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Struct MultiLabelMarginLossImpl#

Inheritance Relationships#

Base Type#

Struct Documentation#

struct MultiLabelMarginLossImpl : public torch::nn::Cloneable<MultiLabelMarginLossImpl>#

Creates a criterion that optimizes a multi-class multi-classification hinge loss (margin-based loss) between input :math:x (a 2D mini-batch Tensor) and output :math:y (which is a 2D Tensor of target class indices).

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

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

Example:

MultiLabelMarginLoss model(MultiLabelMarginLossOptions(torch::kNone));

Public Functions

explicit MultiLabelMarginLossImpl(MultiLabelMarginLossOptions options_ = {})#
virtual void reset() override#

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

virtual void pretty_print(std::ostream &stream) const override#

Pretty prints the L1Loss module into the given stream.

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

Public Members

MultiLabelMarginLossOptions options#

The options with which this Module was constructed.