Remove DataModuleConfig for the reduced config structure

src/otx/algo/utils/xai_utils.py

@@ -287,7 +287,7 @@ def _convert_labels_from_hcls_format(
 
 def set_crop_padded_map_flag(explain_config: ExplainConfig, datamodule: OTXDataModule) -> ExplainConfig:
     """If resize with keep_ratio = True was used, set crop_padded_map flag to True."""
-    for transform in datamodule.config.test_subset.transforms:
+    for transform in datamodule.test_subset.transforms:
         tranf_name = transform["class_path"].split(".")[-1]
         if tranf_name == "Resize" and transform["init_args"].get("keep_ratio", False):
             explain_config.crop_padded_map = True

src/otx/cli/cli.py

@@ -174,8 +174,8 @@ def engine_subcommand_parser(subcommand: str, **kwargs) -> tuple[ArgumentParser,
         parser.link_arguments("work_dir", "workspace.work_dir")
 
         parser.link_arguments("data_root", "engine.data_root")
-        parser.link_arguments("data_root", "data.config.data_root")
-        parser.link_arguments("engine.device", "data.config.device")
+        parser.link_arguments("data_root", "data.data_root")
+        parser.link_arguments("engine.device", "data.device")
 
         added_arguments = parser.add_method_arguments(
             Engine,

src/otx/core/config/data.py

@@ -9,10 +9,8 @@
 
 from copy import deepcopy
 from dataclasses import dataclass, field
-from typing import Any, Optional
+from typing import Any
 
-from otx.core.types.device import DeviceType
-from otx.core.types.image import ImageColorChannel
 from otx.core.types.transformer_libs import TransformLibType
 
 
@@ -109,34 +107,6 @@ class UnlabeledDataConfig(SubsetConfig):
     to_tv_image: bool = True
 
 
-@dataclass
-class DataModuleConfig:
-    """DTO for data module configuration."""
-
-    data_format: str
-    data_root: str
-
-    train_subset: SubsetConfig
-    val_subset: SubsetConfig
-    test_subset: SubsetConfig
-    unlabeled_subset: UnlabeledDataConfig = field(default_factory=lambda: UnlabeledDataConfig())
-
-    tile_config: TileConfig = field(default_factory=lambda: TileConfig())
-    vpm_config: VisualPromptingConfig = field(default_factory=lambda: VisualPromptingConfig())
-
-    mem_cache_size: str = "1GB"
-    mem_cache_img_max_size: Optional[tuple[int, int]] = None
-    image_color_channel: ImageColorChannel = ImageColorChannel.RGB
-    stack_images: bool = True
-
-    include_polygons: bool = False
-    ignore_index: int = 255
-    unannotated_items_ratio: float = 0.0
-
-    auto_num_workers: bool = False
-    device: DeviceType = DeviceType.auto
-
-
 @dataclass
 class SamplerConfig:
     """Configuration class for defining the sampler used in the data loading process.

src/otx/core/data/factory.py

@@ -7,6 +7,8 @@
 
 from typing import TYPE_CHECKING
 
+from otx.core.config.data import VisualPromptingConfig
+from otx.core.types.image import ImageColorChannel
 from otx.core.types.task import OTXTaskType
 from otx.core.types.transformer_libs import TransformLibType
 
@@ -15,7 +17,7 @@
 if TYPE_CHECKING:
     from datumaro import Dataset as DmDataset
 
-    from otx.core.config.data import DataModuleConfig, SubsetConfig
+    from otx.core.config.data import SubsetConfig
     from otx.core.data.mem_cache import MemCacheHandlerBase
 
 
@@ -69,19 +71,24 @@ def create(  # ignore too many return statements
         cls: type[OTXDatasetFactory],
         task: OTXTaskType,
         dm_subset: DmDataset,
-        mem_cache_handler: MemCacheHandlerBase,
         cfg_subset: SubsetConfig,
-        cfg_data_module: DataModuleConfig,
+        mem_cache_handler: MemCacheHandlerBase,
+        mem_cache_img_max_size: tuple[int, int] | None = None,
+        image_color_channel: ImageColorChannel = ImageColorChannel.RGB,
+        stack_images: bool = True,
+        include_polygons: bool = False,
+        ignore_index: int = 255,
+        vpm_config: VisualPromptingConfig = VisualPromptingConfig(),  # noqa: B008
     ) -> OTXDataset:
         """Create OTXDataset."""
         transforms = TransformLibFactory.generate(cfg_subset)
         common_kwargs = {
             "dm_subset": dm_subset,
             "transforms": transforms,
             "mem_cache_handler": mem_cache_handler,
-            "mem_cache_img_max_size": cfg_data_module.mem_cache_img_max_size,
-            "image_color_channel": cfg_data_module.image_color_channel,
-            "stack_images": cfg_data_module.stack_images,
+            "mem_cache_img_max_size": mem_cache_img_max_size,
+            "image_color_channel": image_color_channel,
+            "stack_images": stack_images,
             "to_tv_image": cfg_subset.to_tv_image,
         }
 
@@ -117,14 +124,12 @@ def create(  # ignore too many return statements
         if task in [OTXTaskType.ROTATED_DETECTION, OTXTaskType.INSTANCE_SEGMENTATION]:
             from .dataset.instance_segmentation import OTXInstanceSegDataset
 
-            # NOTE: DataModuleConfig does not have include_polygons attribute
-            include_polygons = getattr(cfg_data_module, "include_polygons", False)
             return OTXInstanceSegDataset(include_polygons=include_polygons, **common_kwargs)
 
         if task == OTXTaskType.SEMANTIC_SEGMENTATION:
             from .dataset.segmentation import OTXSegmentationDataset
 
-            return OTXSegmentationDataset(**common_kwargs, ignore_index=cfg_data_module.ignore_index)
+            return OTXSegmentationDataset(ignore_index=ignore_index, **common_kwargs)
 
         if task == OTXTaskType.ACTION_CLASSIFICATION:
             from .dataset.action_classification import OTXActionClsDataset
@@ -134,15 +139,15 @@ def create(  # ignore too many return statements
         if task == OTXTaskType.VISUAL_PROMPTING:
             from .dataset.visual_prompting import OTXVisualPromptingDataset
 
-            use_bbox = getattr(cfg_data_module.vpm_config, "use_bbox", False)
-            use_point = getattr(cfg_data_module.vpm_config, "use_point", False)
+            use_bbox = getattr(vpm_config, "use_bbox", False)
+            use_point = getattr(vpm_config, "use_point", False)
             return OTXVisualPromptingDataset(use_bbox=use_bbox, use_point=use_point, **common_kwargs)
 
         if task == OTXTaskType.ZERO_SHOT_VISUAL_PROMPTING:
             from .dataset.visual_prompting import OTXZeroShotVisualPromptingDataset
 
-            use_bbox = getattr(cfg_data_module.vpm_config, "use_bbox", False)
-            use_point = getattr(cfg_data_module.vpm_config, "use_point", False)
+            use_bbox = getattr(vpm_config, "use_bbox", False)
+            use_point = getattr(vpm_config, "use_point", False)
             return OTXZeroShotVisualPromptingDataset(use_bbox=use_bbox, use_point=use_point, **common_kwargs)
 
         raise NotImplementedError(task)

src/otx/core/data/mem_cache.py

@@ -82,8 +82,9 @@ class MemCacheHandlerBase:
     It will be combined with LoadImageFromOTXDataset to store/retrieve the samples in memory.
     """
 
-    def __init__(self, mem_size: int):
+    def __init__(self, mem_size: int, mem_cache_img_max_size: tuple[int, int] | None = None):
         self._mem_size = mem_size
+        self._mem_cache_img_max_size = mem_cache_img_max_size
         self._init_data_structs(mem_size)
 
     def _init_data_structs(self, mem_size: int) -> None:
@@ -108,6 +109,11 @@ def mem_size(self) -> int:
         """Get the reserved memory pool size (bytes)."""
         return len(self._arr)
 
+    @property
+    def mem_cache_img_max_size(self) -> tuple[int, int] | None:
+        """Get the image max size in mem cache."""
+        return self._mem_cache_img_max_size
+
     def get(self, key: Any) -> tuple[np.ndarray | None, dict | None]:  # noqa: ANN401
         """Try to look up the cached item with the given key.