import numpy as np
import math

if __name__ == '__main__':
    raise DeprecationWarning("This should not be used, lazygrid of skluc should be used instead")

    batch_size = np.logspace(3, 9, dtype=int, base=2, num=4)
    num_epoch = 100
    # sigma = np.logspace(-1, 2, base=10, num=3)
    sigma = [1]
    # gamma = np.logspace(-4, 0, base=10, num=3)
    gamma = [1]
    subsample_size = np.logspace(3, 9, dtype=int, base=2, num=4)
    networks_types = ["dense", "deepfriedconvnet", "deepstorm"]
    datasets = ["cifar"]
    output_dense = 2048
    nys_layer_dim_out = np.logspace(3, int(math.log(output_dense, 2)), dtype=int, base=2, num=3)
    for d in datasets:
        for network in networks_types:
            s_network = network + " " + "--" + str(d) + " " + "--time" + " " + "--test" + " " + "-e" + " " + str(num_epoch) + " "
            for b_size in batch_size:
                s_epoch = s_network + "-s " + str(b_size) + " "
                if network == "deepfriedconvnet":
                    for sig in sigma:
                        s_sigma = s_epoch + "-S " + "{:.5f}".format(sig)
                        print(s_sigma)
                elif network == "deepstorm":
                    for gam in gamma:
                        s_gamma = s_epoch + "-G " + "{:.5f}".format(gam) + " "
                        for nys_size in subsample_size:
                            s_nys = s_gamma + "-m " + str(nys_size) + " "
                            for nys_output_size in nys_layer_dim_out:
                                s_nys_out = s_nys + "-w" + " " + str(nys_output_size)
                                print(s_nys_out)
                else:
                    print(s_epoch)
                    pass