def plot_penalties(): # Plot the results plt.clf() l1_color = 'r' l2_color = 'g' elastic_net_color = 'b' line = np.linspace(-1.5, 1.5, 1001) xx, yy = np.meshgrid(line, line) l2 = xx**2 + yy**2 l1 = np.abs(xx) + np.abs(yy) rho = 0.5 elastic_net = rho * l1 + (1 - rho) * l2 fig = plt.figure(figsize=(10, 10), dpi=100) ax = plt.gca() elastic_net_contour = plt.contour( xx, yy, elastic_net, levels=[1], colors=elastic_net_color ) l2_contour = plt.contour(xx, yy, l2, levels=[1], colors=l2_color) l1_contour = plt.contour(xx, yy, l1, levels=[1], colors=l1_color) ax.set_aspect("equal") ax.spines["left"].set_position("center") ax.spines["right"].set_color("none") ax.spines["bottom"].set_position("center") ax.spines["top"].set_color("none") plt.clabel( elastic_net_contour, inline=1, fontsize=18, fmt={1.0: "elastic-net"}, manual=[(-1, -1)],) plt.clabel(l2_contour, inline=1, fontsize=18, fmt={1.0: "L2"}, manual=[(-1, -1)]) plt.clabel(l1_contour, inline=1, fontsize=18, fmt={1.0: "L1"}, manual=[(-1, -1)]) plt.tight_layout() # plt.show() return fig title = "SGD Penalties" with gr.Blocks(title=title) as demo: gr.Markdown(f"# {title}") gr.Markdown(" **[Demo is based on sklearn docs](https://scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_penalties.html#sphx-glr-auto-examples-linear-model-plot-sgd-penalties-py)**") # greet_btn.click(fn=greet, inputs=name, outputs=output) x = gr.Dropdown(["red", "blue", "green"], label="l1_color", type="index"), y = gr.Dropdown(["red", "blue", "green"], label="l2_color", type="index"), z = gr.Dropdown(["red", "blue", "green"], label="elastic_net_color", type="index"), btn = gr.Button(value="Visualize SGD penalties") btn.click(plot_penalties, outputs= gr.Plot() ) # demo.launch()