How to use the netron.solvers.GridSearch.GridSearch function in netron

loss_type = self.grid.params_grid["loss"][0]
        for layers in self.create_network_structures(self.grid.params_grid["layers"], self.grid.params_grid["layer_nums"], input_shape):
            print "Current network: %s" % "->".join(layers)
            flat_params_grid = self.grid.create_flat_layers_grid(layers, input_shape, output_dim)
            for optimizer_name in self.grid.params_grid["optimizers"]:
                flat_grid = flat_params_grid.copy()
                flat_grid.update(self.grid.create_flat_optimizer_grid(optimizer_name))
                for params in ParameterGrid(flat_grid):
                    nn_params = self.grid.fold_params(params)
                    yield self.model_factory.create_model(layers, nn_params, loss_type)

# Example.
if __name__ == "__main__":
    import sys

    job_stream = GridSearch(sys.argv[1], [1], 1, "keras", "sin_data.npz")
    for i in range(5):
        print "Model #" + str(i)
        print "=" * 10
        print job_stream.get_new_job(worker_id = 1)