def test_lifetime_sparsity_values(self):
feat_maps = np.zeros([10, 1, 1, 3])
feat_maps[:5, :, :, 1] = 1.0
feat_maps[..., 2] = 1.0
sparsity = lifetime_sparsity(feat_maps)
self.assertAlmostEqual(sparsity[0], 1.0)
self.assertAlmostEqual(sparsity[1], 0.55, places=1)
self.assertAlmostEqual(sparsity[2], 0.0)
# mean acts, mean sparsity, and number active
plt.errorbar(x = list(range(mean_acts.size)), y = mean_acts, yerr = se_acts)
plt.xlabel('Neuron Index')
plt.ylabel('Mean Activation +/- 1 SE')
plt.savefig(os.path.join(args.save_dir, 'mean_activations_line.png'), bbox_inches = 'tight')
plt.close()
seaborn.boxplot(y = mean_acts)
plt.ylabel('Mean Activation')
plt.savefig(os.path.join(args.save_dir, 'mean_activations_box.png'), bbox_inches = 'tight')
plt.close()
logging.info('PLOTTING LIFETIME SPARSITY')
lifetime = lifetime_sparsity(acts)
lifetime.sort()
plt.plot(lifetime[::-1])
plt.xlabel('Neuron Index')
plt.ylabel('Lifetime Sparsity')
plt.savefig(os.path.join(args.save_dir, 'lifetime_sparsity_line.png'), bbox_inches = 'tight')
plt.close()
seaborn.boxplot(y = lifetime)
plt.ylabel('Lifetime Sparsity')
plt.savefig(os.path.join(args.save_dir, 'lifetime_sparsity_box.png'), bbox_inches = 'tight')
plt.close()
logging.info('PLOTTING POPULATION SPARSITY')
def test_lifetime_sparsity_shape_hw_equal_1(self):
feat_maps = np.zeros([10, 1, 1, 7])
sparsity = lifetime_sparsity(feat_maps)
self.assertEqual(sparsity.size, 7)