From 3f2decb66335124f4c417ee5452f67fd6a9d48ad Mon Sep 17 00:00:00 2001 From: miheer vaidya Date: Thu, 21 Nov 2019 15:47:31 -0700 Subject: [PATCH 1/3] Use the best tuner possible --- tutorials/autotvm/tune_simple_template.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/autotvm/tune_simple_template.py b/tutorials/autotvm/tune_simple_template.py index dc1b2ce4a4fd..073d1a2b73e1 100644 --- a/tutorials/autotvm/tune_simple_template.py +++ b/tutorials/autotvm/tune_simple_template.py @@ -295,7 +295,7 @@ def matmul(N, L, M, dtype): runner=autotvm.LocalRunner(number=5)) # begin tuning, log records to file `matmul.log` -tuner = autotvm.tuner.RandomTuner(task) +tuner = autotvm.tuner.XGBTuner(task) tuner.tune(n_trial=10, measure_option=measure_option, callbacks=[autotvm.callback.log_to_file('matmul.log')]) From 18bf91821e91e7c713cb3c7731929568c596b455 Mon Sep 17 00:00:00 2001 From: miheer vaidya Date: Fri, 13 Dec 2019 17:07:17 -0700 Subject: [PATCH 2/3] Add comment denoting availability of better tuners --- tutorials/autotvm/tune_simple_template.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/tutorials/autotvm/tune_simple_template.py b/tutorials/autotvm/tune_simple_template.py index 073d1a2b73e1..928145eb5258 100644 --- a/tutorials/autotvm/tune_simple_template.py +++ b/tutorials/autotvm/tune_simple_template.py @@ -32,6 +32,8 @@ # Install dependencies # -------------------- # To use autotvm package in TVM, we need to install some extra dependencies. +# This step is needed if you decide to use xgboost for tuning. This example +# as it is doesn't need xgboost. # (change "3" to "2" if you use python2): # # .. code-block:: bash @@ -294,8 +296,9 @@ def matmul(N, L, M, dtype): builder='local', runner=autotvm.LocalRunner(number=5)) -# begin tuning, log records to file `matmul.log` -tuner = autotvm.tuner.XGBTuner(task) +# begin tuning with RandomTuner, log records to file `matmul.log` +# You can use alternatives like XGBTuner. +tuner = autotvm.tuner.RandomTuner(task) tuner.tune(n_trial=10, measure_option=measure_option, callbacks=[autotvm.callback.log_to_file('matmul.log')]) From 42e4498fb3cfb1296022ac54be08fdf73ea1752d Mon Sep 17 00:00:00 2001 From: miheer vaidya Date: Sat, 14 Dec 2019 14:08:43 -0700 Subject: [PATCH 3/3] Fix typos and wording --- tutorials/autotvm/tune_simple_template.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/tutorials/autotvm/tune_simple_template.py b/tutorials/autotvm/tune_simple_template.py index 928145eb5258..2e877b4cd3cc 100644 --- a/tutorials/autotvm/tune_simple_template.py +++ b/tutorials/autotvm/tune_simple_template.py @@ -32,8 +32,7 @@ # Install dependencies # -------------------- # To use autotvm package in TVM, we need to install some extra dependencies. -# This step is needed if you decide to use xgboost for tuning. This example -# as it is doesn't need xgboost. +# This step (installing xgboost) can be skipped as it doesn't need XGBoost # (change "3" to "2" if you use python2): # # .. code-block:: bash @@ -296,7 +295,7 @@ def matmul(N, L, M, dtype): builder='local', runner=autotvm.LocalRunner(number=5)) -# begin tuning with RandomTuner, log records to file `matmul.log` +# Begin tuning with RandomTuner, log records to file `matmul.log` # You can use alternatives like XGBTuner. tuner = autotvm.tuner.RandomTuner(task) tuner.tune(n_trial=10,