numba

Author: Armavica

pytensor/link/numba/dispatch/extra_ops.py

@@ -186,7 +186,7 @@ def ravelmultiindex(*inp):
 
             new_arr = arr.T.astype(np.float64).copy()
             for i, b in enumerate(new_arr):
-                for j, (d, v) in enumerate(zip(shape, b, strict=True)):
+                for j, (d, v) in enumerate(zip(shape, b)):  # noqa: B905
                     if v < 0 or v >= d:
                         mode_fn(new_arr, i, j, v, d)
 

pytensor/link/numba/dispatch/scalar.py

@@ -118,7 +118,7 @@ def {scalar_op_fn_name}({input_names}):
             [
                 f"direct_cast({i_name}, {i_tmp_dtype_name})"
                 for i_name, i_tmp_dtype_name in zip(
-                    input_names, input_tmp_dtype_names.keys(), strict=True
+                    input_names, input_tmp_dtype_names.keys(), strict=False
                 )
             ]
         )

pytensor/link/numba/dispatch/slinalg.py

@@ -421,7 +421,7 @@ def block_diag(*arrs):
         out = np.zeros((out_shape[0], out_shape[1]), dtype=dtype)
 
         r, c = 0, 0
-        for arr, shape in zip(arrs, shapes, strict=True):
+        for arr, shape in zip(arrs, shapes):  # noqa: B905
             rr, cc = shape
             out[r : r + rr, c : c + cc] = arr
             r += rr