gpu info

custom/gpulibs.Dockerfile

@@ -4,6 +4,7 @@ LABEL maintainer="Christoph Schranz <[email protected]>, Mat
 # https://www.tensorflow.org/install/source#gpu
 # installation via conda leads to errors in version 4.8.2
 # Install CUDA-specific nvidia libraries and update libcudnn8 before that
+# using device_lib.list_local_devices() the cudNN version is shown, adapt version to tested compat
 USER ${NB_UID}
 RUN pip install --upgrade pip && \
     pip install --no-cache-dir tensorflow==2.15.0 keras==2.15.0 && \

extra/Getting_Started/GPU-processing.ipynb

@@ -161,9 +161,10 @@
    ],
    "source": [
     "import tensorflow as tf\n",
+    "print(tf.test.is_built_with_cuda(), tf.config.list_physical_devices('GPU'))\n",
+    "\n",
     "from tensorflow.python.client import device_lib\n",
-    "print(tf.config.list_physical_devices('XLA_GPU'))\n",
-    "device_lib.list_local_devices()"
+    "print(device_lib.list_local_devices())"
    ]
   },
   {
@@ -390,7 +391,7 @@
    "outputs": [],
    "source": [
     "if torch.cuda.is_available():\n",
-    "    # Here is the memory of the GPU a border. \n",
+    "    # Here is the memory of the GPU a border.\n",
     "    # A matrix with 100000 lines requires 37 GB, but only 8 GB are available.\n",
     "    H = x.mm( (x.t().mm(x)).inverse() ).mm(x.t())"
    ]
@@ -438,7 +439,7 @@
    ],
    "source": [
     "if torch.cuda.is_available():\n",
-    "    # This operation is difficult, as an symmetric matrix is transferred \n",
+    "    # This operation is difficult, as an symmetric matrix is transferred\n",
     "    # back to the CPU. Is possible up to 30000 rows.\n",
     "    print(H.to(\"cpu\", torch.double)[0:5, 0:5])"
    ]