diff --git a/PyPOTS_Classification.ipynb b/PyPOTS_Classification.ipynb index c9c0af9..16a513f 100644 --- a/PyPOTS_Classification.ipynb +++ b/PyPOTS_Classification.ipynb @@ -116,7 +116,7 @@ " n_classes=physionet2012_dataset[\"n_classes\"],\n", " n_layers=2,\n", " d_model=physionet2012_dataset[\"n_features\"] * 4,\n", - " d_inner=256,\n", + " d_ffn=256,\n", " n_heads=2,\n", " dropout=0.3,\n", " batch_size=32,\n", diff --git a/PyPOTS_Imputation.ipynb b/PyPOTS_Imputation.ipynb index cad76ad..240b22f 100644 --- a/PyPOTS_Imputation.ipynb +++ b/PyPOTS_Imputation.ipynb @@ -111,7 +111,7 @@ " n_features=physionet2012_dataset['n_features'],\n", " n_layers=2,\n", " d_model=256,\n", - " d_inner=128,\n", + " d_ffn=128,\n", " n_heads=4,\n", " d_k=64,\n", " d_v=64,\n", @@ -245,7 +245,7 @@ " n_features=physionet2012_dataset['n_features'],\n", " n_layers=6,\n", " d_model=512,\n", - " d_inner=256,\n", + " d_ffn=256,\n", " n_heads=4,\n", " d_k=128,\n", " d_v=128,\n", @@ -530,7 +530,7 @@ " num_workers=0,\n", " # just leave it to default as None, PyPOTS will automatically assign the best device for you.\n", " # Set it as 'cpu' if you don't have CUDA devices. You can also set it to 'cuda:0' or 'cuda:1' if you have multiple CUDA devices, even parallelly on ['cuda:0', 'cuda:1']\n", - " device='cuda:1',\n", + " device=None,\n", " # set the path for saving tensorboard and trained model files \n", " saving_path=\"tutorial_results/imputation/csdi\",\n", " # only save the best model after training finished.\n", @@ -1047,10 +1047,8 @@ "source": [ "from pypots.optim import Adam\n", "from pypots.imputation import MRNN\n", - "from pypots.utils.metrics import cal_mae\n", "\n", "# initialize the model\n", - "# initialize the model\n", "mrnn = MRNN(\n", " n_steps=physionet2012_dataset['n_steps'],\n", " n_features=physionet2012_dataset['n_features'],\n",