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import json
from pathlib import Path
from typing import NamedTuple
from typing import Union
from .param import Param
class DatasetConfig(NamedTuple):
param: Param
input_glob: str
target_glob: str
input_mean_path: Path
input_var_path: Path
target_mean_path: Path
target_var_path: Path
seed: int
num_test: int
class ModelConfig(NamedTuple):
in_size: int
num_scale: int
base_num_z: int
out_size: int
class LossConfig(NamedTuple):
l1: float
class TrainConfig(NamedTuple):
batchsize: int
gpu: int
log_iteration: int
snapshot_iteration: int
output: Path
class Config(NamedTuple):
dataset: DatasetConfig
model: ModelConfig
loss: LossConfig
train: TrainConfig
def save_as_json(self, path):
d = _namedtuple_to_dict(self)
json.dump(d, open(path, 'w'), indent=2, sort_keys=True, default=_default_path)
def _default_path(o):
if isinstance(o, Path):
return str(o)
raise TypeError(repr(o) + " is not JSON serializable")
def _namedtuple_to_dict(o: NamedTuple):
return {
k: v if not hasattr(v, '_asdict') else _namedtuple_to_dict(v)
for k, v in o._asdict().items()
}
def create_from_json(s: Union[str, Path]):
try:
d = json.loads(s)
except TypeError:
d = json.load(open(s))
return Config(
dataset=DatasetConfig(
param=Param(),
input_glob=d['dataset']['input_glob'],
target_glob=d['dataset']['target_glob'],
input_mean_path=Path(d['dataset']['input_mean_path']).expanduser(),
input_var_path=Path(d['dataset']['input_var_path']).expanduser(),
target_mean_path=Path(d['dataset']['target_mean_path']).expanduser(),
target_var_path=Path(d['dataset']['target_var_path']).expanduser(),
seed=d['dataset']['seed'],
num_test=d['dataset']['num_test'],
),
model=ModelConfig(
in_size=d['model']['in_size'],
num_scale=d['model']['num_scale'],
base_num_z=d['model']['base_num_z'],
out_size=d['model']['out_size'],
),
loss=LossConfig(
l1=d['loss']['l1'],
),
train=TrainConfig(
batchsize=d['train']['batchsize'],
gpu=d['train']['gpu'],
log_iteration=d['train']['log_iteration'],
snapshot_iteration=d['train']['snapshot_iteration'],
output=Path(d['train']['output']).expanduser(),
),
)
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