remove /nfs from official docs

Author: romankouz

scratch/animal-filtering.ipynb

@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 8,
    "id": "brutal-safety",
    "metadata": {},
    "outputs": [],
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 9,
    "id": "animated-chrome",
    "metadata": {},
    "outputs": [],
@@ -30,24 +30,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "id": "floppy-melissa",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(array(['Female', 'Male'], dtype=object),\n",
-       " array(['Naive', 'Parenting', 'Virgin Parenting', 'Aggression to pup',\n",
-       "        'Aggression to adult', 'Mating'], dtype=object),\n",
-       " array(['Astrocyte', 'Inhibitory', 'OD Mature 2', 'Endothelial 1',\n",
-       "        'Ambiguous', 'Pericytes', 'Endothelial 2', 'OD Mature 1',\n",
-       "        'OD Immature 1', 'Excitatory', 'Microglia', 'Endothelial 3',\n",
-       "        'OD Mature 4', 'OD Immature 2', 'OD Mature 3', 'Ependymal'],\n",
-       "       dtype=object))"
+       "(array(['Male'], dtype=object),\n",
+       " array(['Naive'], dtype=object),\n",
+       " array(['Excitatory'], dtype=object))"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }

spatial/train_xenium.py

@@ -53,10 +53,7 @@ def setup_logger(cfg, filepath):
 def setup_checkpoint_callback(cfg, logger, filepath):
     callbacks = []
     if cfg.training.trainer.enable_checkpointing:
-        checkpoint_dir = os.path.join(
-            "/nfs/turbo/lsa-regier/scratch/roko/output/lightning_logs/checkpoints",
-            f"{cfg.model.name}Xenium",
-        )
+        checkpoint_dir = f"lightning_logs/checkpoints/{cfg.model.name}Xenium"
         # checkpoint_dir = os.path.join(cfg.paths.output, checkpoint_dir)
         checkpoint_callback = ModelCheckpoint(
             dirpath=checkpoint_dir,
@@ -207,10 +204,8 @@ def train(cfg: DictConfig, data=None, validate_only=False, lightning_integration
                     num_workers=2,
                 )
                 if validate_only:
-                    checkpoint_dir = os.path.join(
-                        "/nfs/turbo/lsa-regier/scratch/roko",
-                        "output/lightning_logs/checkpoints",
-                        f"{cfg.model.name}Xenium",
+                    checkpoint_dir = (
+                        f"lightning_logs/checkpoints/{cfg.model.name}Xenium"
                     )
                     ckpt_path_for_validation = os.path.join(
                         checkpoint_dir, cfg.training.filepath + ".ckpt"
@@ -222,10 +217,8 @@ def train(cfg: DictConfig, data=None, validate_only=False, lightning_integration
                     trainer.fit(model, datamodule)
             else:
                 if validate_only:
-                    checkpoint_dir = os.path.join(
-                        "/nfs/turbo/lsa-regier/scratch/roko",
-                        "output/lightning_logs/checkpoints",
-                        f"{cfg.model.name}Xenium",
+                    checkpoint_dir = (
+                        f"lightning_logs/checkpoints/{cfg.model.name}Xenium"
                     )
                     ckpt_path_for_validation = os.path.join(
                         checkpoint_dir, cfg.training.filepath + ".ckpt"
@@ -263,11 +256,7 @@ def train(cfg: DictConfig, data=None, validate_only=False, lightning_integration
                 num_workers=2,
             )
             if validate_only:
-                checkpoint_dir = os.path.join(
-                    "/nfs/turbo/lsa-regier/scratch/roko",
-                    "output/lightning_logs/checkpoints",
-                    f"{cfg.model.name}Xenium",
-                )
+                checkpoint_dir = f"lightning_logs/checkpoints/{cfg.model.name}Xenium"
                 # checkpoint_dir = os.path.join(cfg.paths.output, checkpoint_dir)
                 ckpt_path_for_validation = os.path.join(
                     checkpoint_dir, cfg.training.filepath + ".ckpt"
@@ -278,11 +267,7 @@ def train(cfg: DictConfig, data=None, validate_only=False, lightning_integration
 
         else:
             if validate_only:
-                checkpoint_dir = os.path.join(
-                    "/nfs/turbo/lsa-regier/scratch/roko",
-                    "output/lightning_logs/checkpoints",
-                    f"{cfg.model.name}Xenium",
-                )
+                checkpoint_dir = f"lightning_logs/checkpoints/{cfg.model.name}Xenium"
                 # checkpoint_dir = os.path.join(cfg.paths.output, checkpoint_dir)
                 ckpt_path_for_validation = os.path.join(
                     checkpoint_dir, cfg.training.filepath + ".ckpt"