File size: 1,656 Bytes
3894c45 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | """
This enables dynamic loading of models, similarly to what happens with the dataset.
"""
import importlib
from networks.base_model import BaseModel
def find_model_using_name(model_name):
"""Import the module "networks/[model_name]_model.py".
In the file, the class called DatasetNameModel() will
be instantiated. It has to be a subclass of BaseModel,
and it is case-insensitive.
"""
model_filename = "networks." + model_name + "_model"
modellib = importlib.import_module(model_filename)
model = None
target_model_name = model_name.replace('_', '') + 'model'
for name, cls in modellib.__dict__.items():
if name.lower() == target_model_name.lower() \
and issubclass(cls, BaseModel):
model = cls
if model is None:
print("In %s.py, there should be a subclass of BaseModel with class name that matches %s in lowercase." % (model_filename, target_model_name))
exit(0)
return model
def get_model_options(model_name):
model_filename = "networks." + model_name + "_model"
modellib = importlib.import_module(model_filename)
for name, cls in modellib.__dict__.items():
if name.lower() == 'modeloptions':
return cls
return None
def create_model(opt):
"""Create a model given the option.
This function warps the class CustomDatasetDataLoader.
This is the main interface between this package and 'train.py'/'test.py'
Example:
>>> from networks import create_model
>>> model = create_model(opt)
"""
model = find_model_using_name(opt.model)
instance = model(opt)
return instance
|