gistfile1.txt

def plot_decision_boundary_gpu(pred_func):
	# Set min and max values and give it some padding
    x_min, x_max = train_X[:, 0].min() - .5, train_X[:, 0].max() + .5
    y_min, y_max = train_X[:, 1].min() - .5, train_X[:, 1].max() + .5
    h = 0.01
    # Generate a grid of points with distance h between them
    xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))

    X.set_value((np.c_[xx.ravel(), yy.ravel()]).astype('float32'))
    #Z = pred_func(np.c_[xx.ravel(), yy.ravel()])
    Z = pred_func()
    Z = Z.reshape(xx.shape)

    # Plot the contour and training examples
    plt.contourf(xx, yy, Z, cmap=plt.cm.Spectral)
    plt.scatter(train_X[:, 0], train_X[:, 1], c=train_y, cmap=plt.cm.Spectral)