Shape-as-Point/optim_hierarchy.py

import argparse
import os

from src.utils import load_config

os.environ["MKL_THREADING_LAYER"] = "GNU"


def main():
    parser = argparse.ArgumentParser(description="MNIST toy experiment")
    parser.add_argument("config", type=str, help="Path to config file.")
    parser.add_argument("--start_res", type=int, default=-1, help="Resolution to start with.")
    parser.add_argument("--object_id", type=int, default=-1, help="Object index.")

    args, unknown = parser.parse_known_args()
    cfg = load_config(args.config, "configs/default.yaml")

    resolutions = [32, 64, 128, 256]
    iterations = [1000, 1000, 1000, 200]
    lrs = [2e-3, 2e-3 * 0.7, 2e-3 * (0.7**2), 2e-3 * (0.7**3)]  # reduce lr
    for idx, (res, iteration, lr) in enumerate(zip(resolutions, iterations, lrs)):
        if res < args.start_res:
            continue

        if res > cfg["model"]["grid_res"]:
            continue

        psr_sigma = 2 if res <= 128 else 3

        if res > 128:
            psr_sigma = 5 if "thingi_noisy" in args.config else 3

        if args.object_id != -1:
            out_dir = os.path.join(cfg["train"]["out_dir"], "object_%02d" % args.object_id, "res_%d" % res)
        else:
            out_dir = os.path.join(cfg["train"]["out_dir"], "res_%d" % res)

        # sample from mesh when resampling is enabled, otherwise reuse the pointcloud
        init_shape = "mesh" if cfg["train"]["resample_every"] > 0 else "pointcloud"

        if args.object_id != -1:
            input_mesh = (
                "None"
                if idx == 0
                else os.path.join(
                    cfg["train"]["out_dir"],
                    "object_%02d" % args.object_id,
                    "res_%d" % (resolutions[idx - 1]),
                    "vis",
                    init_shape,
                    "%04d.ply" % (iterations[idx - 1]),
                )
            )
        else:
            input_mesh = (
                "None"
                if idx == 0
                else os.path.join(
                    cfg["train"]["out_dir"],
                    "res_%d" % (resolutions[idx - 1]),
                    "vis",
                    init_shape,
                    "%04d.ply" % (iterations[idx - 1]),
                )
            )

        cmd = "export MKL_SERVICE_FORCE_INTEL=1 && "
        cmd += (
            "python optim.py %s --model:grid_res %d --model:psr_sigma %d \
                                   --train:input_mesh %s --train:total_epochs %d \
                                   --train:out_dir %s --train:lr_pcl %f \
                                   --data:object_id %d"
            % (args.config, res, psr_sigma, input_mesh, iteration, out_dir, lr, args.object_id)
        )
        print(cmd)
        os.system(cmd)


if __name__ == "__main__":
    main()