Skip to content

Commit

Permalink
[AutoTVM] New rank-binary loss_type for the new xgboost >= 2.0.0 beha…
Browse files Browse the repository at this point in the history
…viour (#14468)

New rank-binary loss_type for the new xgboost >= 2.0.0 behaviour

Signed-off-by: Balint Cristian <[email protected]>
  • Loading branch information
cbalint13 authored Apr 11, 2023
1 parent e5fc9f6 commit 515583c
Show file tree
Hide file tree
Showing 20 changed files with 438 additions and 32 deletions.
36 changes: 35 additions & 1 deletion apps/benchmark/adreno/adreno_gpu_bench_clml.py
Original file line number Diff line number Diff line change
Expand Up @@ -116,6 +116,7 @@ def print_progress(msg):
def tune_tasks(
tasks,
measure_option,
tuner="xgb",
n_trial=1024,
early_stopping=None,
log_filename="tuning.log",
Expand All @@ -127,7 +128,40 @@ def tune_tasks(
for i, tsk in enumerate(reversed(tasks)):
print("Task: ", tsk)
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
tuner_obj = XGBTuner(tsk, loss_type="rank")

# create tuner
if tuner == "xgb":
tuner_obj = XGBTuner(tsk, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(tsk, pop_size=50)
elif tuner == "random":
tuner_obj = RandomTuner(tsk)
elif tuner == "gridsearch":
tuner_obj = GridSearchTuner(tsk)
else:
raise ValueError("Invalid tuner: " + tuner)

tsk_trial = min(n_trial, len(tsk.config_space))
tuner_obj.tune(
Expand Down
36 changes: 35 additions & 1 deletion apps/benchmark/adreno/adreno_gpu_bench_texture.py
Original file line number Diff line number Diff line change
Expand Up @@ -115,6 +115,7 @@ def print_progress(msg):
def tune_tasks(
tasks,
measure_option,
tuner="xgb",
n_trial=1024,
early_stopping=None,
log_filename="tuning.log",
Expand All @@ -126,7 +127,40 @@ def tune_tasks(
for i, tsk in enumerate(reversed(tasks)):
print("Task: ", tsk)
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
tuner_obj = XGBTuner(tsk, loss_type="rank")

# create tuner
if tuner == "xgb":
tuner_obj = XGBTuner(tsk, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(tsk, pop_size=50)
elif tuner == "random":
tuner_obj = RandomTuner(tsk)
elif tuner == "gridsearch":
tuner_obj = GridSearchTuner(tsk)
else:
raise ValueError("Invalid tuner: " + tuner)

tsk_trial = min(n_trial, len(tsk.config_space))
tuner_obj.tune(
Expand Down
38 changes: 37 additions & 1 deletion gallery/how_to/deploy_models/deploy_model_on_adreno.py
Original file line number Diff line number Diff line change
Expand Up @@ -323,7 +323,43 @@
for i, tsk in enumerate(reversed(tasks[:3])):
print("Task:", tsk)
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
tuner_obj = XGBTuner(tsk, loss_type="rank")

# choose tuner
tuner = "xgb"

# create tuner
if tuner == "xgb":
tuner_obj = XGBTuner(tsk, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(tsk, pop_size=50)
elif tuner == "random":
tuner_obj = RandomTuner(tsk)
elif tuner == "gridsearch":
tuner_obj = GridSearchTuner(tsk)
else:
raise ValueError("Invalid tuner: " + tuner)

tsk_trial = min(n_trial, len(tsk.config_space))
tuner_obj.tune(
Expand Down
24 changes: 20 additions & 4 deletions gallery/how_to/tune_with_autotvm/tune_relay_arm.py
Original file line number Diff line number Diff line change
Expand Up @@ -275,14 +275,30 @@ def tune_tasks(
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))

# create tuner
if tuner == "xgb" or tuner == "xgb-rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
if tuner == "xgb":
tuner_obj = XGBTuner(tsk, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(tsk, pop_size=50)
elif tuner == "random":
Expand Down
24 changes: 23 additions & 1 deletion gallery/how_to/tune_with_autotvm/tune_relay_cuda.py
Original file line number Diff line number Diff line change
Expand Up @@ -185,8 +185,30 @@ def tune_tasks(
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))

# create tuner
if tuner == "xgb" or tuner == "xgb-rank":
if tuner == "xgb":
tuner_obj = XGBTuner(tsk, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(tsk, pop_size=100)
elif tuner == "random":
Expand Down
24 changes: 23 additions & 1 deletion gallery/how_to/tune_with_autotvm/tune_relay_mobile_gpu.py
Original file line number Diff line number Diff line change
Expand Up @@ -272,8 +272,30 @@ def tune_tasks(
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))

# create tuner
if tuner == "xgb" or tuner == "xgb-rank":
if tuner == "xgb":
tuner_obj = XGBTuner(tsk, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(tsk, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(tsk, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(tsk, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(tsk, pop_size=50)
elif tuner == "random":
Expand Down
24 changes: 23 additions & 1 deletion gallery/how_to/tune_with_autotvm/tune_relay_x86.py
Original file line number Diff line number Diff line change
Expand Up @@ -154,8 +154,30 @@ def tune_kernels(
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))

# create tuner
if tuner == "xgb" or tuner == "xgb-rank":
if tuner == "xgb":
tuner_obj = XGBTuner(task, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(task, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(task, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(task, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(task, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(task, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(task, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(task, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(task, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(task, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(task, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(task, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(task, pop_size=50)
elif tuner == "random":
Expand Down
39 changes: 38 additions & 1 deletion gallery/tutorial/autotvm_relay_x86.py
Original file line number Diff line number Diff line change
Expand Up @@ -355,7 +355,44 @@
# Tune the extracted tasks sequentially.
for i, task in enumerate(tasks):
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
tuner_obj = XGBTuner(task, loss_type="rank")

# choose tuner
tuner = "xgb"

# create tuner
if tuner == "xgb":
tuner_obj = XGBTuner(task, loss_type="reg")
elif tuner == "xgb_knob":
tuner_obj = XGBTuner(task, loss_type="reg", feature_type="knob")
elif tuner == "xgb_itervar":
tuner_obj = XGBTuner(task, loss_type="reg", feature_type="itervar")
elif tuner == "xgb_curve":
tuner_obj = XGBTuner(task, loss_type="reg", feature_type="curve")
elif tuner == "xgb_rank":
tuner_obj = XGBTuner(task, loss_type="rank")
elif tuner == "xgb_rank_knob":
tuner_obj = XGBTuner(task, loss_type="rank", feature_type="knob")
elif tuner == "xgb_rank_itervar":
tuner_obj = XGBTuner(task, loss_type="rank", feature_type="itervar")
elif tuner == "xgb_rank_curve":
tuner_obj = XGBTuner(task, loss_type="rank", feature_type="curve")
elif tuner == "xgb_rank_binary":
tuner_obj = XGBTuner(task, loss_type="rank-binary")
elif tuner == "xgb_rank_binary_knob":
tuner_obj = XGBTuner(task, loss_type="rank-binary", feature_type="knob")
elif tuner == "xgb_rank_binary_itervar":
tuner_obj = XGBTuner(task, loss_type="rank-binary", feature_type="itervar")
elif tuner == "xgb_rank_binary_curve":
tuner_obj = XGBTuner(task, loss_type="rank-binary", feature_type="curve")
elif tuner == "ga":
tuner_obj = GATuner(task, pop_size=50)
elif tuner == "random":
tuner_obj = RandomTuner(task)
elif tuner == "gridsearch":
tuner_obj = GridSearchTuner(task)
else:
raise ValueError("Invalid tuner: " + tuner)

tuner_obj.tune(
n_trial=min(tuning_option["trials"], len(task.config_space)),
early_stopping=tuning_option["early_stopping"],
Expand Down
2 changes: 1 addition & 1 deletion python/tvm/autotvm/testing/tune_relay.py
Original file line number Diff line number Diff line change
Expand Up @@ -212,7 +212,7 @@ def main():
if ARGS.num_trials > 0:
for i, task in enumerate(tasks):
prefix = "[Task %2d/%2d] " % (i + 1, len(tasks))
tuner_obj = XGBTuner(task, loss_type="rank")
tuner_obj = XGBTuner(task, loss_type="reg")
n_trial = min(len(task.config_space), ARGS.num_trials)
tuner_obj.tune(
n_trial=n_trial,
Expand Down
Loading

0 comments on commit 515583c

Please sign in to comment.