@Namespace(value="torch::nn") @NoOffset @Properties(inherit=torch.class) public class MarginRankingLossImpl extends MarginRankingLossImplCloneable
x1
, :math:x2
, two 1D mini-batch Tensors
,
and a label 1D mini-batch tensor :math:y
(containing 1 or -1).
See https://pytorch.org/docs/master/nn.html#torch.nn.MarginRankingLoss to
learn about the exact behavior of this module.
See the documentation for torch::nn::MarginRankingLossOptions
class to
learn what constructor arguments are supported for this module.
Example:
MarginRankingLoss
model(MarginRankingLossOptions().margin(0.5).reduction(torch::kSum));
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
---|
MarginRankingLossImpl() |
MarginRankingLossImpl(MarginRankingLossOptions options_) |
MarginRankingLossImpl(Module pointer)
Downcast constructor.
|
MarginRankingLossImpl(Pointer p)
Pointer cast constructor.
|
Modifier and Type | Method and Description |
---|---|
Tensor |
forward(Tensor input1,
Tensor input2,
Tensor targets) |
MarginRankingLossOptions |
options()
The options with which this
Module was constructed. |
MarginRankingLossImpl |
options(MarginRankingLossOptions setter) |
void |
pretty_print(Pointer stream)
Pretty prints the
MarginRankingLoss 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, clone
apply, 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_grad
address, 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, zero
public MarginRankingLossImpl(Pointer p)
Pointer(Pointer)
.public MarginRankingLossImpl(Module pointer)
public MarginRankingLossImpl(@ByVal(nullValue="torch::nn::MarginRankingLossOptions{}") MarginRankingLossOptions options_)
public MarginRankingLossImpl()
public void reset()
MarginRankingLossImplCloneable
reset()
must perform initialization of all members with reference
semantics, most importantly parameters, buffers and submodules.reset
in class MarginRankingLossImplCloneable
public void pretty_print(@Cast(value="std::ostream*") @ByRef Pointer stream)
MarginRankingLoss
module into the given stream
.pretty_print
in class Module
@ByVal public Tensor forward(@Const @ByRef Tensor input1, @Const @ByRef Tensor input2, @Const @ByRef Tensor targets)
@ByRef public MarginRankingLossOptions options()
Module
was constructed.public MarginRankingLossImpl options(MarginRankingLossOptions setter)
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