diff --git a/docs/Custom_Operation_for_GPUs.md b/docs/Custom_Operation_for_GPUs.md
index 6e9b0a0ad..44cdaf1f1 100644
--- a/docs/Custom_Operation_for_GPUs.md
+++ b/docs/Custom_Operation_for_GPUs.md
@@ -236,7 +236,7 @@ def _rms_norm_fwd_cuda_lowering(ctx, x, weight, eps):
     )
     out = custom_call(
         b"rms_forward_affine_mixed_dtype",
-        out_types=[
+        result_types=[
             ir.RankedTensorType.get(x_shape, w_type.element_type),
             ir.RankedTensorType.get((n1,), iv_element_type),
         ],
@@ -244,7 +244,7 @@ def _rms_norm_fwd_cuda_lowering(ctx, x, weight, eps):
         backend_config=opaque,
         operand_layouts=default_layouts(x_shape, w_shape),
         result_layouts=default_layouts(x_shape, (n1,)),
-    )
+    ).results
     return out
 
 
@@ -277,7 +277,7 @@ def _rms_norm_bwd_cuda_lowering(ctx, grad_output, invvar, x, weight, eps):
     )
     out = custom_call(
         b"rms_backward_affine",
-        out_types=[
+        result_types=[
             ir.RankedTensorType.get(x_shape, x_type.element_type),
             ir.RankedTensorType.get(w_shape, w_type.element_type),
             ir.RankedTensorType.get(part_grad_shape, iv_type.element_type),
@@ -286,7 +286,7 @@ def _rms_norm_bwd_cuda_lowering(ctx, grad_output, invvar, x, weight, eps):
         backend_config=opaque,
         operand_layouts=default_layouts(x_shape, (n1,), x_shape, w_shape),
         result_layouts=default_layouts(x_shape, w_shape, part_grad_shape),
-    )
+    ).results
     return out
 
 
@@ -345,7 +345,7 @@ See [How JAX primitives work](https://jax.readthedocs.io/en/latest/notebooks/How
 from functools import reduce
 from operator import mul
 
-from jax.abstract_arrays import ShapedArray
+from jax.core import ShapedArray
 
 
 def _rms_norm_fwd_abstract(x, weight, eps):
@@ -804,7 +804,7 @@ import jax
 import jax.numpy as jnp
 from build import gpu_ops
 from jax import core, dtypes
-from jax.abstract_arrays import ShapedArray
+from jax.core import ShapedArray
 from jax.experimental.maps import xmap
 from jax.experimental.pjit import pjit
 from jax.interpreters import mlir, xla
@@ -887,7 +887,7 @@ def _rms_norm_fwd_cuda_lowering(ctx, x, weight, eps):
     )
     out = custom_call(
         b"rms_forward_affine_mixed_dtype",
-        out_types=[
+        result_types=[
             ir.RankedTensorType.get(x_shape, w_type.element_type),
             ir.RankedTensorType.get((n1,), iv_element_type),
         ],
@@ -895,7 +895,7 @@ def _rms_norm_fwd_cuda_lowering(ctx, x, weight, eps):
         backend_config=opaque,
         operand_layouts=default_layouts(x_shape, w_shape),
         result_layouts=default_layouts(x_shape, (n1,)),
-    )
+    ).results
     return out
 
 
@@ -928,7 +928,7 @@ def _rms_norm_bwd_cuda_lowering(ctx, grad_output, invvar, x, weight, eps):
     )
     out = custom_call(
         b"rms_backward_affine",
-        out_types=[
+        result_types=[
             ir.RankedTensorType.get(x_shape, x_type.element_type),
             ir.RankedTensorType.get(w_shape, w_type.element_type),
             ir.RankedTensorType.get(part_grad_shape, iv_type.element_type),
@@ -937,7 +937,7 @@ def _rms_norm_bwd_cuda_lowering(ctx, grad_output, invvar, x, weight, eps):
         backend_config=opaque,
         operand_layouts=default_layouts(x_shape, (n1,), x_shape, w_shape),
         result_layouts=default_layouts(x_shape, w_shape, part_grad_shape),
-    )
+    ).results
     return out
 
 
diff --git a/jax/_src/interpreters/mlir.py b/jax/_src/interpreters/mlir.py
index 5cfaff667..dac8e34f6 100644
--- a/jax/_src/interpreters/mlir.py
+++ b/jax/_src/interpreters/mlir.py
@@ -1453,7 +1453,7 @@ def jaxpr_subcomp(ctx: ModuleContext, jaxpr: core.Jaxpr,
       out_nodes = tuple(map(wrap_singleton_ir_values, ans))
     except TypeError as e:
       raise ValueError("Output of translation rule must be iterable: "
-                       f"{eqn}, got output {ans}") from e
+                       f"{eqn}, got output {ans} from {rule.__name__}") from e
 
     assert all(isinstance(v, tuple) for v in out_nodes), (ans, eqn)
     assert all(isinstance(v, ir.Value) for w in out_nodes for v in w), (