Added encoding size as a CL parameter in train_model.py

deepof/models.py

@@ -586,7 +586,7 @@ class SEQ_2_SEQ_GMVAE:
                     tfd.Independent(
                         tfd.Normal(
                             loc=gauss[1][..., : self.ENCODING, k],
-                            scale=softplus(gauss[1][..., self.ENCODING:, k]),
+                            scale=softplus(gauss[1][..., self.ENCODING :, k]),
                         ),
                         reinterpreted_batch_ndims=1,
                     )

deepof/train_model.py

@@ -413,7 +413,9 @@ if not tune:
                 callbacks=callbacks_,
             )
 
-            gmvaep.save_weights("{}_final_weights.h5".format(run_ID))
+            gmvaep.save_weights(
+                "GMVAE_loss={}_encoding={}_final_weights.h5".format(loss, encoding_size)
+            )
 
         # To avoid stability issues
         tf.keras.backend.clear_session()

deepof/train_utils.py

@@ -239,4 +239,4 @@ def tune_search(
 
     print(tuner.results_summary())
 
-    return best_hparams, best_run
\ No newline at end of file
+    return best_hparams, best_run