graph magic

2 files changed, 14 insertions, 12 deletions

diff --git a/cli/app/search/live.py b/cli/app/search/live.py
index b52ec03..63799a1 100644
--- a/cli/app/search/live.py
+++ b/cli/app/search/live.py
@@ -220,6 +220,7 @@ class Interpolator:
     gen_layer_name = 'module_apply_' + gen_signature + '/' + params.inv_layer
     encoding_latent = tf.get_default_graph().get_tensor_by_name(gen_layer_name)
 
+    print(encoding_latent.get_shape())
     encoding_shape = [1,] + encoding_latent.get_shape().as_list()[1:]
     print(encoding_shape)
     encoding_shape_placeholder = tf.constant(np.zeros(encoding_shape, dtype=np.float32))
@@ -272,20 +273,21 @@ class Interpolator:
   def set_encoding(self, opt):
     next_id = opt['id']
     data = load_pickle(os.path.join(app_cfg.DIR_VECTORS, "file_{}.pkl".format(next_id)))
+    encoding = np.expand_dims(data['encoding'], axis=0)
     encoding_stored = self.lerp_params['encoding_stored']
     encoding_mix = self.lerp_params['encoding_mix']
     # if we're showing an encoding already, lerp to the next one
     if encoding_mix.n.value > 0:
-      encoding_stored.switch(target_value=data['encoding'])
+      encoding_stored.switch(target_value=encoding)
     # otherwise (we're showing the latent)...
     else:
       # jump to the stored encoding, then switch
       if encoding_stored.n.value < 0.5:
         encoding_stored.n.value = 0
-        encoding_stored.a.assign(data['encoding'])
+        encoding_stored.a.assign(encoding)
       else:
         encoding_stored.n.value = 1
-        encoding_stored.b.assign(data['encoding'])
+        encoding_stored.b.assign(encoding)
       encoding_mix.switch()
 
   def on_step(self, i, dt, sess):
diff --git a/cli/app/utils/cortex_utils.py b/cli/app/utils/cortex_utils.py
index 8f00dfa..bf49f96 100644
--- a/cli/app/utils/cortex_utils.py
+++ b/cli/app/utils/cortex_utils.py
@@ -68,27 +68,27 @@ def fetch_file(url, fn, **kwargs):
         f.write(chunk)
   return size
 
-def upload_fp_to_cortex(opt_folder_id, fp):
+def upload_fp_to_cortex(opt_folder_id, fp, generated='true', module='biggan', activity='invert', datatype='image'):
   """Upload an open file/BytesIO object"""
   files = {
     'file': fp
   }
   data = {
     'folder_id': opt_folder_id,
-    'generated': 'true',
-    'module': 'biggan',
-    'activity': 'invert',
-    'datatype': 'image',
+    'generated': generated,
+    'module': module,
+    'activity': activity,
+    'datatype': datatype,
   }
   url = os.path.join(api_url('folder'), str(opt_folder_id), 'upload/')
   r = requests.post(url, files=files, data=data)
   return None if r.status_code != 200 else r.json()
 
-def upload_bytes_to_cortex(opt_folder_id, fn, fp, mimetype):
+def upload_bytes_to_cortex(opt_folder_id, fn, fp, mimetype, **kwargs):
   """Upload a BytesIO object"""
-  return upload_fp_to_cortex(opt_folder_id, (fn, fp.getvalue(), mimetype,))
+  return upload_fp_to_cortex(opt_folder_id, (fn, fp.getvalue(), mimetype,), **kwargs)
 
-def upload_file_to_cortex(opt_folder_id, fn):
+def upload_file_to_cortex(opt_folder_id, fn, **kwargs):
   """Upload a file from disk"""
   with open(fn, 'rb') as fp:
-    return upload_fp_to_cortex(opt_folder_id, fp)
+    return upload_fp_to_cortex(opt_folder_id, fp, **kwargs)