run notebooks

single-cell-data · Sep 17, 2024 · e66b4c2 · e66b4c2
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diff --git a/other_packages/python/tiledbsoma_ml/notebooks/tutorial_lightning.ipynb b/other_packages/python/tiledbsoma_ml/notebooks/tutorial_lightning.ipynb
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -43,7 +43,7 @@
     "    CZI_Census_Homo_Sapiens_URL,\n",
     "    context=soma.SOMATileDBContext(tiledb_config={\"vfs.s3.region\": \"us-west-2\"}),\n",
     ")\n",
-    "obs_value_filter = \"tissue_general == 'lung' and is_primary_data == True\"\n",
+    "obs_value_filter = \"tissue_general == 'tongue' and is_primary_data == True\"\n",
     "\n",
     "with experiment.axis_query(\n",
     "    measurement_name=\"RNA\", obs_query=soma.AxisQuery(value_filter=obs_value_filter)\n",
@@ -57,7 +57,8 @@
     "        obs_column_names=[\"cell_type\"],\n",
     "        batch_size=128,\n",
     "        shuffle=True,\n",
-    "    )\n"
+    "        seed=12345,\n",
+    "    )"
    ]
   },
   {
@@ -69,7 +70,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -116,7 +117,7 @@
     "\n",
     "    def configure_optimizers(self):\n",
     "        optimizer = torch.optim.Adam(self.parameters(), lr=self.learning_rate)\n",
-    "        return optimizer\n"
+    "        return optimizer"
    ]
   },
   {
@@ -128,11 +129,76 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "GPU available: True (cuda), used: True\n",
+      "TPU available: False, using: 0 TPU cores\n",
+      "HPU available: False, using: 0 HPUs\n",
+      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
+      "\n",
+      "  | Name    | Type             | Params | Mode \n",
+      "-----------------------------------------------------\n",
+      "0 | linear  | Linear           | 726 K  | train\n",
+      "1 | loss_fn | CrossEntropyLoss | 0      | train\n",
+      "-----------------------------------------------------\n",
+      "726 K     Trainable params\n",
+      "0         Non-trainable params\n",
+      "726 K     Total params\n",
+      "2.905     Total estimated model params size (MB)\n",
+      "2         Modules in train mode\n",
+      "0         Modules in eval mode\n",
+      "/home/ubuntu/miniforge3/envs/toymodel/lib/python3.11/site-packages/pytorch_lightning/utilities/data.py:122: Your `IterableDataset` has `__len__` defined. In combination with multi-process data loading (when num_workers > 1), `__len__` could be inaccurate if each worker is not configured independently to avoid having duplicate data.\n",
+      "/home/ubuntu/miniforge3/envs/toymodel/lib/python3.11/site-packages/torchdata/datapipes/__init__.py:18: UserWarning: \n",
+      "################################################################################\n",
+      "WARNING!\n",
+      "The 'datapipes', 'dataloader2' modules are deprecated and will be removed in a\n",
+      "future torchdata release! Please see https://github.com/pytorch/data/issues/1196\n",
+      "to learn more and leave feedback.\n",
+      "################################################################################\n",
+      "\n",
+      "  deprecation_warning()\n",
+      "/home/ubuntu/miniforge3/envs/toymodel/lib/python3.11/site-packages/torchdata/datapipes/__init__.py:18: UserWarning: \n",
+      "################################################################################\n",
+      "WARNING!\n",
+      "The 'datapipes', 'dataloader2' modules are deprecated and will be removed in a\n",
+      "future torchdata release! Please see https://github.com/pytorch/data/issues/1196\n",
+      "to learn more and leave feedback.\n",
+      "################################################################################\n",
+      "\n",
+      "  deprecation_warning()\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 19: 100%|██████████| 118/118 [00:17<00:00,  6.87it/s, v_num=6, train_loss=1.680, train_accuracy=0.977]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "`Trainer.fit` stopped: `max_epochs=20` reached.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 19: 100%|██████████| 118/118 [00:17<00:00,  6.86it/s, v_num=6, train_loss=1.680, train_accuracy=0.977]\n"
+     ]
+    }
+   ],
    "source": [
-    "dataloader = soma_ml.experiment_dataloader(experiment_dataset, num_workers=2, persistent_workers=True)\n",
+    "dataloader = soma_ml.experiment_dataloader(\n",
+    "    experiment_dataset, num_workers=2, persistent_workers=True\n",
+    ")\n",
     "\n",
     "# The size of the input dimension is the number of genes\n",
     "input_dim = experiment_dataset.shape[1]\n",
@@ -147,16 +213,16 @@
     "\n",
     "# Define the PyTorch Lightning Trainer\n",
     "trainer = pl.Trainer(\n",
-    "    max_epochs=10,\n",
+    "    max_epochs=20,\n",
     "    # accelerator=args.accelerator,\n",
     "    # strategy=\"ddp\",\n",
     ")\n",
     "\n",
     "# set precision\n",
-    "torch.set_float32_matmul_precision('medium')\n",
+    "torch.set_float32_matmul_precision(\"high\")\n",
     "\n",
     "# Train the model\n",
-    "trainer.fit(model, train_dataloaders=dataloader)\n"
+    "trainer.fit(model, train_dataloaders=dataloader)"
    ]
   }
  ],