Trainer __repr__ / __str__(DAT-1034)

datamint/_repr_utils.py

@@ -0,0 +1,80 @@
+"""Shared plain-text / Jupyter HTML repr rendering for entities, trainers, and datasets.
+
+Any class that can produce a ``(label, value)`` field list gets a consistent
+`print()` block and a consistent HTML card in Jupyter for free.
+"""
+
+# ---------------------------------------------------------------------------
+# Jinja2 HTML template for the Jupyter card repr
+# ---------------------------------------------------------------------------
+_CARD_HTML_TEMPLATE = """\
+<div style="max-width: 720px; margin: 10px 0; overflow: hidden; border-radius: 18px;
+           border: 1px solid var(--vscode-panel-border, #d0d7de);
+           background: var(--vscode-editor-background, #ffffff);
+           color: var(--vscode-foreground, #1f2328);
+           box-shadow: 0 10px 30px rgba(15, 23, 42, 0.10);">
+
+  {# ---- Header ---- #}
+  <div style="padding: 18px 20px;
+             border-bottom: 1px solid var(--vscode-panel-border, #d0d7de);
+             background: linear-gradient(135deg, rgba(59, 130, 246, 0.14), rgba(16, 185, 129, 0.08));">
+    <div style="font-size: 11px; font-weight: 700; letter-spacing: 0.08em; text-transform: uppercase;
+               color: var(--vscode-descriptionForeground, #57606a);">{{ kind }}</div>
+    <div style="display: flex; align-items: center; justify-content: space-between;
+               gap: 12px; flex-wrap: wrap; margin-top: 8px;">
+      <h4 style="margin: 0; font-size: 22px; font-weight: 700; color: inherit;">{{ name }}</h4>
+    </div>
+  </div>
+
+  {# ---- Fields table ---- #}
+  {%- if fields %}
+  <div style="padding: 12px 20px 18px;">
+    <table style="width: 100%; border-collapse: collapse; font-size: 14px;">
+      {%- for label, value in fields %}
+      <tr>
+        <th style="padding: 10px 12px 10px 0; width: 30%; text-align: left; vertical-align: top;
+                  font-size: 11px; font-weight: 700; letter-spacing: 0.04em; text-transform: uppercase;
+                  color: var(--vscode-descriptionForeground, #57606a); white-space: nowrap;">{{ label }}</th>
+        <td style="padding: 10px 0; border-bottom: 1px solid var(--vscode-panel-border, #d0d7de);">
+          <span style="display: inline-block; padding: 2px 8px; border-radius: 999px;
+                      background: var(--vscode-textCodeBlock-background, #f6f8fa);
+                      color: var(--vscode-textPreformat-foreground, var(--vscode-foreground, #1f2328));
+                      font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, 'Liberation Mono', monospace;
+                      font-size: 13px;"
+          >{{ value }}</span>
+        </td>
+      </tr>
+      {%- endfor %}
+    </table>
+  </div>
+  {%- else %}
+  <div style="padding: 18px 20px; font-size: 14px;
+             color: var(--vscode-descriptionForeground, #57606a);">No non-empty fields to display.</div>
+  {%- endif %}
+
+</div>
+"""
+
+_card_template = None
+
+
+def _get_card_template():
+    """Lazily compile and cache the Jinja2 card template."""
+    global _card_template
+    if _card_template is None:
+        from jinja2 import Environment
+        _card_template = Environment(autoescape=True).from_string(_CARD_HTML_TEMPLATE)
+    return _card_template
+
+
+def render_text_block(header: str, fields: list[tuple[str, str]], empty_message: str = "(no non-empty fields)") -> str:
+    """Plain-text ``Header\\n  Label: value`` block, used by ``__str__``/``__repr__``."""
+    if not fields:
+        return f"{header}\n  {empty_message}"
+    lines = [header] + [f"  {label}: {value}" for label, value in fields]
+    return "\n".join(lines)
+
+
+def render_html_card(kind: str, name: str, fields: list[tuple[str, str]]) -> str:
+    """Styled HTML card for Jupyter's ``_repr_html_`` display hook."""
+    return _get_card_template().render(kind=kind, name=name, fields=fields)

datamint/dataset/base.py

@@ -16,6 +16,7 @@
 import numpy as np
 from datamint.entities.annotation_worklist import AnnotationWorklist
 from datamint.exceptions import DatamintException, ItemNotFoundError
+from datamint._repr_utils import render_text_block, render_html_card
 from .annotation_processor import AnnotationProcessor, MergeStrategy
 from datamint.entities.annotations.annotation_spec import AnnotationSpec, CategoryAnnotationSpec
 from datamint.entities.annotations import AnnotationType
@@ -1225,19 +1226,22 @@ def subset(self, indices: list[int]) -> 'DatamintBaseDataset':
             raise IndexError(f"Subset indices out of bounds for dataset of length {len(self)}.") from e
         return new_ds
 
-    def __repr__(self) -> str:
+    def _extra_repr_fields(self) -> list[tuple[str, str]]:
+        """Hook for subclasses to insert extra ``(label, value)`` lines into the repr."""
+        return []
+
+    def _repr_fields(self) -> list[tuple[str, str]]:
         name = self.project.name if self.project else "<Custom>"
-        head = f"Dataset {name}"
-        body = [f"Number of datapoints: {len(self)}"]
+        fields = [
+            ("Project", name),
+            ("Number of datapoints", str(len(self))),
+        ]
         if self.split_name is not None:
-            body.append(f"Split: {self.split_name}")
+            fields.append(("Split", str(self.split_name)))
         if self.split_source is not None:
-            body.append(f"Split source: {self.split_source}")
+            fields.append(("Split source", str(self.split_source)))
         if self.split_as_of_timestamp is not None:
-            body.append(f"Split as of: {self.split_as_of_timestamp}")
-
-        # if self.manager.root is not None:
-        #    body.append(f"Location: {self.manager.dataset_dir}")
+            fields.append(("Split as of", str(self.split_as_of_timestamp)))
 
         filters = [
             (self.include_annotators, "Including annotators"),
@@ -1249,13 +1253,19 @@ def __repr__(self) -> str:
             (self.include_frame_label_names, "Including frame labels"),
             (self.exclude_frame_label_names, "Excluding frame labels"),
         ]
-
         for value, desc in filters:
             if value is not None:
-                body.append(f"{desc}: {value}")
+                fields.append((desc, str(value)))
+
+        fields.extend(self._extra_repr_fields())
+        return fields
+
+    def __repr__(self) -> str:
+        return render_text_block(self.__class__.__name__, self._repr_fields())
 
-        lines = [head] + ["    " + line for line in body]
-        return "\n".join(lines)
+    def _repr_html_(self) -> str:
+        """HTML representation for Jupyter Notebooks."""
+        return render_html_card(kind="Dataset", name=self.__class__.__name__, fields=self._repr_fields())
 
     def split(
         self,

datamint/dataset/image_dataset.py

@@ -125,11 +125,6 @@ def apply_alb_transform(
         result['image'] = aug_img
         return result
 
-    @override
-    def __repr__(self) -> str:
-        base = super(VolumeDataset, self).__repr__()
-        return f"ImageDataset\n{base}"
-
 
 def detection_collate_fn(batch: list[dict]) -> dict:
     """Collate a list of detection items into a batch.

datamint/dataset/sliced_dataset.py

@@ -584,6 +584,5 @@ def apply_alb_transform(
             result['masks'] = aug_segmentations
         return result
 
-    def __repr__(self) -> str:
-        base = super().__repr__()
-        return f"SlicedVolumeDataset (axis={self._slice_axis})\n{base}"
+    def _extra_repr_fields(self) -> list[tuple[str, str]]:
+        return [*super()._extra_repr_fields(), ("Slice axis", str(self._slice_axis))]

datamint/dataset/sliced_video_dataset.py

@@ -454,7 +454,3 @@ def apply_alb_transform(
             'image': aug_img,
             'segmentations': aug_segmentations,
         }
-
-    def __repr__(self) -> str:
-        base = super().__repr__()
-        return f"SlicedVideoDataset\n{base}"

datamint/dataset/video_dataset.py

@@ -36,10 +36,6 @@ class VideoDataset(MultiFrameDataset):
         print(frame_ds[0]['image'].shape)  # (C, H, W)
     """
 
-    def __repr__(self) -> str:
-        base = super().__repr__()
-        return f"VideoDataset\n{base}"
-
     def frame_by_frame(self) -> 'SlicedVideoDataset':
         """Create a 2D dataset iterating over individual video frames.
 

datamint/dataset/volume_dataset.py

@@ -30,10 +30,6 @@ class VolumeDataset(MultiFrameDataset):
     Inherits multi-frame loading and augmentation from :class:`MultiFrameDataset`.
     """
 
-    def __repr__(self) -> str:
-        base = super().__repr__()
-        return f"VolumeDataset\n{base}"
-
     def slice(self, axis: str | int = 'axial') -> 'SlicedVolumeDataset':
         """Create a 2D dataset by slicing this volume along an axis.
 

datamint/entities/base_entity.py

@@ -6,6 +6,7 @@
 from pydantic import BaseModel, ConfigDict, PrivateAttr
 
 from datamint.types import CacheMode
+from datamint._repr_utils import render_text_block, render_html_card
 
 if TYPE_CHECKING:
     from datamint.api.entity_base_api import EntityBaseApi
@@ -21,68 +22,6 @@
 # Track logged warnings to avoid duplicates
 _LOGGED_WARNINGS: set[tuple[str, str]] = set()
 
-# ---------------------------------------------------------------------------
-# Jinja2 HTML template for BaseEntity Jupyter repr
-# ---------------------------------------------------------------------------
-_ENTITY_HTML_TEMPLATE = """\
-<div style="max-width: 720px; margin: 10px 0; overflow: hidden; border-radius: 18px;
-           border: 1px solid var(--vscode-panel-border, #d0d7de);
-           background: var(--vscode-editor-background, #ffffff);
-           color: var(--vscode-foreground, #1f2328);
-           box-shadow: 0 10px 30px rgba(15, 23, 42, 0.10);">
-
-  {# ---- Header ---- #}
-  <div style="padding: 18px 20px;
-             border-bottom: 1px solid var(--vscode-panel-border, #d0d7de);
-             background: linear-gradient(135deg, rgba(59, 130, 246, 0.14), rgba(16, 185, 129, 0.08));">
-    <div style="font-size: 11px; font-weight: 700; letter-spacing: 0.08em; text-transform: uppercase;
-               color: var(--vscode-descriptionForeground, #57606a);">Entity</div>
-    <div style="display: flex; align-items: center; justify-content: space-between;
-               gap: 12px; flex-wrap: wrap; margin-top: 8px;">
-      <h4 style="margin: 0; font-size: 22px; font-weight: 700; color: inherit;">{{ entity_name }}</h4>
-    </div>
-  </div>
-
-  {# ---- Fields table ---- #}
-  {%- if fields %}
-  <div style="padding: 12px 20px 18px;">
-    <table style="width: 100%; border-collapse: collapse; font-size: 14px;">
-      {%- for name, value in fields %}
-      <tr>
-        <th style="padding: 10px 12px 10px 0; width: 30%; text-align: left; vertical-align: top;
-                  font-size: 11px; font-weight: 700; letter-spacing: 0.04em; text-transform: uppercase;
-                  color: var(--vscode-descriptionForeground, #57606a); white-space: nowrap;">{{ name }}</th>
-        <td style="padding: 10px 0; border-bottom: 1px solid var(--vscode-panel-border, #d0d7de);">
-          <span style="display: inline-block; padding: 2px 8px; border-radius: 999px;
-                      background: var(--vscode-textCodeBlock-background, #f6f8fa);
-                      color: var(--vscode-textPreformat-foreground, var(--vscode-foreground, #1f2328));
-                      font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, 'Liberation Mono', monospace;
-                      font-size: 13px;"
-          >{{ value }}</span>
-        </td>
-      </tr>
-      {%- endfor %}
-    </table>
-  </div>
-  {%- else %}
-  <div style="padding: 18px 20px; font-size: 14px;
-             color: var(--vscode-descriptionForeground, #57606a);">No non-empty fields to display.</div>
-  {%- endif %}
-
-</div>
-"""
-
-_entity_template = None
-
-
-def _get_entity_template():
-    """Lazily compile and cache the Jinja2 entity template."""
-    global _entity_template
-    if _entity_template is None:
-        from jinja2 import Environment
-        _entity_template = Environment(autoescape=True).from_string(_ENTITY_HTML_TEMPLATE)
-    return _entity_template
-
 
 class BaseEntityModel(BaseModel):
     """Shared lightweight Pydantic base for Datamint entities and DTOs."""
@@ -128,25 +67,10 @@ def _get_display_fields(self, max_value_len: int = 120) -> list[tuple[str, str]]
 
     def _repr_html_(self) -> str:
         """HTML representation for Jupyter Notebooks."""
-        entity_id = getattr(self, 'id', None)
-        fields = self._get_display_fields()
-
-        return _get_entity_template().render(
-            entity_name=self.__class__.__name__,
-            entity_id=str(entity_id) if entity_id else None,
-            fields=fields,
-        )
+        return render_html_card(kind='Entity', name=self.__class__.__name__, fields=self._get_display_fields())
 
     def __str__(self) -> str:
-        fields = self._get_display_fields()
-
-        header = self.__class__.__name__
-
-        if not fields:
-            return f"{header}\n  (no non-empty fields)"
-
-        lines = [header] + [f"  {name}: {value}" for name, value in fields]
-        return "\n".join(lines)
+        return render_text_block(self.__class__.__name__, self._get_display_fields())
 
     def __init__(self, **data):
         super().__init__(**data)

datamint/lightning/trainers/base_trainer.py

@@ -20,6 +20,7 @@
 from datamint.mlflow import set_project
 from datamint.mlflow.flavors.model import BaseDatamintModel
 from datamint.lightning.trainers.lightning_modules.base import DatamintLightningModule
+from datamint._repr_utils import render_text_block, render_html_card
 
 if TYPE_CHECKING:
     from albumentations import BaseCompose
@@ -137,6 +138,38 @@ def _project_name(self) -> str:
     def experiment_name(self) -> str:
         return self.mlflow_experiment_name or f"{self._project_name}_training"
 
+    def _model_description(self) -> str:
+        """Short human-readable model description for :meth:`__repr__`. Override per architecture."""
+        if self._user_model is not None:
+            model = self._user_model
+            cls = model if isinstance(model, type) else model.__class__
+            return f"Custom ({cls.__name__})"
+        return self.__class__.__name__.removesuffix("Trainer")
+
+    def _extra_repr_fields(self) -> list[tuple[str, str]]:
+        """Architecture-specific ``(label, value)`` lines inserted between Batch size and Early stopping patience."""
+        return []
+
+    def _repr_fields(self) -> list[tuple[str, str]]:
+        """Fields shown by :meth:`__repr__`/:meth:`_repr_html_`. Cheap and side-effect free: never resolves the dataset or builds the model."""
+        return [
+            ("Project", self._project_name),
+            ("Model", self._model_description()),
+            ("Max epochs", str(self.max_epochs)),
+            ("Batch size", str(self.batch_size)),
+            *self._extra_repr_fields(),
+            ("Early stopping patience", str(self.early_stopping_patience) if self.early_stopping_patience else "disabled"),
+            ("MLflow experiment", self.experiment_name),
+            ("Auto-deploy adapter", "enabled" if self.auto_deploy_adapter else "disabled"),
+        ]
+
+    def __repr__(self) -> str:
+        return render_text_block(self.__class__.__name__, self._repr_fields())
+
+    def _repr_html_(self) -> str:
+        """HTML representation for Jupyter Notebooks."""
+        return render_html_card(kind="Trainer", name=self.__class__.__name__, fields=self._repr_fields())
+
     def _with_project(self):
         set_project(self._project_name)
 

datamint/lightning/trainers/classification_trainer.py

@@ -95,6 +95,16 @@ def __init__(
         else:
             self.image_size = image_size
 
+    def _model_description(self) -> str:
+        if self._user_model is not None:
+            return super()._model_description()
+        pretrained_str = "pretrained" if self.pretrained else "random init"
+        return f"{self.architecture} ({pretrained_str})"
+
+    def _extra_repr_fields(self) -> list[tuple[str, str]]:
+        image_size = f"{self.image_size[0]}×{self.image_size[1]}" if self.image_size else "auto (no resize)"
+        return [*super()._extra_repr_fields(), ("Image size", image_size)]
+
     # ── Template hooks ──────────────────────────────────────────
 
     def _build_dataset(self, project: 'str | Project', **kwargs: Any) -> ImageDataset:

datamint/lightning/trainers/seg2d_trainer.py

@@ -77,6 +77,11 @@ def __init__(
         else:
             self.image_size = image_size
 
+    @override
+    def _extra_repr_fields(self) -> list[tuple[str, str]]:
+        image_size = f"{self.image_size[0]}×{self.image_size[1]}" if self.image_size else "auto (no resize)"
+        return [*super()._extra_repr_fields(), ("Image size", image_size)]
+
     def _build_dataset(self, project: 'str | Project', **kwargs: Any) -> ImageDataset | SlicedVolumeDataset:
         default_params = dict(
             return_as_semantic_segmentation=True,

datamint/lightning/trainers/seg3d_trainer.py

@@ -57,6 +57,19 @@ def __init__(
         else:
             self.image_size = image_size
 
+    def _model_description(self) -> str:
+        if self._user_model is not None:
+            return super()._model_description()
+        return f"{self.encoder_name} encoder"
+
+    def _extra_repr_fields(self) -> list[tuple[str, str]]:
+        image_size = f"{self.image_size[0]}×{self.image_size[1]}" if self.image_size else "auto (original slice size)"
+        return [
+            *super()._extra_repr_fields(),
+            ("Slice axis", str(self.slice_axis)),
+            ("Image size", image_size),
+        ]
+
     # ── Template hooks ──────────────────────────────────────────
 
     def _build_dataset(self, project: 'str | Project', **kwargs: Any):