Deep Neural Network Library (DNNL) has both C and C++ APIs available to users for convenience. There is almost a one-to-one correspondence as far as features are concerned, so users can choose based on language preference and switch back and forth in their projects if they desire. Most of the users choose C++ API though.

The differences are shown in the table below.

Features	C API	**
Language requirements	C99	C++11 and above
Functional coverage	Full	Some of the features may require involving C API
Error handling	Functions return status	Functions throw exceptions
Verbosity	High	Medium
Implementation	Completely inside the library	Header-based thin wrapper around C API with syntactic sugar mostly for convenience
Purpose	Provide simple API and stable ABI to the library	Improve usability
Target audience	Experienced users, FFI	Most of the users and framework developers

Input validation notes

DNNL performs limited input validation to minimize the performance overheads. The user application is responsible for sanitizing inputs passed to the library. Examples of the inputs that may result in unexpected consequences:

Not-a-number (NaN) floating point values
Large u8 or s8 inputs may lead to accumulator overflow
While the bf16 16-bit floating point data type has range close to 32-bit floating point data type, there is a significant reduction in precision.

As DNNL API accepts raw pointers as parameters it's the calling code responsibility to

Allocate memory and validate the buffer sizes before passing them to the library
Ensure that the data buffers do not overlap unless the functionality explicitly permits in-place computations