replacer.create<mlir::func::ReturnOp>(yield_op.getLoc(),
                                            yield_op.getOperands());
      yield_op.erase();
    }

    // Remap the captured operands in the (former) island block with newly
    // created entry block arguments in the function body.
    {
      Block &entry_block = outlined_func.getBody().front();

// TODO(jayconrod): add method to resize the buffer. We'll need that when the
// mutator can increase input length. Only the coordinator will be able to
// do it, since we'll need to send a message to the worker telling it to

  let constructor = "mlir::tf_saved_model::CreateDedupBoundInputBindingPass()";
}

def LowerGlobalsToMlProgramPass: Pass<"tf-saved-model-lower-globals-to-mlprogram", "mlir::ModuleOp"> {
  let summary = "Remove (and remap) function arguments that map to global tensors.";
  let description = [{
    This pass will lower AssignVariableOp and ReadVariableOp to their ml_program

}

// mapRType asserts that typ is a map type, and returns an expression
// that yields the *runtime._type value representing typ.
func mapRType(pos src.XPos, typ *types.Type) ir.Node {
	return kindRType(pos, typ, types.TMAP)
}

// chanRType asserts that typ is a map type, and returns an expression
// that yields the *runtime._type value representing typ.
func chanRType(pos src.XPos, typ *types.Type) ir.Node {