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()