cbalint13 commented on code in PR #18545:
URL: https://github.com/apache/tvm/pull/18545#discussion_r2595630076
##########
docs/how_to/tutorials/e2e_opt_model.py:
##########
@@ -95,13 +95,38 @@
# leverage MetaSchedule to tune the model and store the tuning logs to the
database. We also
# apply the database to the model to get the best performance.
#
+# The ResNet18 model will be divided into 20 independent tuning tasks during
compilation.
+# To ensure each task receives adequate tuning resources in one iteration
while providing
+# early feedback:
+#
+# - To quickly observe tuning progress, each task is allocated a maximum of 16
trials per
+# iteration (controlled by ``MAX_TRIALS_PER_TASK=16``). We should set
``TOTAL_TRIALS``
+# to at least ``320 (20 tasks * 16 trials)`` ensures every task receives one
full iteration
Review Comment:
@ConvolutedDog ,
I might not a good tutorialist, i just wanted to avoid hard imperatives
s/"We should {...}"/"We set {...}".
As for 320 / 16 indeed there will be full coverage of trials (some will fail
anyway, but task is not abandoned) per tasks.
LGTM, let it be.
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