comaniac commented on a change in pull request #7197:
URL: https://github.com/apache/tvm/pull/7197#discussion_r551199732
##########
File path: python/tvm/auto_scheduler/task_scheduler.py
##########
@@ -82,11 +82,12 @@ def make_search_policies(
if isinstance(search_policy, str):
policy_type, model_type = search_policy.split(".")
if model_type == "xgb":
- cost_model = XGBModel(num_warmup_sample=len(tasks) *
num_measures_per_round)
- if load_model_file:
- logger.info("TaskScheduler: Load pretrained model...")
- cost_model.load(load_model_file)
- elif load_log_file:
+ cost_model = XGBModel(
+ num_warmup_sample=len(tasks) * num_measures_per_round,
+ model_file=load_model_file,
+ )
+ if load_log_file:
+ logger.info("TaskScheduler: Reload measured states and
pretrain model...")
Review comment:
```suggestion
logger.info("TaskScheduler: Reload measured states and
pretrained model...")
```
##########
File path: src/auto_scheduler/feature.cc
##########
@@ -1462,12 +1462,18 @@ void GetPerStoreFeaturesFromMeasurePairs(const
Array<MeasureInput>& inputs,
if (find_res == task_cache.end()) {
if (inputs[i]->task->compute_dag.defined()) { // the measure input is
complete
task = inputs[i]->task;
- } else { // the measure input is incomplete
- // rebuild task for incomplete measure pairs read from file
- Array<te::Tensor> tensors = (*workload_key_to_tensors)(workload_key);
- task = SearchTask(ComputeDAG(tensors), workload_key,
inputs[i]->task->target,
- inputs[i]->task->target_host,
inputs[i]->task->hardware_params,
- inputs[i]->task->layout_rewrite_option);
+ } else {
+ // The measure input is incomplete, rebuild task for incomplete
measure pairs read from file
+ try {
+ Array<te::Tensor> tensors = (*workload_key_to_tensors)(workload_key);
+ task = SearchTask(ComputeDAG(tensors), workload_key,
inputs[i]->task->target,
+ inputs[i]->task->target_host,
inputs[i]->task->hardware_params,
+ inputs[i]->task->layout_rewrite_option);
+ } catch (std::exception& e) {
+ // Cannot build ComputeDAG from workload key, the task may have not
been registered in
+ // this search round
+ continue;
Review comment:
Should we have a warning here? Otherwise it may be confusing.
##########
File path: python/tvm/auto_scheduler/cost_model/xgb_model.py
##########
@@ -141,6 +146,12 @@ def update(self, inputs, results):
self.inputs.extend(inputs)
self.results.extend(results)
+ if len(self.inputs) - self.last_train_length < self.last_train_length
/ 5:
Review comment:
```suggestion
if len(inputs) < self.last_train_length / 5:
```
Could you explain a bit more on this logic or make it more straightforward?
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