fix broken flags and deprecated functions

wandb · Dec 6, 2023 · 213e6a0 · 213e6a0
1 parent 126f134
commit 213e6a0
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Showing 2 changed files with 5 additions and 5 deletions.
diff --git a/colabs/pytorch-lightning/Fine_tuning_a_Transformer_with_Pytorch_Lightning.ipynb b/colabs/pytorch-lightning/Fine_tuning_a_Transformer_with_Pytorch_Lightning.ipynb
@@ -245,7 +245,7 @@
     "  \n",
     "  # Download the raw cola data from the 'zipfile' reference we added to the cola-raw artifact.\n",
     "  raw_data_artifact = run.use_artifact(\"cola-raw:latest\")\n",
-    "  zip_path = raw_data_artifact.get_path(\"zipfile\").download()\n",
+    "  zip_path = raw_data_artifact.get_entry(\"zipfile\").download()\n",
     "  !unzip -o $zip_path  # jupyter hack to unzip data :P\n",
     "  \n",
     "  # Read in the raw data, log it to W&B as a wandb.Table\n",
@@ -298,7 +298,7 @@
     "\n",
     "  # Download the preprocessed data\n",
     "  pp_data_artifact = run.use_artifact(\"preprocessed-data:latest\")\n",
-    "  data_path = pp_data_artifact.get_path(\"dataset\").download()\n",
+    "  data_path = pp_data_artifact.get_entry(\"dataset\").download()\n",
     "  dataset = torch.load(data_path)\n",
     "\n",
     "  # Calculate the number of samples to include in each set.\n",
@@ -410,8 +410,8 @@
     "\n",
     "    # Load the datasets from the split-dataset artifact\n",
     "    data = run.use_artifact(\"split-dataset:latest\")\n",
-    "    train_dataset = torch.load(data.get_path(\"train-data\").download())\n",
-    "    val_dataset = torch.load(data.get_path(\"validation-data\").download())\n",
+    "    train_dataset = torch.load(data.get_entry(\"train-data\").download())\n",
+    "    val_dataset = torch.load(data.get_entry(\"validation-data\").download())\n",
     "\n",
     "    # Extract the config object associated with the run\n",
     "    config = run.config\n",

diff --git a/colabs/pytorch-lightning/Profile_PyTorch_Code.ipynb b/colabs/pytorch-lightning/Profile_PyTorch_Code.ipynb
@@ -357,7 +357,7 @@
     "    with profiler:\n",
     "        profiler_callback = TorchTensorboardProfilerCallback(profiler)\n",
     "\n",
-    "        trainer = pl.Trainer(gpus=1, max_epochs=1, max_steps=total_steps,\n",
+    "        trainer = pl.Trainer(max_epochs=1, max_steps=total_steps,\n",
     "                            logger=pl.loggers.WandbLogger(log_model=True, save_code=True),\n",
     "                            callbacks=[profiler_callback], precision=wandb.config.precision)\n",
     "\n",