Add much more flexible argument handling

This commit is contained in:
Guilhem Lavaux 2024-04-03 17:00:41 +02:00
parent fc9cd321e4
commit c0a26290c8
3 changed files with 118 additions and 81 deletions

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@ -1,88 +1,88 @@
arguments:
- 'in-norms':
type: str_list
help: 'comma-sep. list of input normalization functions'
type: str_list
help: 'comma-sep. list of input normalization functions'
- 'tgt-norms':
type: str_list
help: 'comma-sep. list of target normalization functions'
type: str_list
help: 'comma-sep. list of target normalization functions'
- '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'
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'
- 'crop-start':
type: int_tuple
help: 'starting point of the first crop. Default is the origin. Comma-sep. list of 1 or d integers'
type: int_tuple
help: 'starting point of the first crop. Default is the origin. Comma-sep. list of 1 or d integers'
- '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'
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'
- 'crop-step':
type: int_tuple
help: 'spacing between crops. Default is the crop size. Comma-sep. list of 1 or d integers'
type: int_tuple
help: 'spacing between crops. Default is the crop size. Comma-sep. list of 1 or d integers'
- 'in-pad':
'pad': 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'
pad: 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'
- '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'
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'
- 'scale-factor':
default: 1
type: int
help: 'upsampling factor for super-resolution, in which case crop and pad are sizes of the input resolution'
default: 1
type: int
help: 'upsampling factor for super-resolution, in which case crop and pad are sizes of the input resolution'
- 'model':
type: str
required: true
help: '(generator) model'
type: str
required: true
help: '(generator) model'
- 'criterion':
default: 'MSELoss'
type: str
help: 'loss function'
default: 'MSELoss'
type: str
help: 'loss function'
- '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'
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'
- 'load-state-non-strict':
action: 'store_false'
help: 'allow incompatible keys when loading model states'
dest: 'load_state_strict'
action: 'store_false'
help: 'allow incompatible keys when loading model states'
dest: 'load_state_strict'
- 'batch-size':
'batches': 0
type: int
required: true
help: 'mini-batch size, per GPU in training or in total in testing'
'batches': 0
type: int
required: true
help: 'mini-batch size, per GPU in training or in total in testing'
- 'loader-workers':
default: 8
type: int
help: 'number of subprocesses per data loader. 0 to disable multiprocessing'
default: 8
type: int
help: 'number of subprocesses per data loader. 0 to disable multiprocessing'
- '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'
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'
- 'misc-kwargs':
default: '{}'
type: json.loads
help: 'miscellaneous keyword arguments for custom models and norms. Be careful with name collisions'
arguments:
- 'optimizer':
default: 'Adam'
type: str
help: 'optimizer for training'
- 'learning-rate':
default: 0.001
type: float
help: 'learning rate for training'
- 'num-epochs':
default: 100
type: int
help: 'number of training epochs'
- 'save-interval':
default: 10
type: int
help: 'interval for saving checkpoints during training'
- 'log-interval':
default: 10
type: int
help: 'interval for logging training progress'
- 'device':
default: 'cuda'
type: str
help: 'device for training (cuda or cpu)'
default: '{}'
type: json.loads
help: 'miscellaneous keyword arguments for custom models and norms. Be careful with name collisions'
arguments:
- 'optimizer':
default: 'Adam'
type: str
help: 'optimizer for training'
- 'learning-rate':
default: 0.001
type: float
help: 'learning rate for training'
- 'num-epochs':
default: 100
type: int
help: 'number of training epochs'
- 'save-interval':
default: 10
type: int
help: 'interval for saving checkpoints during training'
- 'log-interval':
default: 10
type: int
help: 'interval for logging training progress'
- 'device':
default: 'cuda'
type: str
help: 'device for training (cuda or cpu)'

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@ -1,17 +1,53 @@
from .args import get_args
from . import train
from . import test
import click
import os
import yaml
try:
from yaml import CLoader as Loader
except ImportError:
from yaml import Loader
import importlib.resources
def main():
def _load_resource_file(resource_path):
package = importlib.import_module('map2map') # Import the package
with importlib.resources.path('map2map', resource_path) as path:
return path.read_text() # Read the file and return its content
def str_list(s):
return s.split(',')
def m2m_options(f):
common_args = _load_resource_file('common_args.yaml')
for arg in common_args['arguments']:
argopt = common_args[arg]
if 'type' in argopt:
argopt['type'] = eval(argopt['type'])
f = click.option(f'--{arg}', **argopt)(f)
else:
f = click.option(f'--{arg}', **argopt)(f)
return f
@click.group()
@click.option("--config", type=click.Path())
@click.pass_context
def main(ctx, config):
if os.path.exists(config):
with open(config, 'r') as f:
config = yaml.load(f.read(), Loader=Loader)
ctx.default_map = config
@main.command()
@m2m_options
def train(**kwargs):
args = get_args()
train.node_worker(args)
if args.mode == 'train':
train.node_worker(args)
elif args.mode == 'test':
test.test(args)
if __name__ == '__main__':
main()
@main.command()
@m2m_options
def test():
test.test(args)

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@ -17,7 +17,8 @@ dependencies = [
'numpy',
'scipy',
'matplotlib',
'tensorboard']
'tensorboard',
'click']
authors = [
{name = "Yin Li", email = "eelregit@gmail.com"},
@ -29,7 +30,7 @@ maintainers = [
]
[project.scripts]
m2m = "map2map:main"
m2m = "map2map:main.main"
[project.urls]
#Homepage = "https://example.com"