How params are converted and stored in lib.get_params()

ganler · March 24, 2022, 10:19pm

This is because relay.build optimizes the constants through constant folding. That said, those constants you marked have been folded and simplified.

Actually, it is simplified in the bind_params_by_name function in relay.build. And if you print the output module of that you see:

def @main(%input: Tensor[(7), int32]) -> Tensor[(7), int32] {
  %0 = (meta[relay.Constant][0], meta[relay.Constant][1]);
  %1 = concatenate(%0, axis=-1) /* ty=Tensor[(7), int32] */;
  add(%1, %input) /* ty=Tensor[(7), int32] */
}

You may also want to read the comments:

github.com

apache/tvm/blob/main/python/tvm/relay/build_module.py#L569


        tophub_context = autotvm.tophub.context(list(target.values()))
    else:
        tophub_context = autotvm.utils.EmptyContext()


    with tophub_context:
        bld_mod = BuildModule()
        mod, params = bld_mod.optimize(mod, target, params)
    return mod, params




def bind_params_by_name(func, params):
    """Bind params to function by name.
    This could be useful when assembling custom Relay optimization
    passes that involve constant folding.


    Parameters
    ----------
    func : relay.Function
        The function to bind parameters to.


    params : dict of str to NDArray