MLflow for Darts implementation

.gitignore

@@ -25,3 +25,5 @@ docs_env
 .venv
 
 uv.lock
+repl/
+examples/mlruns/*

darts/models/forecasting/pl_forecasting_module.py

@@ -456,8 +456,11 @@ def _update_metrics(self, output, target, metrics):
             pred = output.squeeze(dim=-1)
 
         # torch metrics require 2D targets of shape (batch size * ocl, num targets)
-        target = target.reshape(-1, self.n_targets)
-        pred = pred.reshape(-1, self.n_targets)
+        # contiguous() is needed because model outputs can be non-contiguous views
+        # (e.g. NBEATS slices the last dimension), and some torchmetrics implementations
+        # call .view() internally which requires a contiguous tensor.
+        target = target.reshape(-1, self.n_targets).contiguous()
+        pred = pred.reshape(-1, self.n_targets).contiguous()
 
         metrics.update(pred, target)
 

darts/tests/conftest.py

@@ -107,6 +107,14 @@
     logger.warning("Ray not installed - Some tests will be skipped.")
     RAY_AVAILABLE = False
 
+try:
+    import mlflow  # noqa: F401
+
+    MLFLOW_AVAILABLE = True
+except ImportError:
+    logger.warning("MLflow not installed - Some tests will be skipped.")
+    MLFLOW_AVAILABLE = False
+
 try:
     import polars  # noqa: F401