map2map/map2map/args.py
2021-05-30 23:04:50 -04:00

207 lines
9.2 KiB
Python

import os
import argparse
import json
import warnings
from .train import ckpt_link
def get_args():
"""Parse arguments and set runtime defaults.
"""
parser = argparse.ArgumentParser(
description='Transform field(s) to field(s)')
subparsers = parser.add_subparsers(title='modes', dest='mode', required=True)
train_parser = subparsers.add_parser(
'train',
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
test_parser = subparsers.add_parser(
'test',
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
add_train_args(train_parser)
add_test_args(test_parser)
args = parser.parse_args()
if args.mode == 'train':
set_train_args(args)
elif args.mode == 'test':
set_test_args(args)
return args
def add_common_args(parser):
parser.add_argument('--in-norms', type=str_list, help='comma-sep. list '
'of input normalization functions')
parser.add_argument('--tgt-norms', type=str_list, help='comma-sep. list '
'of target normalization functions')
parser.add_argument('--crop', type=int_tuple,
help='size to crop the input and target data. Default is the '
'field size. Comma-sep. list of 1 or d integers')
parser.add_argument('--crop-start', type=int_tuple,
help='starting point of the first crop. Default is the origin. '
'Comma-sep. list of 1 or d integers')
parser.add_argument('--crop-stop', type=int_tuple,
help='stopping point of the last crop. Default is the opposite '
'corner to the origin. Comma-sep. list of 1 or d integers')
parser.add_argument('--crop-step', type=int_tuple,
help='spacing between crops. Default is the crop size. '
'Comma-sep. list of 1 or d integers')
parser.add_argument('--in-pad', '--pad', default=0, type=int_tuple,
help='size to pad the input data beyond the crop size, assuming '
'periodic boundary condition. Comma-sep. list of 1, d, or dx2 '
'integers, to pad equally along all axes, symmetrically on each, '
'or by the specified size on every boundary, respectively')
parser.add_argument('--tgt-pad', default=0, type=int_tuple,
help='size to pad the target data beyond the crop size, assuming '
'periodic boundary condition, useful for super-resolution. '
'Comma-sep. list with the same format as --in-pad')
parser.add_argument('--scale-factor', default=1, type=int,
help='upsampling factor for super-resolution, in which case '
'crop and pad are sizes of the input resolution')
parser.add_argument('--model', type=str, required=True,
help='(generator) model')
parser.add_argument('--criterion', default='MSELoss', type=str,
help='loss function')
parser.add_argument('--load-state', default=ckpt_link, type=str,
help='path to load the states of model, optimizer, rng, etc. '
'Default is the checkpoint. '
'Start from scratch in case of empty string or missing checkpoint')
parser.add_argument('--load-state-non-strict', action='store_false',
help='allow incompatible keys when loading model states',
dest='load_state_strict')
# somehow I named it "batches" instead of batch_size at first
# "batches" is kept for now for backward compatibility
parser.add_argument('--batch-size', '--batches', type=int, required=True,
help='mini-batch size, per GPU in training or in total in testing')
parser.add_argument('--loader-workers', default=8, type=int,
help='number of subprocesses per data loader. '
'0 to disable multiprocessing')
parser.add_argument('--callback-at', type=lambda s: os.path.abspath(s),
help='directory of custorm code defining callbacks for models, '
'norms, criteria, and optimizers. Disabled if not set. '
'This is appended to the default locations, '
'thus has the lowest priority')
parser.add_argument('--misc-kwargs', default='{}', type=json.loads,
help='miscellaneous keyword arguments for custom models and '
'norms. Be careful with name collisions')
def add_train_args(parser):
add_common_args(parser)
parser.add_argument('--train-style-pattern', type=str, required=True,
help='glob pattern for training data styles')
parser.add_argument('--train-in-patterns', type=str_list, required=True,
help='comma-sep. list of glob patterns for training input data')
parser.add_argument('--train-tgt-patterns', type=str_list, required=True,
help='comma-sep. list of glob patterns for training target data')
parser.add_argument('--val-style-pattern', type=str,
help='glob pattern for validation data styles')
parser.add_argument('--val-in-patterns', type=str_list,
help='comma-sep. list of glob patterns for validation input data')
parser.add_argument('--val-tgt-patterns', type=str_list,
help='comma-sep. list of glob patterns for validation target data')
parser.add_argument('--augment', action='store_true',
help='enable data augmentation of axis flipping and permutation')
parser.add_argument('--aug-shift', type=int_tuple,
help='data augmentation by shifting cropping by [0, aug_shift) pixels, '
'useful for models that treat neighboring pixels differently, '
'e.g. with strided convolutions. '
'Comma-sep. list of 1 or d integers')
parser.add_argument('--aug-add', type=float,
help='additive data augmentation, (normal) std, '
'same factor for all fields')
parser.add_argument('--aug-mul', type=float,
help='multiplicative data augmentation, (log-normal) std, '
'same factor for all fields')
parser.add_argument('--optimizer', default='Adam', type=str,
help='optimization algorithm')
parser.add_argument('--lr', type=float, required=True,
help='initial learning rate')
parser.add_argument('--optimizer-args', default='{}', type=json.loads,
help='optimizer arguments in addition to the learning rate, '
'e.g. --optimizer-args \'{"betas": [0.5, 0.9]}\'')
parser.add_argument('--reduce-lr-on-plateau', action='store_true',
help='Enable ReduceLROnPlateau learning rate scheduler')
parser.add_argument('--scheduler-args', default='{"verbose": true}',
type=json.loads,
help='arguments for the ReduceLROnPlateau scheduler')
parser.add_argument('--init-weight-std', type=float,
help='weight initialization std')
parser.add_argument('--epochs', default=128, type=int,
help='total number of epochs to run')
parser.add_argument('--seed', default=42, type=int,
help='seed for initializing training')
parser.add_argument('--div-data', action='store_true',
help='enable data division among GPUs for better page caching. '
'Data division is shuffled every epoch. '
'Only relevant if there are multiple crops in each field')
parser.add_argument('--div-shuffle-dist', default=1, type=float,
help='distance to further shuffle cropped samples relative to '
'their fields, to be used with --div-data. '
'Only relevant if there are multiple crops in each file. '
'The order of each sample is randomly displaced by this value. '
'Setting it to 0 turn off this randomization, and setting it to N '
'limits the shuffling within a distance of N files. '
'Change this to balance cache locality and stochasticity')
parser.add_argument('--dist-backend', default='nccl', type=str,
choices=['gloo', 'nccl'], help='distributed backend')
parser.add_argument('--log-interval', default=100, type=int,
help='interval (batches) between logging training loss')
parser.add_argument('--detect-anomaly', action='store_true',
help='enable anomaly detection for the autograd engine')
def add_test_args(parser):
add_common_args(parser)
parser.add_argument('--test-style-pattern', type=str, required=True,
help='glob pattern for test data styles')
parser.add_argument('--test-in-patterns', type=str_list, required=True,
help='comma-sep. list of glob patterns for test input data')
parser.add_argument('--test-tgt-patterns', type=str_list, required=True,
help='comma-sep. list of glob patterns for test target data')
parser.add_argument('--num-threads', type=int,
help='number of CPU threads when cuda is unavailable. '
'Default is the number of CPUs on the node by slurm')
def str_list(s):
return s.split(',')
def int_tuple(s):
t = s.split(',')
t = tuple(int(i) for i in t)
if len(t) == 1:
return t[0]
else:
return t
def set_common_args(args):
pass
def set_train_args(args):
set_common_args(args)
args.val = args.val_in_patterns is not None and \
args.val_tgt_patterns is not None
def set_test_args(args):
set_common_args(args)