Developer Guide for Intel® Data Analytics Acceleration Library 2018 Update 2

Batch Processing

Algorithm Input

The SmoothReLU function accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.

Input ID

Input

data

Pointer to the numeric table of size n x p. This table can be an object of any class derived from NumericTable.

Algorithm Parameters

The SmoothReLU function has the following parameters:

Parameter

Default Value

Description

algorithmFPType

float

The floating-point type that the algorithm uses for intermediate computations. Can be float or double.

method

defaultDense

Performance-oriented computation method, the only method supported by the algorithm.

Algorithm Output

The SmoothReLU function calculates the result described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.

Result ID

Result

output

Pointer to the numeric table of size n x p with the matrix Y. By default, the result is an object of the HomogenNumericTable class, but you can define the result as an object of any class derived from NumericTable except PackedTriangularMatrix, PackedSymmetricMatrix, and CSRNumericTable.

Examples

C++: smoothrelu_dense_batch.cpp

Java*: SmoothReLUDenseBatch.java

Python*: smoothrelu_dense_batch.py

See Also