Dropout Layers

Dropout randomly zeros elements during training as a regularization technique, preventing overfitting by forcing the network to learn redundant representations. During evaluation, dropout is disabled and outputs are scaled appropriately.

• Dropout: Standard dropout for fully-connected layers

• Dropout2d/3d: Spatial dropout that zeros entire channels (better for CNNs)

• AlphaDropout: Maintains self-normalizing property (use with SELU activation)

Note

Remember to call model->train() during training and model->eval() during inference to properly enable/disable dropout behavior.

Dropout

class Dropout : public torch::nn::ModuleHolder<DropoutImpl>

A ModuleHolder subclass for DropoutImpl.

See the documentation for DropoutImpl class to learn what methods it provides, and examples of how to use Dropout with torch::nn::DropoutOptions. See the documentation for ModuleHolder to learn about PyTorch’s module storage semantics.

Public Types

using Impl = DropoutImpl

class DropoutImpl : public torch::nn::detail::_DropoutNd<DropoutImpl>

Applies dropout over a 1-D input.

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

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

Example:

Dropout model(DropoutOptions().p(0.42).inplace(true));

Public Functions

Tensor forward(Tensor input)

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

Pretty prints the Dropout module into the given stream.

Example:

auto dropout = torch::nn::Dropout(torch::nn::DropoutOptions(0.5));

Dropout2d / Dropout3d

class Dropout2d : public torch::nn::ModuleHolder<Dropout2dImpl>

A ModuleHolder subclass for Dropout2dImpl.

See the documentation for Dropout2dImpl class to learn what methods it provides, and examples of how to use Dropout2d with torch::nn::Dropout2dOptions. See the documentation for ModuleHolder to learn about PyTorch’s module storage semantics.

Public Types

using Impl = Dropout2dImpl

class Dropout2dImpl : public torch::nn::detail::_DropoutNd<Dropout2dImpl>

Applies dropout over a 2-D input.

See https://pytorch.org/docs/main/nn.html#torch.nn.Dropout2d to learn about the exact behavior of this module.

See the documentation for torch::nn::Dropout2dOptions class to learn what constructor arguments are supported for this module.

Example:

Dropout2d model(Dropout2dOptions().p(0.42).inplace(true));

Public Functions

Tensor forward(Tensor input)

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

Pretty prints the Dropout2d module into the given stream.

class Dropout3d : public torch::nn::ModuleHolder<Dropout3dImpl>

A ModuleHolder subclass for Dropout3dImpl.

See the documentation for Dropout3dImpl class to learn what methods it provides, and examples of how to use Dropout3d with torch::nn::Dropout3dOptions. See the documentation for ModuleHolder to learn about PyTorch’s module storage semantics.

Public Types

using Impl = Dropout3dImpl

class Dropout3dImpl : public torch::nn::detail::_DropoutNd<Dropout3dImpl>

Applies dropout over a 3-D input.

See https://pytorch.org/docs/main/nn.html#torch.nn.Dropout3d to learn about the exact behavior of this module.

See the documentation for torch::nn::Dropout3dOptions class to learn what constructor arguments are supported for this module.

Example:

Dropout3d model(Dropout3dOptions().p(0.42).inplace(true));

Public Functions

Tensor forward(Tensor input)

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

Pretty prints the Dropout3d module into the given stream.

AlphaDropout

class AlphaDropout : public torch::nn::ModuleHolder<AlphaDropoutImpl>

A ModuleHolder subclass for AlphaDropoutImpl.

See the documentation for AlphaDropoutImpl class to learn what methods it provides, and examples of how to use AlphaDropout with torch::nn::AlphaDropoutOptions. See the documentation for ModuleHolder to learn about PyTorch’s module storage semantics.

Public Types

using Impl = AlphaDropoutImpl

class AlphaDropoutImpl : public torch::nn::detail::_DropoutNd<AlphaDropoutImpl>

Applies Alpha Dropout over the input.

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

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

Example:

AlphaDropout model(AlphaDropoutOptions(0.2).inplace(true));

Public Functions

Tensor forward(const Tensor &input)

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

Pretty prints the AlphaDropout module into the given stream.

FeatureAlphaDropout

class FeatureAlphaDropout : public torch::nn::ModuleHolder<FeatureAlphaDropoutImpl>

A ModuleHolder subclass for FeatureAlphaDropoutImpl.

See the documentation for FeatureAlphaDropoutImpl class to learn what methods it provides, and examples of how to use FeatureAlphaDropout with torch::nn::FeatureAlphaDropoutOptions. See the documentation for ModuleHolder to learn about PyTorch’s module storage semantics.

Public Types

using Impl = FeatureAlphaDropoutImpl

class FeatureAlphaDropoutImpl : public torch::nn::detail::_DropoutNd<FeatureAlphaDropoutImpl>

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

Example:

FeatureAlphaDropout model(FeatureAlphaDropoutOptions(0.2).inplace(true));

Public Functions

Tensor forward(const Tensor &input)

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

Pretty prints the FeatureAlphaDropout module into the given stream.