :math:0. This is used for measuring a relative similarity between
samples. A triplet is composed by a, p and n (i.e., anchor,
positive examples and negative examples respectively). The
shapes of all input tensors should be :math:(N, D).
See https://pytorch.org/docs/master/nn.html#torch.nn.TripletMarginLoss to
learn about the exact behavior of this module.
See the documentation for torch::nn::TripletMarginLossOptions class to
learn what constructor arguments are supported for this module.
Example:
TripletMarginLoss
model(TripletMarginLossOptions().margin(3).p(2).eps(1e-06).swap(false));
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter| Constructor and Description |
|---|
TripletMarginLossImpl() |
TripletMarginLossImpl(Module pointer)
Downcast constructor.
|
TripletMarginLossImpl(Pointer p)
Pointer cast constructor.
|
TripletMarginLossImpl(TripletMarginLossOptions options_) |
| Modifier and Type | Method and Description |
|---|---|
Tensor |
forward(Tensor anchor,
Tensor positive,
Tensor negative) |
TripletMarginLossOptions |
options()
The options with which this
Module was constructed. |
TripletMarginLossImpl |
options(TripletMarginLossOptions setter) |
void |
pretty_print(Pointer stream)
Pretty prints the
TripletMarginLoss module into the given stream. |
void |
reset()
reset() must perform initialization of all members with reference
semantics, most importantly parameters, buffers and submodules. |
asModule, asModule, clone, cloneapply, apply, apply, apply, apply, apply, apply, apply, buffers, buffers, children, eval, is_serializable, is_training, load, modules, modules, name, named_buffers, named_buffers, named_children, named_modules, named_modules, named_modules, named_parameters, named_parameters, parameters, parameters, register_buffer, register_buffer, register_module, register_module, register_parameter, register_parameter, register_parameter, register_parameter, save, shiftLeft, to, to, to, train, unregister_module, unregister_module, zero_gradaddress, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zeropublic TripletMarginLossImpl(Pointer p)
Pointer(Pointer).public TripletMarginLossImpl(Module pointer)
public TripletMarginLossImpl(@ByVal(nullValue="torch::nn::TripletMarginLossOptions{}") TripletMarginLossOptions options_)
public TripletMarginLossImpl()
public void reset()
TripletMarginLossImplCloneablereset() must perform initialization of all members with reference
semantics, most importantly parameters, buffers and submodules.reset in class TripletMarginLossImplCloneablepublic void pretty_print(@Cast(value="std::ostream*") @ByRef Pointer stream)
TripletMarginLoss module into the given stream.pretty_print in class Module@ByVal public Tensor forward(@Const @ByRef Tensor anchor, @Const @ByRef Tensor positive, @Const @ByRef Tensor negative)
@ByRef public TripletMarginLossOptions options()
Module was constructed.public TripletMarginLossImpl options(TripletMarginLossOptions setter)
Copyright © 2024. All rights reserved.