Mergeback 2.1.0 to develop

src/otx/core/data/module.py

@@ -11,7 +11,6 @@
 
 import torch
 from datumaro import Dataset as DmDataset
-from datumaro import Environment
 from lightning import LightningDataModule
 from omegaconf import DictConfig, OmegaConf
 from torch.utils.data import DataLoader, RandomSampler
@@ -105,18 +104,6 @@ def __init__(
 
         VIDEO_EXTENSIONS.append(".mp4")
 
-        # Data Format Check
-        available_data_formats = Environment().detect_dataset(str(self.data_root))
-        if not available_data_formats:
-            msg = f"Invalid data root: {self.data_root}. Please check if the data root is valid."
-            raise ValueError(msg)
-        if self.data_format not in available_data_formats:
-            log.warning(
-                f"Invalid data format: {self.data_format}. Available formats: {available_data_formats} "
-                f"Replace data_format: {self.data_format} -> {available_data_formats[0]}.",
-            )
-            self.data_format = available_data_formats[0]
-
         dataset = DmDataset.import_from(self.data_root, format=self.data_format)
         if self.task != "H_LABEL_CLS":
             dataset = pre_filtering(

tests/unit/core/data/test_module.py

@@ -4,10 +4,9 @@
 
 from pathlib import Path
 from typing import TYPE_CHECKING
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock
 
 import pytest
-from datumaro.components.environment import Environment
 from importlib_resources import files
 from lightning.pytorch.loggers import CSVLogger
 from omegaconf import DictConfig, OmegaConf
@@ -162,43 +161,6 @@ def test_init_input_size(
         assert fxt_config.val_subset.input_size == (1200, 1200)
         assert fxt_config.test_subset.input_size == (800, 800)
 
-    def test_data_format_check(
-        self,
-        mock_dm_dataset,
-        mock_otx_dataset_factory,
-        mock_data_filtering,
-        fxt_config,
-        caplog,
-    ) -> None:
-        # Dataset will have "train_0", "train_1", "val_0", ..., "test_1" subsets
-        mock_dm_subsets = {f"{name}_{idx}": MagicMock() for name in ["train", "val", "test"] for idx in range(2)}
-        mock_dm_dataset.return_value.subsets.return_value = mock_dm_subsets
-        with patch.object(Environment, "detect_dataset", return_value=["voc", "voc_classification"]):
-            _ = OTXDataModule(
-                task=fxt_config.task,
-                data_format=fxt_config.data_format,
-                data_root=fxt_config.data_root,
-                train_subset=fxt_config.train_subset,
-                val_subset=fxt_config.val_subset,
-                test_subset=fxt_config.test_subset,
-            )
-
-        assert "Invalid data format:" in caplog.text
-        assert "Replace data_format:" in caplog.text
-
-        with patch.object(Environment, "detect_dataset", return_value=[]), pytest.raises(
-            ValueError,
-            match="Invalid data root:",
-        ):
-            _ = OTXDataModule(
-                task=fxt_config.task,
-                data_format=fxt_config.data_format,
-                data_root=fxt_config.data_root,
-                train_subset=fxt_config.train_subset,
-                val_subset=fxt_config.val_subset,
-                test_subset=fxt_config.test_subset,
-            )
-
     @pytest.fixture()
     def fxt_real_tv_cls_config(self) -> DictConfig:
         cfg_path = files("otx") / "recipe" / "_base_" / "data" / "torchvision_base.yaml"