You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
50 lines
1017 B
50 lines
1017 B
"""Params for DANN."""
|
|
|
|
import os
|
|
|
|
# params for path
|
|
dataset_root = os.path.expanduser(os.path.join('~', 'Datasets'))
|
|
model_root = os.path.expanduser(os.path.join('~', 'Models', 'pytorch-DANN'))
|
|
|
|
# params for datasets and data loader
|
|
|
|
batch_size = 64
|
|
|
|
office_image_size = 227
|
|
|
|
# params for source dataset
|
|
src_dataset = "amazon31"
|
|
src_model_trained = True
|
|
src_classifier_restore = os.path.join(model_root,src_dataset + '-source-classifier-final.pt')
|
|
class_num_src = 31
|
|
|
|
# params for target dataset
|
|
tgt_dataset = "webcam31"
|
|
tgt_model_trained = True
|
|
dann_restore = os.path.join(model_root , src_dataset + '-' + tgt_dataset + '-dann-final.pt')
|
|
|
|
# params for pretrain
|
|
num_epochs_src = 100
|
|
log_step_src = 10
|
|
save_step_src = 20
|
|
eval_step_src = 20
|
|
|
|
# params for training dann
|
|
|
|
## for digit
|
|
# num_epochs = 400
|
|
# log_step = 100
|
|
# save_step = 20
|
|
# eval_step = 20
|
|
|
|
## for office
|
|
num_epochs = 1000
|
|
log_step = 10 # iters
|
|
save_step = 500
|
|
eval_step = 5 # epochs
|
|
|
|
manual_seed = 8888
|
|
alpha = 0
|
|
|
|
# params for optimizing models
|
|
lr = 2e-4
|