Torch working

notebooks/model-training-v1.ipynb

@@ -51,6 +51,14 @@
     "        print(f\"{class_name}: {count} images\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "64122ad4",
+   "metadata": {},
+   "source": [
+    "Check out sample image from dataset"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -91,6 +99,80 @@
     "plt.title(first_class)\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c19ec00a",
+   "metadata": {},
+   "source": [
+    "Ensure that all images are RGB, all of same resolution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3cedd586",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Unique sizes: {(64, 64)}\n",
+      "Unique modes: {'RGB'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "sizes = set()\n",
+    "modes = set()\n",
+    "\n",
+    "for class_name in os.listdir(data_dir):\n",
+    "    class_path = os.path.join(data_dir, class_name)\n",
+    "    if not os.path.isdir(class_path):\n",
+    "        continue\n",
+    "    for img_name in os.listdir(class_path):\n",
+    "        img = Image.open(os.path.join(class_path, img_name))\n",
+    "        sizes.add(img.size)\n",
+    "        modes.add(img.mode)\n",
+    "\n",
+    "print(f\"Unique sizes: {sizes}\")\n",
+    "print(f\"Unique modes: {modes}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "88ac961b",
+   "metadata": {},
+   "source": [
+    "Ensure that torch works with GPU (5080) [Credit: Claude]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "8f556b22",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True\n",
+      "NVIDIA GeForce RTX 5080\n",
+      "GPU works! torch.Size([1000, 1000])\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "print(torch.cuda.is_available())  \n",
+    "print(torch.cuda.get_device_name(0)) \n",
+    "\n",
+    "x = torch.randn(1000, 1000).cuda()\n",
+    "y = x @ x\n",
+    "print(\"GPU works!\", y.shape)"
+   ]
   }
  ],
  "metadata": {

requirements.txt

@@ -1,22 +1,46 @@
 asttokens==3.0.1
 comm==0.2.3
 contourpy==1.3.3
+cuda-bindings==12.9.4
+cuda-pathfinder==1.2.2
+cuda-toolkit==12.8.1
 cycler==0.12.1
 debugpy==1.8.20
 decorator==5.2.1
 executing==2.2.1
+filelock==3.25.2
 fonttools==4.62.1
+fsspec==2026.2.0
 ipykernel==7.2.0
 ipython==9.10.0
 ipython_pygments_lexers==1.1.1
 jedi==0.19.2
+Jinja2==3.1.6
 jupyter_client==8.8.0
 jupyter_core==5.9.1
 kiwisolver==1.5.0
+MarkupSafe==3.0.2
 matplotlib==3.10.8
 matplotlib-inline==0.2.1
+mpmath==1.3.0
 nest-asyncio==1.6.0
+networkx==3.6.1
 numpy==2.4.3
+nvidia-cublas-cu12==12.8.4.1
+nvidia-cuda-cupti-cu12==12.8.90
+nvidia-cuda-nvrtc-cu12==12.8.93
+nvidia-cuda-runtime-cu12==12.8.90
+nvidia-cudnn-cu12==9.20.0.48
+nvidia-cufft-cu12==11.3.3.83
+nvidia-cufile-cu12==1.13.1.3
+nvidia-curand-cu12==10.3.9.90
+nvidia-cusolver-cu12==11.7.3.90
+nvidia-cusparse-cu12==12.5.8.93
+nvidia-cusparselt-cu12==0.7.1
+nvidia-nccl-cu12==2.29.7
+nvidia-nvjitlink-cu12==12.8.93
+nvidia-nvshmem-cu12==3.4.5
+nvidia-nvtx-cu12==12.8.90
 packaging==26.0
 parso==0.8.6
 pexpect==4.9.0
@@ -32,7 +56,12 @@ python-dateutil==2.9.0.post0
 pyzmq==27.1.0
 six==1.17.0
 stack-data==0.6.3
+sympy==1.14.0
+torch==2.12.0.dev20260318+cu128
+torchaudio==2.11.0.dev20260318+cu128
+torchvision==0.26.0.dev20260318+cu128
 tornado==6.5.5
 traitlets==5.14.3
+triton==3.6.0+git9844da95
 typing_extensions==4.15.0
 wcwidth==0.6.0