Difference between GDAS variants

[D-X-Y]

Which Algorithm
GDAS: Searching for A Robust Neural Architecture in Four GPU Hours

Describe the Question
In search_cells.py, there are two kinds of GDAS implementations:

• First, self._ops[index](x) * weights[index]
• Second, weights[_ie] * edge(nodes[j]) if _ie == argmaxs else weights[_ie] for _ie, edge in enumerate(self.edges[node_str])

[D-X-Y]

Make a commitment to ablatively study this issue.

[D-X-Y]

TODO:

Run
python ./exps/NATS-algos/search-cell.py --dataset cifar10 --data_path $TORCH_HOME/cifar.python --algo gdas_v1 --rand_seed 777
and
python ./exps/NATS-algos/search-cell.py --dataset cifar10 --data_path $TORCH_HOME/cifar.python --algo gdas --rand_seed 777 to see the performance difference.

[Xiao-congxi]

May I ask the author if you have conducted experimental comparisons between these two implementations? Will they bring significant differences?