def test_nconv_checkpoint_and_load_cli(self):
args = self.train_args + (
f'-o {self.out_dir}/nconv.mdl -na nconv -ne 2 -nl 1 -ps 16 '
f'-ocf {self.jsonfn} -bs 2 -chk 1').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
args = self.train_args + (
f'-o {self.out_dir}/nconv.mdl -na nconv -ne 2 -nl 1 -ps 16 '
f'-ocf {self.jsonfn} -bs 2').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_writecsv_cli(self):
args = self.train_args + (
f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 3 -nl 1 -ps 16 '
f'-ocf {self.jsonfn} -bs 2 -lrs -v -csv {self.out_dir}/test.csv'
).split()
retval = nn_train(args)
self.assertEqual(retval, 0)
def test_nconv_3d_var_cli(self):
args = self.train_args + (f'-o {self.out_dir}/unet.mdl -na nconv -ne 1 -nl 1 -cbp 1 -ps 0 -bs 1 --net3d '
f'-ocf {self.jsonfn}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, calc_var=True)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_ord_3d_temperature_map_cli(self):
args = self.train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -bs 4 -ps 16 -3d '
f'-ocf {self.jsonfn} -ord 1 10 5 -vs 0').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, temperature_map=True)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_vae_3d_cli(self):
args = self.train_args + (f'-o {self.out_dir}/vae.mdl -na vae -ne 1 -nl 3 -cbp 1 -ps 16 -bs 4 --net3d '
f'--img-dim 16 16 16 --latent-size 10 -ocf {self.jsonfn}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_no_skip_cli(self):
args = self.train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -ps 16 -bs 2 --net3d --no-skip '
f'-ocf {self.jsonfn}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_lr_scheduler_cli(self):
args = self.train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 3 -nl 1 -ps 16 '
f'-ocf {self.jsonfn} -bs 2 -lrs -v').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_whole_img_cli(self):
args = self.train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 1 -nl 1 -ps 0 -3d '
f'-ocf {self.jsonfn} -bs 1').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_vae_2d_5l_cli(self):
train_args = f'-s {self.train_dir}/tif/ -t {self.train_dir}/tif/'.split(
)
args = train_args + (
f'-o {self.out_dir}/vae.mdl -na vae -ne 1 -nl 5 -cbp 1 -bs 4 -e tif -ps 32 '
f'--img-dim 32 32 --latent-size 10 -ocf {self.jsonfn} -sa 0'
).split()
retval = nn_train(args)
self.assertEqual(retval, 0)
def test_unet_ord_3d_cli(self):
args = self.train_args + (
f'-o {self.out_dir}/unet.mdl -na unet -ne 2 -nl 3 -cbp 1 -bs 4 -ps 16 -3d '
f'-ocf {self.jsonfn} -ord 1 10 2 -vs 0.5 -ns -dp 0.5').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_layernorm_cli(self):
args = self.train_args + (
f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 2 -cbp 1 -ps 16 -bs 2 --net3d '
f'-ocf {self.jsonfn} -nm layer').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_2d_var_cli(self):
train_args = f'-s {self.train_dir}/1/ -t {self.train_dir}/2/'.split()
args = train_args + (f'-o {self.out_dir}/unet.mdl -na nconv -ne 1 -nl 1 -cbp 1 -ps 0 -bs 2 --tiff '
f'-ocf {self.jsonfn}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, calc_var=True)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_nopatch_cli(self):
args = self.train_args + (f'-o {self.out_dir}/nconv_nopatch.mdl -na nconv -ne 1 -nl 2 -ps 0 -bs 2 '
f'--plot-loss {self.out_dir}/loss.png -ocf {self.jsonfn} '
f'-vsd {self.train_dir} -vtd {self.train_dir}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_multimodal_cli(self):
train_args = f'-s {self.train_dir}/1/ {self.train_dir}/1/ -t {self.train_dir}/2/ {self.train_dir}/2/'.split()
args = train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -ps 16 -bs 2 --tiff '
f'-ocf {self.jsonfn}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, multi=2)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_multimodal_tiff_cli(self):
train_args = f'-s {self.train_dir}/1/ {self.train_dir}/1/ -t {self.train_dir}/2/ {self.train_dir}/2/'.split()
args = train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 1 -nl 1 -ps 16 '
f'-ocf {self.jsonfn} -bs 2 --tiff').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, multi=2)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_ord_2d_temperature_map_cli(self):
train_args = f'-s {self.train_dir}/1/ -t {self.train_dir}/2/'.split()
args = train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -bs 4 --tiff '
f'-ocf {self.jsonfn} -ord 1 10 3 -vs 0 -ns').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, temperature_map=True)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_data_aug_3d_cli(self):
args = self.train_args + (f'-o {self.out_dir}/nconv_nopatch.mdl -na nconv -ne 1 -nl 2 -ps 0 -bs 2 '
f'--plot-loss {self.out_dir}/loss.png -ocf {self.jsonfn} --net3d '
f'-vsd {self.train_dir} -vtd {self.train_dir} -p 0 0 1 1 '
f'-g 0.01 -gn 0 -std 1 -tx -ty').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_data_aug_2d_cli(self):
train_args = f'-s {self.train_dir}/1/ -t {self.train_dir}/2/'.split()
args = train_args + (f'-o {self.out_dir}/nconv_nopatch.mdl -na nconv -ne 1 -nl 2 -ps 0 -bs 2 '
f'--plot-loss {self.out_dir}/loss.png -ocf {self.jsonfn} --tiff '
f'-p 1 1 1 1 -r 10 -ts 0.5 -sc 0.1 '
f'-hf -vf -g 0.1 -gn 0.2 -std 1 -tx -ty').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_png_cli(self):
train_args = f'-s {self.train_dir}/png/ -t {self.train_dir}/png/'.split(
)
args = train_args + (
f'-o {self.out_dir}/nconv.mdl -na nconv -ne 1 -nl 1 -cbp 1 -ps 0 -bs 2 -e png '
f'-ocf {self.jsonfn} -p 1 1 0 0 0 ').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, calc_var=True)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_attention_cli(self):
train_args = f'-s {self.train_dir}/tif/ -t {self.train_dir}/tif/'.split(
)
args = train_args + (
f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 2 -cbp 3 -ps 0 -bs 2 -e tif -ps 8 '
f'-ocf {self.jsonfn} -at').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_nconv_2d_crop_cli(self):
train_args = f'-s {self.train_dir}/tif/ -t {self.train_dir}/tif/'.split(
)
args = train_args + (
f'-o {self.out_dir}/nconv.mdl -na nconv -ne 1 -nl 1 -cbp 1 -ps 0 -bs 2 -e tif -ps 8 '
f'-ocf {self.jsonfn}').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_ord_2d_temperature_map_calc_var_cli(self):
train_args = f'-s {self.train_dir}/tif/ -t {self.train_dir}/tif/'.split(
)
args = train_args + (
f'-o {self.out_dir}/unet.mdl -na unet -ne 2 -nl 3 -cbp 1 -bs 4 -e tif '
f'-ocf {self.jsonfn} -ord 1 10 4 -vs 0.5 -ns -dp 0.5').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn,
temperature_map=True,
calc_var=True,
mc=2)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_unet_ord_2d_cli(self):
import warnings
with warnings.catch_warnings():
warnings.simplefilter("error")
train_args = f'-s {self.train_dir}/tif/ -t {self.train_dir}/tif/'.split(
)
valid = f'-vsd {self.train_dir}/tif/ -vtd {self.train_dir}/tif/'
args = train_args + (
f'-o {self.out_dir}/unet.mdl -na unet -ne 2 -nl 3 -cbp 1 -bs 4 -e tif '
f'-ocf {self.jsonfn} -ord 1 10 10 {valid} -dp 0.5').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
self.__modify_ocf(self.jsonfn, mc=2)
retval = nn_predict([self.jsonfn])
self.assertEqual(retval, 0)
def test_vae_2d_3l_cli(self):
train_args = f'-s {self.train_dir}/1/ -t {self.train_dir}/2/'.split()
args = train_args + (f'-o {self.out_dir}/vae.mdl -na vae -ne 1 -nl 3 -cbp 2 -bs 4 --tiff '
f'--img-dim 256 256 --latent-size 10 -ocf {self.jsonfn} -sa 0').split()
retval = nn_train(args)
self.assertEqual(retval, 0)
