---
title: "rnn(initialHiddenStates:inputHiddenWeight:hiddenHiddenWeight:bias:direction:activation:outputSequence:)"
framework: accelerate
role: symbol
role_heading: Instance Method
path: "accelerate/bnnsgraph/builder/tensor/rnn(initialhiddenstates:inputhiddenweight:hiddenhiddenweight:bias:direction:activation:outputsequence:)"
---

# rnn(initialHiddenStates:inputHiddenWeight:hiddenHiddenWeight:bias:direction:activation:outputSequence:)

Adds an RNN operation to the current graph.

## Declaration

```swift
func rnn(initialHiddenStates: BNNSGraph.Builder.Tensor<T>, inputHiddenWeight: BNNSGraph.Builder.Tensor<T>, hiddenHiddenWeight: BNNSGraph.Builder.Tensor<T>, bias: BNNSGraph.Builder.Tensor<T>, direction: BNNSGraph.Builder.Direction, activation: BNNSGraph.Builder.Activation, outputSequence: Bool) -> (output: BNNSGraph.Builder.Tensor<T>, hiddenStates: BNNSGraph.Builder.Tensor<T>)
```

## Parameters

- `initialHiddenStates`: The initial hidden states, with the shape (N, Hout), that the operation uses in the second matrix multiplication above when computing h[0, ...].
- `inputHiddenWeight`: The input-hidden weight with the shape (Hout, Hin).
- `hiddenHiddenWeight`: The hidden-hidden weight with the shape (Hout, Hout).
- `bias`: The bias (the sum of input-hidden and hidden-hidden biases) with the shape (Hout,).
- `direction`: An enumeration that specifies a forward or backward RNN.
- `activation`: An enumeration that controls the output activation function.
- `outputSequence`: When true, output is of shape (L, N, Hout) and contains hidden states from every step, h[:, ...]. When false, output is of shape (1, N, Hout) and contains hidden states from the last step, h[-1, ...].

## Discussion

Discussion For each time t, from 0 to L-1, this operation performs the following: h[t, ...] = activation(matmul(x[t, ...], inputHiddenWeight^T) +                        matmul(h[t-1, ...], hiddenHiddenWeight^T) +                        bias) The input tensor x is of shape (L, N, Hin). hiddenStates is of shape (N, Hout) and contains hidden states from the last step, h[-1, ...].