Add some placeholder missing docstrings and # noqa tags

deepsensor/model/convnp.py

@@ -975,6 +975,14 @@ def ar_sample(
 
 
 def concat_tasks(tasks: List[Task], multiple: int = 1) -> Task:
+    """
+    Concatenate a list of tasks into a single task containing multiple batches.
+
+    ```{warning}
+    `concat_tasks` has been moved to deepsensor.data.task and will be removed from "
+        "deepsensor.model.convnp in a future release.
+    ```
+    """
     warnings.warn(
         "concat_tasks has been moved to deepsensor.data.task and will be removed from "
         "deepsensor.model.convnp in a future release.",

deepsensor/model/model.py

@@ -81,7 +81,7 @@ def std(self, task: Task):
         var = self.variance(task)
         return var**0.5
 
-    def stddev(self, *args, **kwargs):
+    def stddev(self, *args, **kwargs): # noqa
         return self.std(*args, **kwargs)
 
     def covariance(self, task: Task, *args, **kwargs):
@@ -609,7 +609,7 @@ def unnormalise_pred_array(arr, **kwargs):
         return pred
 
 
-def main():  # pragma: no cover
+def main():  # pragma: no cover # noqa
     import deepsensor.tensorflow
     from deepsensor.data.loader import TaskLoader
     from deepsensor.data.processor import DataProcessor

deepsensor/tensorflow/__init__.py

@@ -17,6 +17,7 @@
 
 
 def convert_to_tensor(arr):
+    """Convert `arr` to tensorflow tensor."""
     return tf.convert_to_tensor(arr)
 
 

deepsensor/torch/__init__.py

@@ -17,6 +17,7 @@
 
 
 def convert_to_tensor(arr):
+    """Convert `arr` to pytorch tensor."""
     return torch.tensor(arr)
 
 

deepsensor/train/train.py

@@ -172,6 +172,7 @@ def __call__(
         progress_bar=False,
         tqdm_notebook=False,
     ) -> List[float]:
+        """Train model for one epoch."""
         return train_epoch(
             model=self.model,
             tasks=tasks,