func::FuncOp func() {
      return SymbolTable::lookupNearestSymbolFrom<func::FuncOp>(*this, getF());
    }

    // 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() {

      }
    }
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/apps/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getAppsV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

            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

		x := v_0
		v.reset(OpAMD64ROUNDSD)
		v.AuxInt = int8ToAuxInt(1)
		v.AddArg(x)
		return true
	}
}
func rewriteValueAMD64_OpGetG(v *Value) bool {
	v_0 := v.Args[0]
	// match: (GetG mem)
	// cond: v.Block.Func.OwnAux.Fn.ABI() != obj.ABIInternal
	// result: (LoweredGetG mem)
	for {
		mem := v_0
		if !(v.Block.Func.OwnAux.Fn.ABI() != obj.ABIInternal) {
			break
		}

		v.AddArg2(v0, v1)
		return true
	}
}
func rewriteValuegeneric_OpNilCheck(v *Value) bool {
	v_1 := v.Args[1]
	v_0 := v.Args[0]
	b := v.Block
	fe := b.Func.fe
	// match: (NilCheck ptr:(GetG mem) mem)
	// result: ptr
	for {
		ptr := v_0
		if ptr.Op != OpGetG {
			break
		}
		mem := ptr.Args[0]
		if mem != v_1 {
			break
		}
		v.copyOf(ptr)