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BiasGelu
Description
It’s an extension of Gelu. It takes the sum of input A and bias input B as the input of Gelu activation.
Input parameters
specified_outputs_name : array, this parameter lets you manually assign custom names to the output tensors of a node.
Graphs in : cluster, ONNX model architecture.
A – T : object, the normal input data.
B – T : object, the bias input data that is a 1D tensor.


training? : boolean, whether the layer is in training mode (can store data for backward).
Default value “True”.
lda coeff : float, defines the coefficient by which the loss derivative will be multiplied before being sent to the previous layer (since during the backward run we go backwards).
Default value “1”.
name (optional) : string, name of the node.

Output parameters
C – T : object, the output.
Type Constraints
T in (tensor(bfloat16)
, tensor(double)
, tensor(float)
, tensor(float16)
) : Constrain input and output types to float tensors.