reprocess

3 files changed, 9 insertions, 9 deletions

diff --git a/cli/app/commands/biggan/extract_dense_vectors.py b/cli/app/commands/biggan/extract_dense_vectors.py
index 7fef459..45a13db 100644
--- a/cli/app/commands/biggan/extract_dense_vectors.py
+++ b/cli/app/commands/biggan/extract_dense_vectors.py
@@ -17,9 +17,9 @@ from app.search.json import params_dense_dict
   help='Export a video for each dataset')
 @click.option('-rp', '--reprocess', 'opt_reprocess', is_flag=True,
   help='Reprocess images')
-@click.option('-sc', '--stochastic_clipping', 'opt_stochastic_clipping', default=0,
+@click.option('-sc', '--stochastic_clipping', 'opt_stochastic_clipping', is_flag=True,
   help='Compute feature loss')
-@click.option('-lc', '--label_clipping', 'opt_label_clipping', default=0,
+@click.option('-lc', '--label_clipping', 'opt_label_clipping', is_flag=True,
   help='Normalize labels every N steps')
 @click.option('-feat', '--use_feature_detector', 'opt_use_feature_detector', is_flag=True,
   help='Compute feature loss')
diff --git a/cli/app/commands/biggan/search_class.py b/cli/app/commands/biggan/search_class.py
index 050fbef..7a7bfdb 100644
--- a/cli/app/commands/biggan/search_class.py
+++ b/cli/app/commands/biggan/search_class.py
@@ -19,10 +19,10 @@ from app.utils.cortex_utils import cortex_folder, download_cortex_files, find_un
   help='Export a video for each dataset')
 @click.option('-t', '--tag', 'opt_tag', default='inverse_' + str(int(time.time() * 1000)), 
   help='Tag this dataset')
-@click.option('-sc', '--stochastic_clipping', 'opt_stochastic_clipping', default=0,
-  help='Compute feature loss. Specify interval to do the clipping')
-@click.option('-lc', '--label_clipping', 'opt_label_clipping', default=0,
-  help='Normalize labels every N steps. Specify interval to do the normalization')
+@click.option('-sc', '--stochastic_clipping', 'opt_stochastic_clipping', is_flag=True,
+  help='Compute feature loss')
+@click.option('-lc', '--label_clipping', 'opt_label_clipping', is_flag=True,
+  help='Normalize labels every N steps')
 @click.option('-feat', '--use_feature_detector', 'opt_use_feature_detector', is_flag=True,
   help='Compute feature loss')
 @click.option('-ll', '--feature_layers', 'opt_feature_layers', default="1a,2a,4a,7a",
diff --git a/cli/app/search/search_class.py b/cli/app/search/search_class.py
index 7961a0c..c732801 100644
--- a/cli/app/search/search_class.py
+++ b/cli/app/search/search_class.py
@@ -45,7 +45,7 @@ feature_layer_names = {
 }
 
 def find_nearest_vector_for_images(paths, opt_dims, opt_steps, opt_video, opt_tag,
-  opt_limit=-1, opt_stochastic_clipping=0, opt_label_clipping=0,
+  opt_limit=-1, opt_stochastic_clipping=True, opt_label_clipping=True,
   opt_use_feature_detector=False, opt_feature_layers=[1,2,4,7], opt_snapshot_interval=20, opt_clip_interval=500):
   tf.reset_default_graph()
   sess = tf.compat.v1.Session()
@@ -186,9 +186,9 @@ def find_nearest_vector(sess, generator, opt_fp_in, opt_dims, out_images, out_la
       if i % 20 == 0:
         print('iter: {}, loss: {}'.format(i, curr_loss))
       if i > 0:
-        if opt_stochastic_clipping != 0 and (i % opt_stochastic_clipping) == 0:
+        if opt_stochastic_clipping and (i % opt_clip_interval) == 0:
           sess.run(clip_latent)
-        if opt_label_clipping != 0 and (i % opt_label_clipping) == 0:
+        if opt_label_clipping and (i % opt_clip_interval) == 0:
           sess.run(clip_labels)
       if opt_video and opt_snapshot_interval != 0 and (i % opt_snapshot_interval) == 0:
         phi_guess = sess.run(output)