Deep Neural Network Library (DNNL)  1.2.0
Performance library for Deep Learning
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Primitive Attributes

A quick recap of the primitive creation step, which consists of the following:

  1. Initializing an operation descriptor, which contains some basic information about the operation.
  2. Creating a primitive descriptor based on the operation descriptor, engine, and attributes. During creation of a primitive for backward propagation, the primitive descriptor from the forward propagation might be required as well (see Training-Specific Aspects).
  3. Creating a primitive, solely based on a primitive descriptor.

Details on why all these steps are required can be found in Basic Concepts. The fact that is important for us now is that a primitive descriptor created at step 2 fully defines the operation that the corresponding primitive will execute. Once the primitive descriptor is created, it cannot be changed.

The parameters passed to create a primitive descriptor specify the problem. An engine specifies where the primitive will be executed. An operation descriptor specifies the basics: the operation kind; the propagation kind; the source, destination, and other tensors; the strides (if applicable); and so on.

Attributes specify some extra properties of the primitive. The attributes were designed to be extensible, hence they are an opaque structure. Users must create them before use and must set required specifics using the corresponding setters. The attributes are copied during primitive descriptor creation, so users can change or destroy attributes right after that.

If nothing special is required, attributes can stay empty, which is equivalent to the default attributes. For that purpose in the C API users can pass NULL as an attribute to the dnnl_primitive_desc_create function. In the C++ API, primitive descriptors' constructors have empty attributes as default parameters, so unless required users can simply omit them.

Attributes Usage

Below are the skeletons of using attributes with the C and C++ APIs. Error handling is omitted to simplify reading.

// ### C API ###
dnnl_op_desc_t op_d; // some operation descriptor, e.g. dnnl_eltwise_desc_t
...
// init op_d
dnnl_primitive_attr_t attr; // opaque attributes
dnnl_primitive_attr_set_SOMETHING(attr, params); // setting attributes params
dnnl_primitive_attr_set_SOMETHING_ELSE(attr, other_params);
dnnl_primitive_desc_t op_pd; // operation primitive descriptor
dnnl_primitive_desc_create(&op_pd, &op_d, attr, engine, hint_fwd_pd);
// changing attr object here doesn't have any effect on op_pd
// once attr is no more used we can immediately destroy it
...
// ### C++ API ###
dnnl::primitive_attr attr;
attr.set_SOMETHING(params);
attr.set_SOMETHING_ELSE(params);
primitive::primitive_desc pd(..., attr);
// in C++ destroying of attr happens automatically

Supported Attributes

As mentioned above, the attributes enable extending or changing the default primitive behavior. Currently the following attributes are supported. The detailed explanation is provided in the corresponding sections.

Attribute Related Error Handling

Unfortunately, the attribute extension API allows specifying properties that the library currently doesn't support. Since the attributes are created separately from the corresponding primitive descriptor, users can successfully set attributes in whatever configuration they want. However, when they try to create a primitive descriptor with the attribute it might appear that neither implementation supports such a configuration. In this case a user will get dnnl_unimplemented in the case of the C API or a corresponding dnnl::error object as an exception in the case of the C++ API. Unfortunately, the library doesn't currently provide any hints about what exactly is going wrong in this case. The corresponding section of the documentation simply documents the primitives' capabilities.

Warning
Error handling of attributes might be complicated and obscure.