fix typos, gradients

pytensor/gradient.py

@@ -1815,17 +1815,22 @@ def random_projection(shape, dtype):
     # This sum() is defined above, it's not the builtin sum.
     if sum_outputs:
         t_rs = [
-            shared(random_projection(o.shape, o.dtype), borrow=True) for o in o_fn_out
+            shared(
+                value=random_projection(o.shape, o.dtype),
+                borrow=True,
+                name=f"random_projection_{i}",
+            )
+            for i, o in enumerate(o_fn_out)
         ]
-        for i, x in enumerate(t_rs):
-            x.name = "ranom_projection_{i}"
         cost = pytensor.tensor.sum(
             [pytensor.tensor.sum(x * y) for x, y in zip(t_rs, o_output)]
         )
     else:
-        t_r = shared(random_projection(o_fn_out.shape, o_fn_out.dtype), borrow=True)
-        t_r.name = "random_projection"
-
+        t_r = shared(
+            value=random_projection(o_fn_out.shape, o_fn_out.dtype),
+            borrow=True,
+            name="random_projection",
+        )
         cost = pytensor.tensor.sum(t_r * o_output)
 
     if no_debug_ref:

pytensor/tensor/nlinalg.py

@@ -6,6 +6,7 @@
 import numpy as np
 from numpy.core.numeric import normalize_axis_tuple  # type: ignore
 
+import pytensor.printing
 from pytensor import scalar as ps
 from pytensor.gradient import DisconnectedType
 from pytensor.graph.basic import Apply
@@ -552,7 +553,7 @@ def __init__(self, full_matrices: bool = True, compute_uv: bool = True):
             if self.full_matrices:
                 self.gufunc_signature = "(m,n)->(m,m),(k),(n,n)"
             else:
-                self.gufunc_signature = "(m,n)->(m,k),(k),(k,n)"
+                self.gufunc_signature = "(m,n)->(o,k),(k),(k,p)"
         else:
             self.gufunc_signature = "(m,n)->(k)"
 
@@ -653,9 +654,10 @@ def h(t):
                 sign_t = ptb.where(ptm.eq(t, 0), 1, ptm.sign(t))
                 return ptm.maximum(ptm.abs(t), eps) * sign_t
 
-            numer = ptb.ones_like(A) - eye
+            numer = ptb.ones((k, k)) - eye
             denom = h(s[None] - s[:, None]) * h(s[None] + s[:, None])
             E = numer / denom
+            E = pytensor.printing.Print("E")(E)
 
             utgu = U.T @ dU
             vtgv = VT @ dV