Class RNNCellImpl¶
Defined in File rnn.h
Page Contents
Inheritance Relationships¶
Base Type¶
public torch::nn::detail::RNNCellImplBase< RNNCellImpl >
(Template Class RNNCellImplBase)
Class Documentation¶
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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
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inline RNNCellImpl(int64_t input_size, int64_t hidden_size)¶
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explicit RNNCellImpl(const RNNCellOptions &options_)¶
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Tensor forward(const Tensor &input, const Tensor &hx = {})¶
Public Members
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RNNCellOptions options¶
Protected Functions
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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.
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inline virtual unsigned int _forward_num_required_args() override¶
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inline std::vector<torch::nn::AnyValue> _forward_populate_default_args(std::vector<torch::nn::AnyValue> &&arguments) override¶
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virtual std::string get_nonlinearity_str() const override¶
Friends
- friend struct torch::nn::AnyModuleHolder
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inline RNNCellImpl(int64_t input_size, int64_t hidden_size)¶