Make reshape ndim kwarg only

This prevents surprises when passing two scalars, which are interpreted differently in the numpy API

Author: ricardoV94

pytensor/tensor/extra_ops.py

@@ -708,7 +708,10 @@ def grad(self, inputs, gout):
             shape = [x.shape[k] for k in range(x.ndim)]
             shape.insert(axis, repeats)
 
-            return [gz.reshape(shape, x.ndim + 1).sum(axis=axis), DisconnectedType()()]
+            return [
+                gz.reshape(shape, ndim=x.ndim + 1).sum(axis=axis),
+                DisconnectedType()(),
+            ]
         elif repeats.ndim == 1:
             # For this implementation, we would need to specify the length
             # of repeats in order to split gz in the right way to sum

pytensor/tensor/math.py

@@ -2196,7 +2196,7 @@ def _tensordot_as_dot(a, b, axes, dot, batched):
         b_reshaped = b.reshape(b_shape)
 
         out_reshaped = dot(a_reshaped, b_reshaped)
-        out = out_reshaped.reshape(outshape, outndim)
+        out = out_reshaped.reshape(outshape, ndim=outndim)
         # Make sure the broadcastable pattern of the result is correct,
         # since some shape information can be lost in the reshapes.
         if out.type.broadcastable != outbcast:

pytensor/tensor/rewriting/subtensor.py

@@ -155,7 +155,7 @@ def transform_take(a, indices, axis):
 
     ndim = a.ndim + indices.ndim - 1
 
-    return transform_take(a, indices.flatten(), axis).reshape(shape, ndim)
+    return transform_take(a, indices.flatten(), axis).reshape(shape, ndim=ndim)
 
 
 def is_full_slice(x):

pytensor/tensor/slinalg.py

@@ -580,7 +580,7 @@ def kron(a, b):
             f"You passed {int(a.ndim)} and {int(b.ndim)}."
         )
     o = atm.outer(a, b)
-    o = o.reshape(at.concatenate((a.shape, b.shape)), a.ndim + b.ndim)
+    o = o.reshape(at.concatenate((a.shape, b.shape)), ndim=a.ndim + b.ndim)
     shf = o.dimshuffle(0, 2, 1, *list(range(3, o.ndim)))
     if shf.ndim == 3:
         shf = o.dimshuffle(1, 0, 2)

pytensor/tensor/var.py

@@ -283,7 +283,7 @@ def all(self, axis=None, keepdims=False):
     #                     "Variable) due to Python restriction. You can use "
     #                     "PyTensorVariable.shape[0] instead.")
 
-    def reshape(self, shape, ndim=None):
+    def reshape(self, shape, *, ndim=None):
         """Return a reshaped view/copy of this variable.
 
         Parameters