Implementing str method

Switched name from dataset to dataloader
Switched name Prediction to Predict
removed available keyword and instead write None if not available
Switched from unknown to NA

Author: MrWhatZitToYaa

src/lightning/pytorch/core/datamodule.py

@@ -255,16 +255,16 @@ def __str__(self) -> str:
         """
 
         class dataset_info:
-            def __init__(self, available: str, length: str) -> None:
+            def __init__(self, available: bool, length: str) -> None:
                 self.available = available
                 self.length = length
 
         def retrieve_dataset_info(loader: DataLoader) -> dataset_info:
             """Helper function to compute dataset information."""
             dataset = loader.dataset
-            size: str = str(len(dataset)) if isinstance(dataset, Sized) else "unknown"
+            size: str = str(len(dataset)) if isinstance(dataset, Sized) else "NA"
 
-            return dataset_info("yes", size)
+            return dataset_info(True, size)
 
         def loader_info(
             loader: Union[DataLoader, Iterable[DataLoader]],
@@ -282,7 +282,7 @@ def extract_loader_info(methods: list[tuple[str, str]]) -> dict:
                     loader = loader_callback()
                     info[loader_name] = loader_info(loader)
                 except Exception:
-                    info[loader_name] = dataset_info("no", "unknown")
+                    info[loader_name] = dataset_info(False, "")
 
             return info
 
@@ -292,11 +292,11 @@ def format_loader_info(info: dict[str, Union[dataset_info, Iterable[dataset_info
             for loader_name, loader_info in info.items():
                 # Single dataset
                 if isinstance(loader_info, dataset_info):
-                    loader_info_formatted = f"available={loader_info.available}, size={loader_info.length}"
+                    loader_info_formatted = "None" if not loader_info.available else f"size={loader_info.length}"
                 # Iterable of datasets
                 else:
                     loader_info_formatted = " ; ".join(
-                        f"{i}. available={loader_info_i.available}, size={loader_info_i.length}"
+                        "None" if not loader_info_i.available else f"{i}. size={loader_info_i.length}"
                         for i, loader_info_i in enumerate(loader_info, start=1)
                     )
 
@@ -306,10 +306,10 @@ def format_loader_info(info: dict[str, Union[dataset_info, Iterable[dataset_info
 
         # Available dataloader methods
         datamodule_loader_methods: list[tuple[str, str]] = [
-            ("Train dataset", "train_dataloader"),
-            ("Validation dataset", "val_dataloader"),
-            ("Test dataset", "test_dataloader"),
-            ("Prediction dataset", "predict_dataloader"),
+            ("Train dataloader", "train_dataloader"),
+            ("Validation dataloader", "val_dataloader"),
+            ("Test dataloader", "test_dataloader"),
+            ("Predict dataloader", "predict_dataloader"),
         ]
 
         # Retrieve information for each dataloader method

tests/tests_pytorch/core/test_datamodules.py

@@ -522,10 +522,10 @@ def test_datamodule_string_not_available():
     dm = BoringDataModule()
 
     expected_output = (
-        f"{{Train dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Validation dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Test dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Prediction dataset: available=no, size=unknown}}"
+        f"{{Train dataloader: None}}{os.linesep}"
+        f"{{Validation dataloader: None}}{os.linesep}"
+        f"{{Test dataloader: None}}{os.linesep}"
+        f"{{Predict dataloader: None}}"
     )
     out = str(dm)
 
@@ -537,10 +537,10 @@ def test_datamodule_string_fit_setup():
     dm.setup(stage="fit")
 
     expected_output = (
-        f"{{Train dataset: available=yes, size=64}}{os.linesep}"
-        f"{{Validation dataset: available=yes, size=64}}{os.linesep}"
-        f"{{Test dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Prediction dataset: available=no, size=unknown}}"
+        f"{{Train dataloader: size=64}}{os.linesep}"
+        f"{{Validation dataloader: size=64}}{os.linesep}"
+        f"{{Test dataloader: None}}{os.linesep}"
+        f"{{Predict dataloader: None}}"
     )
     output = str(dm)
 
@@ -552,10 +552,10 @@ def test_datamodule_string_validation_setup():
     dm.setup(stage="validate")
 
     expected_output = (
-        f"{{Train dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Validation dataset: available=yes, size=64}}{os.linesep}"
-        f"{{Test dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Prediction dataset: available=no, size=unknown}}"
+        f"{{Train dataloader: None}}{os.linesep}"
+        f"{{Validation dataloader: size=64}}{os.linesep}"
+        f"{{Test dataloader: None}}{os.linesep}"
+        f"{{Predict dataloader: None}}"
     )
     output = str(dm)
 
@@ -567,10 +567,10 @@ def test_datamodule_string_test_setup():
     dm.setup(stage="test")
 
     expected_output = (
-        f"{{Train dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Validation dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Test dataset: available=yes, size=64}}{os.linesep}"
-        f"{{Prediction dataset: available=no, size=unknown}}"
+        f"{{Train dataloader: None}}{os.linesep}"
+        f"{{Validation dataloader: None}}{os.linesep}"
+        f"{{Test dataloader: size=64}}{os.linesep}"
+        f"{{Predict dataloader: None}}"
     )
     output = str(dm)
 
@@ -582,10 +582,10 @@ def test_datamodule_string_predict_setup():
     dm.setup(stage="predict")
 
     expected_output = (
-        f"{{Train dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Validation dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Test dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Prediction dataset: available=yes, size=64}}"
+        f"{{Train dataloader: None}}{os.linesep}"
+        f"{{Validation dataloader: None}}{os.linesep}"
+        f"{{Test dataloader: None}}{os.linesep}"
+        f"{{Predict dataloader: size=64}}"
     )
     output = str(dm)
 
@@ -597,10 +597,10 @@ def test_datamodule_string_no_len():
     dm.setup("fit")
 
     expected_output = (
-        f"{{Train dataset: available=yes, size=unknown}}{os.linesep}"
-        f"{{Validation dataset: available=yes, size=unknown}}{os.linesep}"
-        f"{{Test dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Prediction dataset: available=no, size=unknown}}"
+        f"{{Train dataloader: size=NA}}{os.linesep}"
+        f"{{Validation dataloader: size=NA}}{os.linesep}"
+        f"{{Test dataloader: None}}{os.linesep}"
+        f"{{Predict dataloader: None}}"
     )
     output = str(dm)
 
@@ -612,10 +612,10 @@ def test_datamodule_string_iterable():
     dm.setup("fit")
 
     expected_output = (
-        f"{{Train dataset: 1. available=yes, size=16 ; 2. available=yes, size=unknown}}{os.linesep}"
-        f"{{Validation dataset: 1. available=yes, size=32 ; 2. available=yes, size=unknown}}{os.linesep}"
-        f"{{Test dataset: available=no, size=unknown}}{os.linesep}"
-        f"{{Prediction dataset: available=no, size=unknown}}"
+        f"{{Train dataloader: 1. size=16 ; 2. size=NA}}{os.linesep}"
+        f"{{Validation dataloader: 1. size=32 ; 2. size=NA}}{os.linesep}"
+        f"{{Test dataloader: None}}{os.linesep}"
+        f"{{Predict dataloader: None}}"
     )
     output = str(dm)