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Struct SoftMarginLossImpl

Inheritance Relationships

Base Type

Struct Documentation

struct torch::nn::SoftMarginLossImpl : public torch::nn::Cloneable<SoftMarginLossImpl>

Creates a criterion that optimizes a two-class classification logistic loss between input tensor :math:x and target tensor :math:y (containing 1 or -1).

See https://pytorch.org/docs/master/nn.html#torch.nn.SoftMarginLoss to learn about the exact behavior of this module.

See the documentation for torch::nn::SoftMarginLossOptions class to learn what constructor arguments are supported for this module.

Example:

SoftMarginLoss model(SoftMarginLossOptions(torch::kNone));

Public Functions

SoftMarginLossImpl(const SoftMarginLossOptions &options_ = {})
void pretty_print(std::ostream &stream) const override

Pretty prints the SoftMarginLoss module into the given stream.

void reset() override

reset() must perform initialization of all members with reference semantics, most importantly parameters, buffers and submodules.

Tensor forward(const Tensor &input, const Tensor &target)

Public Members

SoftMarginLossOptions options

The options with which this Module was constructed.

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