run isort

examples/baseline.py

@@ -2,12 +2,11 @@
 from typing import Dict
 
 import torch
-from torch import Tensor
-from torchmetrics import AUROC, AveragePrecision, MeanAbsoluteError
-
 from rtb.data import Table
 from rtb.data.task import TaskType
 from rtb.datasets import get_dataset
+from torch import Tensor
+from torchmetrics import AUROC, AveragePrecision, MeanAbsoluteError
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--dataset", type=str, default="relbench-forum")

examples/fake/new_train.py

@@ -2,13 +2,12 @@
 
 import torch
 import torch.nn.functional as F
-from torch_geometric.loader import NodeLoader
-from torch_geometric.nn import MLP
-from torch_geometric.sampler import NeighborSampler
-
 from rtb.datasets import FakeProductDataset
 from rtb.external.graph import make_pkey_fkey_graph
 from rtb.external.nn import HeteroEncoder, HeteroGraphSAGE
+from torch_geometric.loader import NodeLoader
+from torch_geometric.nn import MLP
+from torch_geometric.sampler import NeighborSampler
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--task", type=str, default="churn", choices=["churn", "ltv"])

examples/fake/train.py

@@ -2,13 +2,12 @@
 
 import torch
 import torch.nn.functional as F
-from torch_geometric.loader import NodeLoader
-from torch_geometric.nn import MLP
-from torch_geometric.sampler import NeighborSampler
-
 from rtb.datasets import FakeProductDataset
 from rtb.external.graph import get_train_table_input, make_pkey_fkey_graph
 from rtb.external.nn import HeteroEncoder, HeteroGraphSAGE
+from torch_geometric.loader import NodeLoader
+from torch_geometric.nn import MLP
+from torch_geometric.sampler import NeighborSampler
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--task", type=str, default="churn", choices=["churn", "ltv"])

examples/xgboost_baseline.py

@@ -4,15 +4,14 @@
 import pandas as pd
 import torch
 import torch_frame
+from rtb.data.task import TaskType
+from rtb.datasets import get_dataset
 from text_embedder import GloveTextEmbedding
 from torch_frame.config.text_embedder import TextEmbedderConfig
 from torch_frame.data import Dataset
 from torch_frame.gbdt import XGBoost
 from torch_frame.typing import Metric
 
-from rtb.data.task import TaskType
-from rtb.datasets import get_dataset
-
 parser = argparse.ArgumentParser()
 parser.add_argument("--dataset", type=str, default="rtb-forum")
 parser.add_argument("--task", type=str, default="UserSumCommentScoresTask")

relbench/tasks/amazon.py

@@ -4,7 +4,7 @@
 import pandas as pd
 
 from relbench.data import Database, RelBenchTask, Table
-from relbench.metrics import accuracy, f1, mae, rmse, roc_auc, average_precision
+from relbench.metrics import accuracy, average_precision, f1, mae, rmse, roc_auc
 
 
 class ChurnTask(RelBenchTask):