.. _l-onnx-doc-GRUUnit:

=======
GRUUnit
=======

.. contents::
    :local:


.. _l-onnx-op-gruunit-1:

GRUUnit - 1
===========

**Version**

* **name**: `GRUUnit (GitHub) <https://github.com/onnx/onnx/blob/main/docs/Operators.md#GRUUnit>`_
* **domain**: **main**
* **since_version**: **1**
* **function**:
* **support_level**:
* **shape inference**:

This version of the operator has been available
**since version 1**.

**Summary**

GRUUnit computes the activations of a standard GRU,
in a sequence-length aware fashion.
Concretely, given the (fused) inputs X (TxNxD), the previous hidden
state (NxD), and the sequence lengths (N), computes the GRU
activations, avoiding computation if the input is invalid (as in, the
value at X[t][n] >= seqLengths[n].

**Attributes**

* **drop_states**:
  Bool to determine if hidden state is zeroes or passed along for
  timesteps past the given sequence_length. Default value is ``?``.

**Inputs**

* **hidden_prev** (heterogeneous) - **T**:
  The previous GRU hidden state.
* **gates** (heterogeneous) - **T**:
  Unactivated gate outputs from forget, update, and output gates, pre-
  activation.
* **seq_lengths** (heterogeneous) - **T**:
  Array of sequence lengths.  len(seq_lengths) should equal batch size
  N.
* **t** (heterogeneous) - **T**:
  The timestep for this operation.

**Outputs**

* **hidden** (heterogeneous) - **T**:
  The new GRU hidden state calculated by this op.

**Examples**