%cst = "tf.Const"() {value = dense<[1, -1, 4]> : tensor<3xi32>} : () -> tensor<3xi32>
      %0 = "tf.Slice"(%arg0, %arg1, %cst) {_XlaHasReferenceVars = false, _xla_inferred_shapes = [#tf_type.shape<1x?x4>], device = "/job:localhost/replica:0/task:0/device:TPU:0"} : (tensor<3x3x10xbf16>, tensor<3xi32>, tensor<3xi32>) -> tensor<1x?x4xbf16>
      return %0 : tensor<1x?x4xbf16>
    }
  })";

    // CHECK-NOT: tf.ResourceApplyAdam

  %3 = "tf.AddV2"(%arg0, %1) {_xla_inferred_shapes = [#tf_type.shape<>], device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %4 = "tf.Pack"(%3) {_xla_inferred_shapes = [#tf_type.shape<1>], axis = 0 : i64, device = ""} : (tensor<i32>) -> tensor<1xi32>
  %5 = "tf.Pack"(%arg0) {_xla_inferred_shapes = [#tf_type.shape<1>], axis = 0 : i64, device = ""} : (tensor<i32>) -> tensor<1xi32>

  %outputs_8  =  "tf.Const"() {device = "/job:localhost/replica:0/task:0/device:CPU:0", value = dense<1> : tensor<i32>} : () -> tensor<i32>
  // CHECK: [[elems:%.*]] = "tf.VarHandleOp"
  %outputs_10  =  "tf.VarHandleOp"() {_xla_inferred_shapes = [#tf_type.shape<>], allowed_devices = [], container = "", device = "/job:localhost/replica:0/task:0/device:CPU:0", shared_name = "w"} : () -> tensor<!tf_type.resource<tensor<3x1xf32>>>