// Rebuild the binary. This shows how you can apply the best schedule from a
// log file without reruning the search again.
sch, args = task.compute_dag.apply_steps_from_state(inp.state)
func = tvm.build(sch, args, target)
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// A more complicated example is to resume the search.
// In this case, we need to create the search policy and cost model by ourselves
After Change
print("Equivalent python schedule:")
print(task.print_best(log_file, print_mode="schedule"))
print("CUDA source code:")
print(task.print_best(log_file, print_mode="cuda"))
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// A more complicated example is to resume the search.
