bda4689a2792e3b4a9e93b8d4fead564c27316d8,examples/mnist/mnist_env_test.py,,,#,35

Before Change

		input_exc_weights = network.connections[("X", "Ae")].w
		square_weights = get_square_weights(input_exc_weights.view(784, n_neurons), n_sqrt)
		square_assignments = get_square_assignments(assignments, n_sqrt)
		_voltages = {"Ae" : voltages["Ae"].get("v"), "Ai" : voltages["Ai"].get("v")}
		
		if i == 0:
			// inpt_axes, inpt_ims = plot_input(images[i].view(28, 28), inpt.t(), label=labels[i])
			weights_im = plot_weights(square_weights)

After Change

	// Optionally plot various simulation information.
	if plot:
		image = pipeline.obs.view(28, 28)
		inpt = pipeline.encoded.view(time, 784).sum(0).view(28, 28)
		input_exc_weights = network.connections[("X", "Ae")].w
		square_weights = get_square_weights(input_exc_weights.view(784, n_neurons), n_sqrt)
		square_assignments = get_square_assignments(assignments, n_sqrt)
		

Instances