antinucleon opened a new pull request #7053:
URL: https://github.com/apache/tvm/pull/7053
This PR enables correctness check for a generated schedule.
It is useful for:
- Metal / ROCM: For some invalid schedule, driver may skip it instead of
return any errors (which will show as an impossble large FLOPS number)
- Sparse kernel search
Example 1: correctness check. This will generate random buffers for
correctness check
```
if train_flag:
#measure_ctx = auto_scheduler.LocalRPCMeasureContext(min_repeat_ms=300)
measure_runner = auto_scheduler.RPCRunner("m1", "127.0.0.1", 9190,
min_repeat_ms=300, timeout=30, repeat=3)
tune_option = auto_scheduler.TuningOptions(
num_measure_trials=1500,
check_correctness=True,
builder_n_parallel=1,
runner=measure_runner,
measure_callbacks=[auto_scheduler.RecordToFile(log_file)],
verbose=2,
)
sch, args = auto_scheduler.auto_schedule(task,
tuning_options=tune_option)
```
Example 2: Sparse tuning, this will register given buffers for measure.
```
if train_flag:
#measure_ctx = auto_scheduler.LocalRPCMeasureContext(min_repeat_ms=300)
measure_runner = auto_scheduler.RPCRunner("m1", "127.0.0.1", 9190,
min_repeat_ms=300, timeout=30, repeat=3)
tune_option = auto_scheduler.TuningOptions(
num_measure_trials=1500,
#runner=measure_ctx.runner,
check_correctness=False,
builder_n_parallel=1,
runner=measure_runner,
measure_callbacks=[auto_scheduler.RecordToFile(log_file)],
verbose=2,
)
for k, v in BUFFER.items():
tune_option.register_buffer(k, v)
```
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