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11 changes: 6 additions & 5 deletions notebooks/1_VAE_molecular.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,7 @@
" run_cmd('mv {}/* . '.format(GIT_NAME))\n",
" run_cmd('rm -rf {}'.format(GIT_NAME))\n",
" run_cmd('pip install --upgrade --force-reinstall tf-nightly-gpu-2.0-preview')\n",
" run_cmd('pip install --upgrade --force-reinstall tensorflow_probability==0.8.0rc0')\n",
"else:\n",
" SRC_DIR='..'\n",
" \n",
Expand Down Expand Up @@ -392,8 +393,8 @@
"source": [
"z = encoder.predict(x_test)\n",
"recon_x = decoder.predict(z)\n",
"print(np.abs(recon_x[0]-x[0]))\n",
"print(np.linalg.norm(recon_x[0]-x[0]))"
"print(np.abs(recon_x[0]-x_test[0]))\n",
"print(np.linalg.norm(recon_x[0]-x_test[0]))"
]
},
{
Expand Down Expand Up @@ -542,10 +543,10 @@
"\n",
"## Que esta pasando?\n",
"\n",
"* Iteratar sobre los datos en epochs\n",
"* En cada epoch, encodificamos, calculamos la media y log-varianza del posterior aproxiamdor $q(z|x)$\n",
"* Iterar sobre los datos en epochs\n",
"* En cada epoch, encodificamos, calculamos la media y log-varianza del posterior aproximador $q(z|x)$\n",
"* Usamos el truco de reparametrizacion para samplear de $q(z|x)$\n",
"* Nuestros samples reparametrizados se pasan al decoder para obtain logits de la distribucion generativa $p(x|z)$\n",
"* Nuestros samples reparametrizados se pasan al decoder para obtener logits de la distribucion generativa $p(x|z)$\n",
"\n",
"#### Funcion de perdida\n",
"\n",
Expand Down