minor fixes to linear regression notebook

Author: paul-buerkner

examples/Linear_Regression_Starter.ipynb

@@ -28,28 +28,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2025-02-14T10:51:27.573003Z",
      "start_time": "2025-02-14T10:51:27.568939Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING:bayesflow:\n",
-      "When using torch backend, we need to disable autograd by default to avoid excessive memory usage. Use\n",
-      "\n",
-      "with torch.enable_grad():\n",
-      "    ...\n",
-      "\n",
-      "in contexts where you need gradients (e.g. custom training loops).\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import numpy as np\n",
     "\n",
@@ -598,7 +584,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2025-02-14T10:52:51.132695Z",
@@ -618,7 +604,7 @@
     }
    ],
    "source": [
-    "f = bf.diagnostics.plots.loss(history, )"
+    "f = bf.diagnostics.plots.loss(history)"
    ]
   },
   {
@@ -964,27 +950,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2025-04-21 11:54:04.969579: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
-      "2025-04-21 11:54:04.977366: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
-      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
-      "E0000 00:00:1745250844.984817 4140753 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
-      "E0000 00:00:1745250844.987174 4140753 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
-      "W0000 00:00:1745250844.993850 4140753 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "W0000 00:00:1745250844.993860 4140753 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "W0000 00:00:1745250844.993861 4140753 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "W0000 00:00:1745250844.993863 4140753 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
-      "2025-04-21 11:54:04.996047: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
-      "To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Recommended - full serialization (checkpoints folder must exist)\n",
     "workflow.approximator.save(filepath=\"checkpoints/regression.keras\")\n",
@@ -1002,18 +970,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/radevs/anaconda3/envs/bf/lib/python3.11/site-packages/keras/src/saving/serialization_lib.py:734: UserWarning: `compile()` was not called as part of model loading because the model's `compile()` method is custom. All subclassed Models that have `compile()` overridden should also override `get_compile_config()` and `compile_from_config(config)`. Alternatively, you can call `compile()` manually after loading.\n",
-      "  instance.compile_from_config(compile_config)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Load approximator\n",
     "approximator = keras.saving.load_model(\"checkpoints/regression.keras\")"
@@ -1052,13 +1011,6 @@
     "    variable_names=par_names\n",
     ")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -1073,16 +1025,7 @@
    "name": "python3"
   },
   "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.11"
+   "name": "python"
   },
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {