Exampled tested and updated

Author: VincentStimper

example/real_nvp.ipynb

@@ -40,8 +40,8 @@
     "b = torch.Tensor([1 if i % 2 == 0 else 0 for i in range(latent_size)])\n",
     "flows = []\n",
     "for i in range(K):\n",
-    "    s = nf.nets.MLP([latent_size, 2 * latent_size, latent_size], init_zeros=True)#, output_fn=\"tanh\", output_scale=3.)\n",
-    "    t = nf.nets.MLP([latent_size, 2 * latent_size, latent_size], init_zeros=True)#, output_fn=\"tanh\", output_scale=3.)\n",
+    "    s = nf.nets.MLP([latent_size, 2 * latent_size, latent_size], init_zeros=True)\n",
+    "    t = nf.nets.MLP([latent_size, 2 * latent_size, latent_size], init_zeros=True)\n",
     "    if i % 2 == 0:\n",
     "        flows += [nf.flows.MaskedAffineFlow(b, s, t)]\n",
     "    else:\n",
@@ -135,8 +135,6 @@
     "        log_prob = nfm.log_prob(zz).to('cpu').view(*xx.shape)\n",
     "        prob = torch.exp(log_prob)\n",
     "        prob[torch.isnan(prob)] = 0\n",
-    "        #np.save('/scratch2/vs488/lectures/aml/optimization/log/no_annealing_real_nvp_prob_%06i.npy' % (it + 1),\n",
-    "        #        prob.data.numpy())\n",
     "\n",
     "        plt.figure(figsize=(15, 15))\n",
     "        plt.pcolormesh(xx, yy, prob.data.numpy())\n",
@@ -167,18 +165,11 @@
     "plt.gca().set_aspect('equal', 'box')\n",
     "plt.show()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -192,7 +183,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.11"
   }
  },
  "nbformat": 4,