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run_metrics.py
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run_metrics.py
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"""Main entry point for calculating the metrics for MSG-StyleGAN network."""
import os
import config
import dnnlib
import dnnlib.tflib as tflib
from dnnlib import EasyDict
from metrics import metric_base
from training import misc
# ----------------------------------------------------------------------------
def run_pickle(submit_config, metric_args, network_pkl, dataset_args, mirror_augment):
ctx = dnnlib.RunContext(submit_config)
tflib.init_tf()
print(
'Evaluating %s metric on network_pkl "%s"...' % (metric_args.name, network_pkl)
)
metric = dnnlib.util.call_func_by_name(**metric_args)
print()
metric.run(
network_pkl,
dataset_args=dataset_args,
mirror_augment=mirror_augment,
num_gpus=submit_config.num_gpus,
)
print()
ctx.close()
# ----------------------------------------------------------------------------
def run_snapshot(submit_config, metric_args, run_id, snapshot):
ctx = dnnlib.RunContext(submit_config)
tflib.init_tf()
print(
"Evaluating %s metric on run_id %s, snapshot %s..."
% (metric_args.name, run_id, snapshot)
)
run_dir = misc.locate_run_dir(run_id)
network_pkl = misc.locate_network_pkl(run_dir, snapshot)
metric = dnnlib.util.call_func_by_name(**metric_args)
print()
metric.run(network_pkl, run_dir=run_dir, num_gpus=submit_config.num_gpus)
print()
ctx.close()
# ----------------------------------------------------------------------------
def run_all_snapshots(submit_config, metric_args, run_id):
ctx = dnnlib.RunContext(submit_config)
tflib.init_tf()
print(
"Evaluating %s metric on all snapshots of run_id %s..."
% (metric_args.name, run_id)
)
run_dir = misc.locate_run_dir(run_id)
network_pkls = misc.list_network_pkls(run_dir)
metric = dnnlib.util.call_func_by_name(**metric_args)
print()
for idx, network_pkl in enumerate(network_pkls):
ctx.update("", idx, len(network_pkls))
metric.run(network_pkl, run_dir=run_dir, num_gpus=submit_config.num_gpus)
print()
ctx.close()
# ----------------------------------------------------------------------------
def main():
submit_config = dnnlib.SubmitConfig()
# Which metrics to evaluate?
metrics = []
metric_base.fid50k.update(
{"inception_net_path": os.path.join(config.result_dir, "inception_network", "inception_v3_features.pkl")})
metrics += [metric_base.fid50k]
# Which networks to evaluate them on?
tasks = []
tasks += [
EasyDict(
run_func_name="run_metrics.run_pickle",
network_pkl="/home/karnewar/msg-stylegan/00002-msg-stylegan-indian_celebs-4gpu/network-snapshot.pkl",
dataset_args=EasyDict(tfrecord_dir="indian_celebs/tfrecords", shuffle_mb=0),
mirror_augment=True,
)
]
# tasks += [EasyDict(run_func_name='run_metrics.run_snapshot', run_id=100, snapshot=25000)]
# tasks += [EasyDict(run_func_name='run_metrics.run_all_snapshots', run_id=100)]
# How many GPUs to use?
submit_config.num_gpus = 1
# submit_config.num_gpus = 2
# submit_config.num_gpus = 4
# submit_config.num_gpus = 8
# Execute.
submit_config.run_dir_root = dnnlib.submission.submit.get_template_from_path(
config.result_dir
)
submit_config.run_dir_ignore += config.run_dir_ignore
for task in tasks:
for metric in metrics:
submit_config.run_desc = "%s-%s" % (task.run_func_name, metric.name)
if task.run_func_name.endswith("run_snapshot"):
submit_config.run_desc += "-%s-%s" % (task.run_id, task.snapshot)
if task.run_func_name.endswith("run_all_snapshots"):
submit_config.run_desc += "-%s" % task.run_id
submit_config.run_desc += "-%dgpu" % submit_config.num_gpus
dnnlib.submit_run(submit_config, metric_args=metric, **task)
# ----------------------------------------------------------------------------
if __name__ == "__main__":
main()
# ----------------------------------------------------------------------------