}

    // Erases variable arguments from `batch_func_op`. `erase_indices` contains
    // the indices of the arguments to erase.
    void eraseArguments(const BitVector& erase_indices);

    // Gets the argument operands to the called function.
    operand_range getArgOperands() {
      // Merge `in_tensors` and `captured_tensors`. `operandSegmentSizes`

- Fix azure file migration panic ([#94853](https://github.com/kubernetes/kubernetes/pull/94853), [@andyzhangx](https://github.com/andyzhangx)) [SIG Cloud Provider]
- Fix bug where loadbalancer deletion gets stuck because of missing resource group [#75198](https://github.com/kubernetes/kubernetes/issues/75198) ([#93962](https://github.com/kubernetes/kubernetes/pull/93962), [@phiphi282](https://github.com/phiphi282)) [SIG Cloud Provider]

              }
            ],
            "default": {},
            "description": "Spec for the ResourceClaim. The entire content is copied unchanged into the ResourceClaim that gets created from this template. The same fields as in a ResourceClaim are also valid here."
          }
        },
        "required": [
          "spec"
        ],
        "type": "object"
      },

			},
		},
		"PersistentVolumeClaimVolumeSource must not reference a generated PVC": {
			expectedError: "spec.volumes[0].persistentVolumeClaim.claimName: Invalid value: \"123-ephemeral-volume\": must not reference a PVC that gets created for an ephemeral volume",
			spec: core.Pod{
				ObjectMeta: metav1.ObjectMeta{Name: "123", Namespace: "ns"},
				Spec: core.PodSpec{
					Volumes: []core.Volume{

              }
            ],
            "default": {},
            "description": "The specification for the PersistentVolumeClaim. The entire content is copied unchanged into the PVC that gets created from this template. The same fields as in a PersistentVolumeClaim are also valid here."
          }
        },
        "required": [
          "spec"
        ],
        "type": "object"
      },

            instead of relying on `Model.inputs` and `Model.input_names`, which
            are no longer set for subclass Models. This attr is set in eager,
            `tf.function`, and graph modes. This gets rid of the need for users
            to manually call `Model._set_inputs` when using Custom Training
            Loops(CTLs).
        *   Dynamic shapes are supported for generators by calling the Model on