fixed feature sizes, cvae working

auto_encoder_static.py

@@ -54,7 +54,7 @@ uv2mesh = UV2Mesh(res=256, is_skirt=config['is_skirt'], is_smpl_orig=config['is_
 
 
 
-@tf.function
+# @tf.function
 def train_step(batch):
     with tf.GradientTape() as tape:
         pred = model([batch['uv_static'], batch['uv_mask']], training=True)
@@ -187,7 +187,7 @@ def test():
 
 
 if __name__ == '__main__':
-    init_wandb()
+    # init_wandb()
     # allow_memory_growth()
     parser = argparse.ArgumentParser(description='')
     parser.add_argument('--name', type=str)