Deep Neural Network Library (DNNL)  1.1.3
Performance library for Deep Learning
Binary

API reference: C, C++

The binary primitive computes

\[ dst(\overline{x}) = src0(\overline{x}) op src1(\overline{x}), \]

where \(\op\) is either addition or multiplication.

The binary primitive does not have a notion of forward or backward propagations.

Implementation Details

General Notes

Post-ops and Attributes

The binary primitive does not support any post-ops or attributes.

Data Types Support

The source and destination tensors may have f32 or bf16 data types. See Data Types page for more details.

Data Representation

Sources, Destination

The binary primitive works with arbitrary data tensors. There is no special meaning associated with any of tensors dimensions.

Implementation Limitations

  1. Refer to Data Types for limitations related to data types support.
  2. GPU
    • No support.

Performance Tips

  1. Whenever possible, avoid specifying the destination memory format so that the primitive is able to choose the most appropriate one.