MGN benchmark

Author: GuillaumeBroggi

.gitignore

@@ -178,7 +178,7 @@ benchmarks/cfd/gnn_porous_medium/*
 !benchmarks/cfd/gnn_porous_medium/gnn_porous_medium.ipynb
 !benchmarks/cfd/gnn_porous_medium/_assets
 benchmarks/cfd/mgn_cylinder_flow/*
-!benchmarks/cfd/mgn_cylinder_flow/gnn_cylinder_flow.ipynb
+!benchmarks/cfd/mgn_cylinder_flow/mgn_cylinder_flow.ipynb
 !benchmarks/cfd/mgn_cylinder_flow/_assets
 
 # Sphinx docs

benchmarks/cfd/gnn_porous_medium/gnn_porous_medium.ipynb

@@ -139,7 +139,10 @@
                 "    directory.mkdir(parents=True, exist_ok=True)\n",
                 "\n",
                 "# Add `notebook_connected` to the default renderer to ensure the figure are rendered in the the documentation\n",
-                "plotly_renderer = f\"notebook_connected+{pio.renderers.default}\""
+                "plotly_renderer = f\"notebook_connected+{pio.renderers.default}\"\n",
+                "\n",
+                "# Set device\n",
+                "device_type=\"cuda\" if torch.cuda.is_available() else \"cpu\""
             ]
         },
         {
@@ -1670,7 +1673,6 @@
                 "    sample_file_name = f\"porous_network_graph_{porous_network_id:04d}.pt\"\n",
                 "    # Set sample file path\n",
                 "    sample_file_path = directories[\"processed_data\"] / sample_file_name\n",
-                "    # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
                 "    # Save graph sample file\n",
                 "    torch.save(pyg_graph, sample_file_path)\n",
                 "    # Save graph sample file path\n",
@@ -1817,7 +1819,7 @@
                 "    dec_node_hidden_activ_type=\"leakyrelu\",\n",
                 "    dec_node_output_activ_type=\"identity\",\n",
                 "    # Set device\n",
-                "    device_type=\"cuda\" if torch.cuda.is_available() else \"cpu\",\n",
+                "    device_type=device_type,\n",
                 ")"
             ]
         },
@@ -1883,6 +1885,10 @@
                 "    # Set verbosity\n",
                 "    is_verbose=True,\n",
                 "    tqdm_flavor=\"notebook\",\n",
+                "    # Save loss history\n",
+                "    save_loss_every=1,\n",
+                "    # Set device\n",
+                "    device_type=device_type,\n",
                 ")\n",
                 "\n",
                 "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
@@ -2930,8 +2936,6 @@
                 }
             ],
             "source": [
-                "from plotly import graph_objects as go\n",
-                "\n",
                 "with open(directories[\"model\"] / \"loss_history_record.pkl\", \"rb\") as f:\n",
                 "    loss_history_record = pickle.load(f)\n",
                 "\n",
@@ -2998,7 +3002,7 @@
                 "    loss_kwargs={},\n",
                 "    is_normalized_loss=False,\n",
                 "    dataset_file_path=test_dataset_file_path,\n",
-                "    device_type=\"cuda\" if torch.cuda.is_available() else \"cpu\",\n",
+                "    device_type=device_type,\n",
                 "    seed=None,\n",
                 "    is_verbose=True,\n",
                 "    tqdm_flavor=\"notebook\",\n",