masahi commented on a change in pull request #10578:
URL: https://github.com/apache/tvm/pull/10578#discussion_r826551789
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File path: src/relay/backend/te_compiler_cache.cc
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@@ -335,15 +336,14 @@ class ScheduleBuilder : public ExprVisitor {
}
}
if (backend::IsMetaScheduleEnabled()) {
- prim_func = tir::CreatePrimFunc(Concat(fn_inputs, tensor_outs));
- Optional<ObjectRef> opt_mod_or_base_func =
- meta_schedule::MetaScheduleContext::QueryInsideWithScope(
- prim_fn_var->name_hint, IRModule({{prim_fn_var, relay_func}}),
target_,
- Array<IRModule>{IRModule({{prim_fn_var, prim_func}})});
- if (const auto* result = opt_mod_or_base_func.as<tir::PrimFuncNode>())
{
- prim_func = GetRef<tir::PrimFunc>(result);
- } else {
- prim_func = tir::PrimFunc(nullptr);
+ auto relay_mod = IRModule({{prim_fn_var, relay_func}});
+ auto tir_mod =
+ IRModule({{prim_fn_var, tir::CreatePrimFunc(Concat(fn_inputs,
tensor_outs))}});
+ IRModule scheduled_mod =
meta_schedule::MetaScheduleContext::QueryInsideWithScope(
+ prim_fn_var->name_hint, relay_mod, target_,
Array<IRModule>{tir_mod});
+ if (scheduled_mod.defined()) {
Review comment:
There is a case this can be be null, see
https://github.com/apache/tvm/blob/d528861449949c06dfe8dbe43dcbcdc415369b38/src/meta_schedule/integration.cc#L143-L145
This happens when not all extracted tasks are added to the tuning database.
In my case, I only tune `dense` and `batch_matmul`, so all other tasks are
filtered out so `ApplyHistoryBest` won't see them. Since `scheduled_mod` is
null, this branch is not taken and `prim_func` will be left `nullptr` as well.
They are scheduled by TE schedules in this branch
https://github.com/apache/tvm/blob/d528861449949c06dfe8dbe43dcbcdc415369b38/src/relay/backend/te_compiler_cache.cc#L349-L353.
The logic is not obvious, but here we see "selectively tune ops of interest
by meta-schedule, the rest by autotvm" in action.
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