openvino.runtime.opset4.lstm_cell#

openvino.runtime.opset4.lstm_cell(X: Node | int | float | ndarray, initial_hidden_state: Node | int | float | ndarray, initial_cell_state: Node | int | float | ndarray, W: Node | int | float | ndarray, R: Node | int | float | ndarray, B: Node | int | float | ndarray, hidden_size: int, activations: List[str] | None = None, activations_alpha: List[float] | None = None, activations_beta: List[float] | None = None, clip: float = 0.0, name: str | None = None) → Node#

Return a node which performs LSTMCell operation.

Parameters:

  • X – The input tensor with shape: [batch_size, input_size].

  • initial_hidden_state – The hidden state tensor with shape: [batch_size, hidden_size].

  • initial_cell_state – The cell state tensor with shape: [batch_size, hidden_size].

  • W – The weight tensor with shape: [4*hidden_size, input_size].

  • R – The recurrence weight tensor with shape: [4*hidden_size, hidden_size].

  • B – The bias tensor for gates with shape: [4*hidden_size].

  • hidden_size – Specifies hidden state size.

  • activations – The list of three activation functions for gates.

  • activations_alpha – The list of alpha parameters for activation functions.

  • activations_beta – The list of beta parameters for activation functions.

  • clip – Specifies bound values [-C, C] for tensor clipping performed before activations.

  • name – An optional name of the output node.

Returns:

The new node represents LSTMCell. Node outputs count: 2.