Is there a way to save final weights of each cycle after running:
learn.fit(lr*4, n_cycle=3, cycle_mult=1, cycle_len=20)
Thanks
Is there a way to save final weights of each cycle after running:
learn.fit(lr*4, n_cycle=3, cycle_mult=1, cycle_len=20)
Thanks
Yes, use the cycle_save_name
param. You can use load_cycle
to load them back later. See the planet_cv notebook for example.
Hello @jeremy,
I use cycle_save_name
but it does not save my weights in tmp/340/models (cf screenshot and I checked the folder content in my terminal, too). How can I solve this issue ?
Note : before learn.fit()
, I have :
def get_data(sz,bs):
tfms = tfms_from_model(arch, sz, aug_tfms=transforms_side_on, max_zoom=1.1)
data = ImageClassifierData.from_csv(PATH, 'train', label_csv, test_name='test', num_workers=4,
val_idxs=val_idxs, suffix='.jpg', tfms=tfms, bs=bs)
return data if sz>300 else data.resize(340, 'tmp')
data = get_data(sz,bs)
learn = ConvLearner.pretrained(arch, data, precompute=True)
Because you didn’t define cycle_len
, there’s no definition of when a ‘cycle’ is finished, so it’s not saving. Try cycle_len=1
, for instance.
Thank you @jeremy !
I keep in mind now that cycle_save_name
and cycle_len
work together :
learn.fit(lr, 5, cycle_len=1, cycle_save_name="MyModel")