openvino/docs/ops/sequence/RNNCell_1.md

RNNCell

Versioned name: RNNCell-1

Category: Sequence processing

Short description: RNNCell represents a single RNN cell that computes the output using the formula described in the article.

Attributes

• hidden_size

  • Description: hidden_size specifies hidden state size.
  • Range of values: a positive integer
  • Type: int
  • Default value: None
  • Required: yes

• activations

  • Description: activation functions for gates
  • Range of values: any combination of relu, sigmoid, tanh
  • Type: a list of strings
  • Default value: sigmoid,tanh
  • Required: no

• activations_alpha, activations_beta

  • Description: activations_alpha, activations_beta functions attributes
  • Range of values: a list of floating-point numbers
  • Type: float[]
  • Default value: None
  • Required: no

• clip

  • Description: clip specifies value for tensor clipping to be in [-C, C] before activations
  • Range of values: a positive floating-point number
  • Type: float
  • Default value: infinity that means that the clipping is not applied
  • Required: no

Inputs

• 1: X - 2D ([batch_size, input_size]) input data. Required.

• 2: initial_hidden_state - 2D ([batch_size, hidden_size]) input hidden state data. Required.

Outputs

• 1: Ho - 2D ([batch_size, hidden_size]) output hidden state.