Add Model.set_dim method for safer dims resizing

Author: michaelosthege

pymc/model.py

@@ -1067,24 +1067,24 @@ def add_coord(
             raise ValueError(
                 f"Either `values` or `length` must be specified for the '{name}' dimension."
             )
-        if isinstance(length, int):
-            length = at.constant(length)
-        elif length is not None and not isinstance(length, Variable):
-            raise ValueError(
-                f"The `length` passed for the '{name}' coord must be an Aesara Variable or None."
-            )
         if values is not None:
             # Conversion to a tuple ensures that the coordinate values are immutable.
             # Also unlike numpy arrays the's tuple.index(...) which is handy to work with.
             values = tuple(values)
         if name in self.coords:
             if not np.array_equal(values, self.coords[name]):
                 raise ValueError(f"Duplicate and incompatible coordinate: {name}.")
+        if length is not None and not isinstance(length, (int, Variable)):
+            raise ValueError(
+                f"The `length` passed for the '{name}' coord must be an int, Aesara Variable or None."
+            )
         else:
+            if length is None:
+                length = len(values)
             if mutable:
-                self._dim_lengths[name] = length or aesara.shared(len(values))
+                self._dim_lengths[name] = aesara.shared(length)
             else:
-                self._dim_lengths[name] = length or aesara.tensor.constant(len(values))
+                self._dim_lengths[name] = aesara.tensor.constant(length)
             self._coords[name] = values
 
     def add_coords(
@@ -1101,6 +1101,36 @@ def add_coords(
         for name, values in coords.items():
             self.add_coord(name, values, length=lengths.get(name, None))
 
+    def set_dim(self, name: str, new_length: int, coord_values: Optional[Sequence] = None):
+        """Resizes a mutable dimension.
+
+        Parameters
+        ----------
+        name
+            Name of the dimension.
+        new_length
+            New length of the dimension.
+        coord_values
+            Optional sequence of coordinate values.
+        """
+        if not isinstance(self.dim_lengths[name], ScalarSharedVariable):
+            raise ValueError(f"The dimension '{name}' is immutable.")
+        if self.coords.get(name, None) is not None and coord_values is None:
+            raise ValueError(
+                f"'{name}' has coord values. Pass `set_dim(..., coord_values=...)` to update them."
+            )
+        if coord_values is not None:
+            len_cvals = len(coord_values)
+            if len_cvals != new_length:
+                raise ShapeError(
+                    f"Length of new coordinate values does not match the new dimension length.",
+                    actual=len_cvals,
+                    expected=new_length,
+                )
+            self._coords[name] = tuple(coord_values)
+        self.dim_lengths[name].set_value(new_length)
+        return
+
     def set_data(
         self,
         name: str,

pymc/tests/test_model.py

@@ -765,6 +765,39 @@ def test_add_coord_mutable_kwarg():
         assert isinstance(m._dim_lengths["mutable2"], TensorVariable)
 
 
+def test_set_dim():
+    """Test the concious re-sizing of dims created through add_coord()."""
+    with pm.Model() as pmodel:
+        pmodel.add_coord("fdim", mutable=False, length=1)
+        pmodel.add_coord("mdim", mutable=True, length=2)
+        a = pm.Normal("a", dims="mdim")
+    assert a.eval().shape == (2,)
+
+    with pytest.raises(ValueError, match="is immutable"):
+        pmodel.set_dim("fdim", 3)
+
+    pmodel.set_dim("mdim", 3)
+    assert a.eval().shape == (3,)
+
+
+def test_set_dim_with_coords():
+    """Test the concious re-sizing of dims created through add_coord() with coord value."""
+    with pm.Model() as pmodel:
+        pmodel.add_coord("mdim", mutable=True, length=2, values=["A", "B"])
+        a = pm.Normal("a", dims="mdim")
+    assert len(pmodel.coords["mdim"]) == 2
+
+    with pytest.raises(ValueError, match="has coord values"):
+        pmodel.set_dim("mdim", new_length=3)
+
+    with pytest.raises(ShapeError, match="does not match"):
+        pmodel.set_dim("mdim", new_length=3, coord_values=["A", "B"])
+
+    pmodel.set_dim("mdim", 3, ["A", "B", "C"])
+    assert a.eval().shape == (3,)
+    assert pmodel.coords["mdim"] == ("A", "B", "C")
+
+
 @pytest.mark.parametrize("jacobian", [True, False])
 def test_model_logp(jacobian):
     with pm.Model() as m: