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Hparam trial indices #509

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Merged
merged 9 commits into from
Sep 30, 2023
Merged

Hparam trial indices #509

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234eb5a
add hparam index flags to submission_runner
priyakasimbeg Sep 13, 2023
7a0f0f9
fix
priyakasimbeg Sep 13, 2023
fe05acd
clarify
priyakasimbeg Sep 13, 2023
77f44fb
reformatting
priyakasimbeg Sep 13, 2023
0100e44
fix
priyakasimbeg Sep 13, 2023
3c5882b
fix
priyakasimbeg Sep 13, 2023
70cfc72
merge fix
priyakasimbeg Sep 30, 2023
a76083b
fix
priyakasimbeg Sep 30, 2023
88e9d9e
fix
priyakasimbeg Sep 30, 2023
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19 changes: 17 additions & 2 deletions submission_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
import datetime
import gc
import importlib
import itertools
import json
import os
import struct
Expand Down Expand Up @@ -133,6 +134,14 @@
flags.DEFINE_boolean('save_checkpoints',
True,
'Whether or not to checkpoint the model at every eval.')
flags.DEFINE_integer(
'hparam_start_index',
None,
'Start index to slice set of hyperparameters in tuning search space.')
flags.DEFINE_integer(
'hparam_end_index',
None,
'End index to slice set of hyperparameters in tuning spearch space.')
flags.DEFINE_integer(
'rng_seed',
None,
Expand Down Expand Up @@ -455,6 +464,8 @@ def score_submission_on_workload(workload: spec.Workload,
num_tuning_trials: Optional[int] = None,
log_dir: Optional[str] = None,
save_checkpoints: Optional[bool] = True,
hparam_start_index: Optional[bool] = None,
hparam_end_index: Optional[bool] = None,
rng_seed: Optional[int] = None):
# Expand paths because '~' may not be recognized
data_dir = os.path.expanduser(data_dir)
Expand Down Expand Up @@ -500,7 +511,9 @@ def score_submission_on_workload(workload: spec.Workload,
json.load(search_space_file), num_tuning_trials)
all_timings = []
all_metrics = []
for hi, hyperparameters in enumerate(tuning_search_space):
tuning_search_space_iter = itertools.islice(
enumerate(tuning_search_space), hparam_start_index, hparam_end_index)
for hi, hyperparameters in tuning_search_space_iter:
# Generate a new seed from hardware sources of randomness for each trial.
if not rng_seed:
rng_seed = struct.unpack('I', os.urandom(4))[0]
Expand Down Expand Up @@ -545,7 +558,7 @@ def score_submission_on_workload(workload: spec.Workload,
all_timings.append(timing)
all_metrics.append(metrics)
score = min(all_timings)
for ti in range(num_tuning_trials):
for ti, _ in tuning_search_space_iter:
logging.info(f'Tuning trial {ti + 1}/{num_tuning_trials}')
logging.info(f'Hyperparameters: {tuning_search_space[ti]}')
logging.info(f'Metrics: {all_metrics[ti]}')
Expand Down Expand Up @@ -621,6 +634,8 @@ def main(_):
num_tuning_trials=FLAGS.num_tuning_trials,
log_dir=logging_dir_path,
save_checkpoints=FLAGS.save_checkpoints,
hparam_start_index=FLAGS.hparam_start_index,
hparam_end_index=FLAGS.hparam_end_index,
rng_seed=FLAGS.rng_seed)
logging.info(f'Final {FLAGS.workload} score: {score}')

Expand Down