def _from_human_readable_architecture()

in nni/nas/pytorch/fixed.py [0:0]

• 19 lines of code
• 29 McCabe index (conditional complexity)

    def _from_human_readable_architecture(self, human_arc):
        # convert from an exported architecture
        result_arc = {k: to_list(v) for k, v in human_arc.items()}  # there could be tensors, numpy arrays, etc.
        # First, convert non-list to list, because there could be {"op1": 0} or {"op1": "conv"},
        # which means {"op1": [0, ]} ir {"op1": ["conv", ]}
        result_arc = {k: v if isinstance(v, list) else [v] for k, v in result_arc.items()}
        # Second, infer which ones are multi-hot arrays and which ones are in human-readable format.
        # This is non-trivial, since if an array in [0, 1], we cannot know for sure it means [false, true] or [true, true].
        # Here, we assume an multihot array has to be a boolean array or a float array and matches the length.
        for mutable in self.mutables:
            if mutable.key not in result_arc:
                continue  # skip silently
            choice_arr = result_arc[mutable.key]
            if all(isinstance(v, bool) for v in choice_arr) or all(isinstance(v, float) for v in choice_arr):
                if (isinstance(mutable, LayerChoice) and len(mutable) == len(choice_arr)) or \
                        (isinstance(mutable, InputChoice) and mutable.n_candidates == len(choice_arr)):
                    # multihot, do nothing
                    continue
            if isinstance(mutable, LayerChoice):
                choice_arr = [mutable.names.index(val) if isinstance(val, str) else val for val in choice_arr]
                choice_arr = [i in choice_arr for i in range(len(mutable))]
            elif isinstance(mutable, InputChoice):
                choice_arr = [mutable.choose_from.index(val) if isinstance(val, str) else val for val in choice_arr]
                choice_arr = [i in choice_arr for i in range(mutable.n_candidates)]
            result_arc[mutable.key] = choice_arr
        return result_arc