def get_classes(rootdir):
classes = []
filedirs = fcfiles.get_filedirs(rootdir)
for filedir in filedirs:
fdict = fcfiles.load_pickle(filedir)
c = fdict['c']
if not c in classes:
classes.append(c)
return classes
def _delete_filedirs(self):
if self.delete_all_previous_epochs_files:
to_delete_filedirs = [
f for f in files.get_filedirs(self.complete_save_roodir)
if files.get_dict_from_filedir(f)['id'] == self.id
]
if len(to_delete_filedirs) > 0:
epochs_to_delete = [
int(files.get_dict_from_filedir(f)['epoch'])
for f in to_delete_filedirs
]
prints.print_red(
f'> (id={self.id}) deleting previous epochs={epochs_to_delete} in={self.complete_save_roodir}'
)
files.delete_filedirs(to_delete_filedirs, verbose=0)
def load_model(
self,
target_id: str = None,
target_epoch: int = None,
):
if target_id is None:
target_id = self.id
if not target_id == self.id:
self.id = target_id
filedirs = files.get_filedirs(self.complete_save_roodir,
fext=C_.SAVE_FEXT)
if len(filedirs) == 0:
prints.print_red(
f'*** no files in {self.complete_save_roodir} ***')
raise Exception(f'*** no files in {self.complete_save_roodir} ***')
return False
if target_epoch is None: # seach the last epoch with that id
filedics = [
files.get_dict_from_filedir(filedir) for filedir in filedirs
]
epochs = [
int(filedic['epoch']) for filedic in filedics
if filedic['id'] == target_id
]
if len(epochs) == 0:
prints.print_red(
f'*** no files with id {target_id} in {self.complete_save_roodir} ***'
)
raise Exception(
f'*** no files with id {target_id} in {self.complete_save_roodir} ***'
)
return False
epochs = sorted(epochs)
target_epoch = epochs[-1]
to_load_filedir = f'{self.complete_save_roodir}/id{C_.KEY_VALUE_SEP_CHAR}{target_id}{C_.KEY_KEY_SEP_CHAR}epoch{C_.KEY_VALUE_SEP_CHAR}{target_epoch}.{C_.SAVE_FEXT}'
prints.print_blue(f'> loading model={to_load_filedir}')
loaded_dic = torch.load(to_load_filedir, map_location=self.device)
self.model.load_state_dict(loaded_dic['state_dict'])
for lmonitor in self.lmonitors:
#lmonitor.history_dict = loaded_dic['lmonitors'][lmonitor.name]
pass
return self.model
def get_band_names(rootdir):
filedirs = fcfiles.get_filedirs(rootdir)
filedir = filedirs[0]
return fcfiles.load_pickle(filedir)['band_names']
def empty_roodir(rootdir):
return len(fcfiles.get_filedirs(rootdir)) == 0
kfs = lcdataset.kfolds if main_args.kf == '.' else main_args.kf
kfs = [kfs] if isinstance(kfs, str) else kfs
setns = [str(setn) for setn in ['train', 'val']
] if main_args.setn == '.' else main_args.setn
setns = [setns] if isinstance(setns, str) else setns
new_lcdataset = lcdataset.copy() # copy with all original lcsets
for setn in setns:
for kf in kfs:
lcset_name = f'{kf}@{setn}'
lcset = new_lcdataset[lcset_name]
synth_rootdir = f'../save/ssne/{main_args.method}/{cfilename}/{lcset_name}'
print('synth_rootdir=', synth_rootdir)
synth_lcset = lcset.copy({}) # copy
filedirs = fcfiles.get_filedirs(synth_rootdir, fext='ssne')
bar = ProgressBar(len(filedirs))
for filedir in filedirs:
d = fcfiles.load_pickle(filedir)
lcobj_name = d['lcobj_name']
bar(f'lcset_name={lcset_name} - lcobj_name={lcobj_name}')
for k, new_lcobj in enumerate(d['new_lcobjs']):
synth_lcset.set_lcobj(f'{lcobj_name}.{k+1}', new_lcobj)
bar.done()
synth_lcset.reset()
new_lcset_name = f'{lcset_name}.{main_args.method}'
new_lcdataset.set_lcset(new_lcset_name, synth_lcset)