fixed some issues and added test cases

src/pytorch_tabular/tabular_model.py

@@ -1832,7 +1832,20 @@ def ret_summary(self, model=None, max_depth: int = -1) -> str:
 
     def __str__(self) -> str:
         """Returns a readable summary of the TabularModel object."""
-        return f"{self.__class__.__name__}(model={self.model.__class__.__name__ if self.has_model else 'None'})"
+        return f"{self.__class__.__name__}(model={self.model.__class__.__name__ if self.has_model else self.config._model_name+'(Not Initialized)'})"
+
+    def __repr__(self) -> str:
+        """Returns an unambiguous representation of the TabularModel object."""
+        config_str = json.dumps(
+            OmegaConf.to_container(self.config, resolve=True), indent=4
+        )
+        ret_str = f"{self.__class__.__name__}(\n"
+        if self.has_model:
+            ret_str += f"  model={self.model.__class__.__name__},\n"
+        else:
+            ret_str += f"  model={self.config._model_name} (Not Initialized),\n"
+        ret_str += f"  config={config_str},\n"
+        return ret_str
 
     def _repr_html_(self):
         """Generate an HTML representation for Jupyter Notebook."""
@@ -1912,10 +1925,18 @@ def _repr_html_(self):
         header_html = f"<div class='header'>{html.escape(self.model.__class__.__name__ if self.has_model else self.config._model_name)}{model_status}</div>"
 
         # Config Section
-        config_html = self._generate_collapsible_section("Model Config", self.config, uid=uid, is_dict=True)
+        config_html = self._generate_collapsible_section(
+            "Model Config", self.config, uid=uid, is_dict=True
+        )
 
         # Summary Section
-        summary_html = "" if not self.has_model else self._generate_collapsible_section("Model Summary", self._generate_model_summary_table(), uid=uid)
+        summary_html = (
+            ""
+            if not self.has_model
+            else self._generate_collapsible_section(
+                "Model Summary", self._generate_model_summary_table(), uid=uid
+            )
+        )
 
         # Combine sections
         return f"""
@@ -1930,7 +1951,9 @@ def _repr_html_(self):
     def _generate_collapsible_section(self, title, content, uid, is_dict=False):
         container_id = title.lower().replace(" ", "_") + uid
         if is_dict:
-            content = self._generate_nested_collapsible_sections(OmegaConf.to_container(content, resolve=True), container_id)
+            content = self._generate_nested_collapsible_sections(
+                OmegaConf.to_container(content, resolve=True), container_id
+            )
         return f"""
         <div>
             <span class="toggle-button" onclick="toggleVisibility('{container_id}')">&#9654;</span>
@@ -1947,7 +1970,9 @@ def _generate_nested_collapsible_sections(self, content, parent_id):
             if isinstance(value, dict):
                 nested_id = f"{parent_id}_{key}".replace(" ", "_")
                 nested_id = nested_id + str(uuid.uuid4())
-                nested_content = self._generate_nested_collapsible_sections(value, nested_id)
+                nested_content = self._generate_nested_collapsible_sections(
+                    value, nested_id
+                )
                 html_content += f"""
                 <div>
                     <span class="toggle-button" onclick="toggleVisibility('{nested_id}')">&#9654;</span>

tests/test_common.py

@@ -31,7 +31,7 @@
 
 MODEL_CONFIG_SAVE_TEST = [
     (CategoryEmbeddingModelConfig, {"layers": "10-20"}),
-    (AutoIntConfig, {"num_heads": 1, "num_attn_blocks": 1}),
+    (GANDALFConfig, {}),
     (NodeConfig, {"num_trees": 100, "depth": 2}),
     (TabNetModelConfig, {"n_a": 2, "n_d": 2}),
 ]
@@ -1247,3 +1247,63 @@ def test_model_compare_regression(regression_data, model_list, continuous_cols,
     # # there may be multiple models with the same score
     # best_models = comp_df.loc[comp_df[f"test_{rank_metric[0]}"] == best_score, "model"].values.tolist()
     # assert best_model.model._get_name() in best_models
+
+@pytest.mark.parametrize("model_config_class", MODEL_CONFIG_SAVE_TEST)
+@pytest.mark.parametrize("continuous_cols", [list(DATASET_CONTINUOUS_COLUMNS)])
+@pytest.mark.parametrize("categorical_cols", [["HouseAgeBin"]])
+@pytest.mark.parametrize("custom_metrics", [None, [fake_metric]])
+@pytest.mark.parametrize("custom_loss", [None, torch.nn.L1Loss()])
+@pytest.mark.parametrize("custom_optimizer", [None, torch.optim.Adagrad, "SGD", "torch_optimizer.AdaBound"])
+def test_str_repr(
+    regression_data,
+    model_config_class,
+    continuous_cols,
+    categorical_cols,
+    custom_metrics,
+    custom_loss,
+    custom_optimizer,
+):
+    (train, test, target) = regression_data
+    data_config = DataConfig(
+        target=target,
+        continuous_cols=continuous_cols,
+        categorical_cols=categorical_cols,
+    )
+    model_config_class, model_config_params = model_config_class
+    model_config_params["task"] = "regression"
+    model_config = model_config_class(**model_config_params)
+    trainer_config = TrainerConfig(
+        max_epochs=3,
+        checkpoints=None,
+        early_stopping=None,
+        accelerator="cpu",
+        fast_dev_run=True,
+    )
+    optimizer_config = OptimizerConfig()
+
+    tabular_model = TabularModel(
+        data_config=data_config,
+        model_config=model_config,
+        optimizer_config=optimizer_config,
+        trainer_config=trainer_config,
+    )
+    assert "Not Initialized" in str(tabular_model)
+    assert "Not Initialized" in repr(tabular_model)
+    assert "Model Summary" not in tabular_model._repr_html_()
+    assert "Model Config" in tabular_model._repr_html_()
+    assert "config" in tabular_model.__repr__()
+    assert "config" not in str(tabular_model)
+    tabular_model.fit(
+        train=train,
+        metrics=custom_metrics,
+        metrics_prob_inputs=None if custom_metrics is None else [False],
+        loss=custom_loss,
+        optimizer=custom_optimizer,
+        optimizer_params={}
+    )
+    assert model_config_class._model_name in str(tabular_model)
+    assert model_config_class._model_name in repr(tabular_model)
+    assert "Model Summary" in tabular_model._repr_html_()
+    assert "Model Config" in tabular_model._repr_html_()
+    assert "config" in tabular_model.__repr__()
+    assert model_config_class._model_name in tabular_model._repr_html_()