ops) will be placed in the graph. This is used to produce the
      desired reference patterns understood by the backend. Weighted
      ops such as linear and conv require different observers (or
      quantization parameters passed to quantize ops in the reference
      model) for the input and the output.
  There are two observation types:

     *OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT* (default): the
     output observer instance will be different from the input.
     This is the most common observation type.

     *OUTPUT_SHARE_OBSERVER_WITH_INPUT*: the output observer
     instance will be the same as the input. This is useful for
     operators like *cat*.

  Note: This will be renamed in the near future, since we will
  soon insert QuantDeQuantStubs with observers (and fake
  quantizes) attached instead of observers themselves.

  Return type:
     *BackendPatternConfig*

set_pattern(pattern)
  Set the pattern to configure.
