def plot_curves(i_batch, adv_loss, gen_loss, l1_reg, cols):
    """Plot SAM's various losses."""
    from matplotlib import pyplot as plt
    if i_batch == 0:
        try:
            ax.clear()
            ax.plot(range(len(adv_plt)), adv_plt, "r-",
                    linewidth=1.5, markersize=4,
                    label="Discriminator")
            ax.plot(range(len(adv_plt)), gen_plt, "g-", linewidth=1.5,
                    markersize=4, label="Generators")
            ax.plot(range(len(adv_plt)), l1_plt, "b-",
                    linewidth=1.5, markersize=4,
                    label="L1-Regularization")
            plt.legend()

            adv_plt.append(adv_loss.cpu().data[0])
            gen_plt.append(gen_loss.cpu().data[0] / cols)
            l1_plt.append(l1_reg.cpu().data[0])

            plt.pause(0.0001)

        except NameError:
            plt.ion()
            fig, ax = plt.figure()
            plt.xlabel("Epoch")
            plt.ylabel("Losses")

            plt.pause(0.0001)

            adv_plt = [adv_loss.cpu().data[0]]
            gen_plt = [gen_loss.cpu().data[0] / cols]
            l1_plt = [l1_reg.cpu().data[0]]

    else:
        adv_plt.append(adv_loss.cpu().data[0])
        gen_plt.append(gen_loss.cpu().data[0] / cols)
        l1_plt.append(l1_reg.cpu().data[0])
def plot_curves(i_batch, adv_loss, gen_loss, l1_reg, cols):
    """Plot SAM's various losses."""
    from matplotlib import pyplot as plt
    if i_batch == 0:
        try:
            ax.clear()
            ax.plot(range(len(adv_plt)), adv_plt, "r-",
                    linewidth=1.5, markersize=4,
                    label="Discriminator")
            ax.plot(range(len(adv_plt)), gen_plt, "g-", linewidth=1.5,
                    markersize=4, label="Generators")
            ax.plot(range(len(adv_plt)), l1_plt, "b-",
                    linewidth=1.5, markersize=4,
                    label="L1-Regularization")
            plt.legend()

            adv_plt.append(adv_loss.cpu().data[0])
            gen_plt.append(gen_loss.cpu().data[0] / cols)
            l1_plt.append(l1_reg.cpu().data[0])

            plt.pause(0.0001)

        except NameError:
            plt.ion()
            fig, ax = plt.figure()
            plt.xlabel("Epoch")
            plt.ylabel("Losses")

            plt.pause(0.0001)

            adv_plt = [adv_loss.cpu().data[0]]
            gen_plt = [gen_loss.cpu().data[0] / cols]
            l1_plt = [l1_reg.cpu().data[0]]

    else:
        adv_plt.append(adv_loss.cpu().data[0])
        gen_plt.append(gen_loss.cpu().data[0] / cols)
        l1_plt.append(l1_reg.cpu().data[0])
def plot_curves ( i_batch , adv_loss , gen_loss , l1_reg , cols ) : from matplotlib import pyplot as plt if i_batch == 0 : try : ax . clear ( ) ax . plot ( range ( len ( adv_plt ) ) , adv_plt , "r-" , linewidth = 1.5 , markersize = 4 , label = "Discriminator" ) ax . plot ( range ( len ( adv_plt ) ) , gen_plt , "g-" , linewidth = 1.5 , markersize = 4 , label = "Generators" ) ax . plot ( range ( len ( adv_plt ) ) , l1_plt , "b-" , linewidth = 1.5 , markersize = 4 , label = "L1-Regularization" ) plt . legend ( ) adv_plt . append ( adv_loss . cpu ( ) . data [ 0 ] ) gen_plt . append ( gen_loss . cpu ( ) . data [ 0 ] / cols ) l1_plt . append ( l1_reg . cpu ( ) . data [ 0 ] ) plt . pause ( 0.0001 ) except NameError : plt . ion ( ) fig , ax = plt . figure ( ) plt . xlabel ( "Epoch" ) plt . ylabel ( "Losses" ) plt . pause ( 0.0001 ) adv_plt = [ adv_loss . cpu ( ) . data [ 0 ] ] gen_plt = [ gen_loss . cpu ( ) . data [ 0 ] / cols ] l1_plt = [ l1_reg . cpu ( ) . data [ 0 ] ] else : adv_plt . append ( adv_loss . cpu ( ) . data [ 0 ] ) gen_plt . append ( gen_loss . cpu ( ) . data [ 0 ] / cols ) l1_plt . append ( l1_reg . cpu ( ) . data [ 0 ] )
Plot SAM's various losses.
Plot SAM s various losses .