Class RNNCellImpl

• Defined in File rnn.h

Inheritance Relationships

Base Type

• public torch::nn::detail::RNNCellImplBase< RNNCellImpl > (Template Class RNNCellImplBase)

Class Documentation

class RNNCellImpl : public torch::nn::detail::RNNCellImplBase<RNNCellImpl>

An Elman RNN cell with tanh or ReLU non-linearity.

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

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

Example:

RNNCell model(RNNCellOptions(20,
10).bias(false).nonlinearity(torch::kReLU));

Public Functions

inline RNNCellImpl(int64_t input_size, int64_t hidden_size)

explicit RNNCellImpl(const RNNCellOptions &options_)

Tensor forward(const Tensor &input, Tensor hx = {})

Public Members

RNNCellOptions options

Protected Functions

inline virtual bool _forward_has_default_args() override

The following three functions allow a module with default arguments in its forward method to be used in a Sequential module.

You should NEVER override these functions manually. Instead, you should use the FORWARD_HAS_DEFAULT_ARGS macro.

inline virtual unsigned int _forward_num_required_args() override

inline std::vector<torch::nn::AnyValue> _forward_populate_default_args(std::vector<torch::nn::AnyValue> &&arguments) override

virtual std::string get_nonlinearity_str() const override

Friends

friend struct torch::nn::AnyModuleHolder