Loading examples/notebooks/Explaining_Tox21.ipynb +2 −2 Original line number Diff line number Diff line Loading @@ -97,7 +97,7 @@ " dc.metrics.roc_auc_score, np.mean, mode=\"classification\")\n", "\n", "nb_epoch = 10\n", "model = dc.models.tensorgraph.fcnet.MultitaskClassifier(\n", "model = dc.models.MultitaskClassifier(\n", " len(tox21_tasks),\n", " train_dataset.get_data_shape()[0])\n", "\n", Loading Loading @@ -168,7 +168,7 @@ "# We need a function which takes a 2d numpy array (samples, features) and returns predictions (samples,)\n", "def eval_model(my_model, transformers):\n", " def eval_closure(x):\n", " ds = dc.data.NumpyDataset(x, None, None, None, n_tasks=n_tasks)\n", " ds = dc.data.NumpyDataset(x, None, None, None, n_tasks=len(tox21_tasks))\n", " # The 0th task is NR-AR\n", " predictions = model.predict(ds)[:,0]\n", " return predictions\n", Loading
examples/notebooks/Explaining_Tox21.ipynb +2 −2 Original line number Diff line number Diff line Loading @@ -97,7 +97,7 @@ " dc.metrics.roc_auc_score, np.mean, mode=\"classification\")\n", "\n", "nb_epoch = 10\n", "model = dc.models.tensorgraph.fcnet.MultitaskClassifier(\n", "model = dc.models.MultitaskClassifier(\n", " len(tox21_tasks),\n", " train_dataset.get_data_shape()[0])\n", "\n", Loading Loading @@ -168,7 +168,7 @@ "# We need a function which takes a 2d numpy array (samples, features) and returns predictions (samples,)\n", "def eval_model(my_model, transformers):\n", " def eval_closure(x):\n", " ds = dc.data.NumpyDataset(x, None, None, None, n_tasks=n_tasks)\n", " ds = dc.data.NumpyDataset(x, None, None, None, n_tasks=len(tox21_tasks))\n", " # The 0th task is NR-AR\n", " predictions = model.predict(ds)[:,0]\n", " return predictions\n",
