// Print equivalent python schedule API. This can be used for debugging and
// learning the behavior of the auto-scheduler.
print("Equivalent python schedule:")
print(task.compute_dag.print_python_code_from_state(inp.state))
// 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)
After Change
print(task.print_best(log_file, print_mode="schedule"))
print("CUDA source code:")
print(task.print_best(log_file, print_mode="cuda"))
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// A more complicated example is to resume the search.
// In this case, we need to create the search policy and cost model by ourselves
