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 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 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 16 ' f'-ocf {self.jsonfn} -bs 2 -v -csv {self.out_dir}/test.csv' ).split() retval = nn_train(args) self.assertEqual(retval, 0)
def test_nconv_amsgrad_cli(self): args = self.train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 3 -nl 1 -ps 16 16 ' f'-ocf {self.jsonfn} -bs 2 -v -opt amsgrad').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_ks331_ns_cli(self): args = self.train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 2 -cbp 1 -ps 16 16 16 -bs 2 -dm 3 ' f'-ocf {self.jsonfn} -ks 3 3 1 -ns -ic').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_cwattention_semi3d_cli(self): args = self.train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 2 -cbp 4 -bs 4 -ps 8 8 8 -dm 3 ' f'-ocf {self.jsonfn} -at channel -ks 3 3 1 -ic -s3 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_3d_var_cli(self): args = self.train_args + (f'-o {self.out_dir}/nconv.mdl -na nconv -ne 1 -nl 1 -cbp 1 -bs 1 -dm 3 ' 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_whole_img_cli(self): args = self.train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 1 -nl 1 -dm 3 ' 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_unet_resblock_3d_cli(self): args = self.train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -ps 16 16 16 -bs 2 -dm 3 ' f'-ocf {self.jsonfn} -acv -rb').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_3d_cli(self): args = self.train_args + (f'-o {self.out_dir}/vae.mdl -na vae -ne 1 -nl 3 -cbp 1 -ps 16 16 16 -bs 4 -dm 3 ' 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_nconv_restarts_cli(self): args = self.train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 3 -nl 1 -ps 16 16 ' f'-ocf {self.jsonfn} -bs 2 -lrs cosinerestarts -tm 2 -rp 2 -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_unet_bce_cli(self): train_args = f'-s {self.train_dir} -t {self.train_dir}/mask/'.split() args = train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 1 -cbp 1 -ps 16 16 16 -bs 2 -dm 3 ' f'-ocf {self.jsonfn} -l bce').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_unburn_3d_cli(self): args = self.train_args + ( f'-o {self.out_dir}/unburnnet.mdl -na unburnnet -ne 1 -nl 1 -cbp 1 -ps 32 32 32 -bs 4 -dm 3 ' f'-ocf {self.jsonfn} -ls 5 -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_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 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_nconv_nopatch_cli(self): args = self.train_args + (f'-o {self.out_dir}/nconv_nopatch.mdl -na nconv -ne 1 -nl 2 -bs 2 -dm 3 ' f'--plot-loss {self.out_dir}/loss.png -ocf {self.jsonfn} ' f'-vsd {self.train_dir} -vtd {self.train_dir} -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_tif_predict_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 -bs 2 -e tif ' f'-ocf {self.jsonfn}').split() retval = nn_train(args) self.assertEqual(retval, 0) self._modify_ocf(self.jsonfn, calc_var=True, tif_out=True) retval = nn_predict([self.jsonfn]) self.assertEqual(retval, 0)
def test_nconv_color_tb_cli(self): train_args = f'-s {self.train_dir}/color/ -t {self.train_dir}/color/'.split() args = train_args + (f'-o {self.out_dir}/nconv.mdl -na nconv -ne 1 -nl 1 -cbp 1 -bs 2 -e png -co -dm 2 ' f'-ocf {self.jsonfn} -tb').split() retval = nn_train(args) self.assertEqual(retval, 0) self._modify_ocf(self.jsonfn, color_out=True, bs=1) 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 -bs 2 -e tif -ps 8 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_cwattention_2d_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 4 -bs 4 -e tif -ps 8 8 ' f'-ocf {self.jsonfn} -at channel').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_densenet_cli(self): train_args = f'-s {self.train_dir}/tif/ -t {self.train_dir}/tif/'.split() args = train_args + (f'-o {self.out_dir}/densenet.mdl -na densenet -ne 1 -bs 2 -e tif ' 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_multimodal_tiff_cli(self): train_args = f'-s {self.train_dir}/tif/ {self.train_dir}/tif/ -t {self.train_dir}/tif/ {self.train_dir}/tif/'.split() args = train_args + (f'-o {self.out_dir}/nconv_patch.mdl -na nconv -ne 1 -nl 1 -ps 16 16 ' f'-ocf {self.jsonfn} -bs 2 -e tif -th 0').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_lrsd_cli(self): args = self.train_args + ( f'-o {self.out_dir}/lrsdnet.mdl -na lrsdnet -ne 1 -nl 2 -cbp 2 -ps 32 32 32 -bs 4 -dm 3 ' 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_ord_3d_cli(self): args = self.train_args + ( f'-o {self.out_dir}/ordnet.mdl -na ordnet -ne 2 -nl 3 -cbp 1 -bs 4 -ps 16 16 16 -dm 3 ' 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_resblock_2d_no_skip_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 3 -cbp 1 -bs 2 -e tif -ps 16 16 ' f'-ocf {self.jsonfn} -acv -rb -ns').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_color_2d_cli(self): train_args = f'-s {self.train_dir}/color/ -t {self.train_dir}/color/'.split() args = train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -bs 2 -e png -dm 2 ' f'-ocf {self.jsonfn} -co').split() retval = nn_train(args) self.assertEqual(retval, 0) self._modify_ocf(self.jsonfn, color_out=True, bs=1) retval = nn_predict([self.jsonfn]) self.assertEqual(retval, 0)
def test_unet_multimodal_cli(self): train_args = f'-s {self.train_dir}/tif/ {self.train_dir}/tif/ -t {self.train_dir}/tif/ {self.train_dir}/tif/'.split() args = train_args + (f'-o {self.out_dir}/unet.mdl -na unet -ne 1 -nl 3 -cbp 1 -ps 16 16 -bs 2 -e tif ' 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_unet_softmax_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 -bs 2 -e tif -ps 8 8 ' f'-ocf {self.jsonfn} -sx').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_3d_cli(self): args = self.train_args + (f'-o {self.out_dir}/nconv_nopatch.mdl -na nconv -ne 1 -nl 2 -bs 2 ' f'--plot-loss {self.out_dir}/loss.png -ocf {self.jsonfn} -dm 3 ' f'-vsd {self.train_dir} -vtd {self.train_dir} -p 0 0 1 1 1 ' f'-g 0.01 -gn 0 -pwr 1 -tx -ty -blk 5 10 -mean 1 -std 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_burn2_3d_cli(self): train_args = f'-s {self.train_dir} {self.train_dir} -t {self.train_dir} {self.train_dir}'.split( ) args = train_args + ( f'-o {self.out_dir}/burn2net.mdl -na burn2net -ne 1 -nl 1 -cbp 1 -ps 32 32 32 -bs 4 -dm 3 ' f'-ocf {self.jsonfn} -ls 5').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_burn2p21_2d_cli(self): train_args = f'-s {self.train_dir}/tif/ {self.train_dir}/tif/ -t {self.train_dir}/tif/ {self.train_dir}/tif/'.split( ) args = train_args + ( f'-o {self.out_dir}/burn2net.mdl -na burn2net -ne 1 -nl 1 -cbp 1 -ps 32 32 -bs 4 -e tif ' f'-ocf {self.jsonfn} -ls 5').split() retval = nn_train(args) self.assertEqual(retval, 0) self._modify_ocf(self.jsonfn, model='burn2netp21') retval = nn_predict([self.jsonfn]) self.assertEqual(retval, 0)
def test_nconv_data_aug_2d_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_nopatch.mdl -na nconv -ne 1 -nl 2 -bs 2 ' f'--plot-loss {self.out_dir}/loss.png -ocf {self.jsonfn} -e tif ' f'-p 1 1 1 1 1 -r 10 -ts 0.5 -sc 0.1 -mean 1 -std 1 ' f'-hf -vf -g 0.1 -gn 0.2 -pwr 1 -tx -ty -blk 5 6 -th 0').split() retval = nn_train(args) self.assertEqual(retval, 0) self._modify_ocf(self.jsonfn) retval = nn_predict([self.jsonfn]) self.assertEqual(retval, 0)