gridsearch_optimizer.py 文件源码

def build_grid(self, grid_sizes):
        grid_dict = {}
        for param_name, param in self.param_dict.items():
            if param.param_type == 'continuous':
                grid_dict[param_name] = np.linspace(param.lower, param.upper, grid_sizes[param_name])
            elif param.param_type == 'integer':
                step_size = int(round((param.upper - param.lower)/float(grid_sizes[param_name])))
                grid_dict[param_name] = np.concatenate([np.arange(param.lower, param.upper, step_size), [param.upper]])
            elif param.param_type == 'categorical':
                grid_dict[param_name] = param.possible_values
            elif param.param_type == 'boolean':
                grid_dict[param_name] = [True, False]
        # now build the grid as a list with all possible combinations i.e. the cartesian product
        grid = []
        for params in list(itertools.product(*[[(k,v) for v in vals] for k, vals in grid_dict.items()])):
            grid.append(dict(params))
        return grid