Dropped support for tf.keras and eager execution

jernsting · May 27, 2020 · 1ca7976 · 1ca7976
1 parent 9748a4b
commit 1ca7976
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Showing 3 changed files with 6 additions and 11 deletions.
diff --git a/.travis.yml b/.travis.yml
@@ -5,8 +5,6 @@ python:
   - 3.6
 env:
   - KERAS_BACKEND=tensorflow
-  - KERAS_BACKEND=tensorflow TF_KERAS=1
-  - KERAS_BACKEND=tensorflow TF_KERAS=1 TF_EAGER=1
   - KERAS_BACKEND=tensorflow TF_KERAS=1 TF_2=1
   # - KERAS_BACKEND=theano THEANO_FLAGS=optimizer=fast_compile
   # - KERAS_BACKEND=cntk PYTHONWARNINGS=ignore

diff --git a/README.md b/README.md
@@ -3,8 +3,6 @@
 [![Build Status](https://travis-ci.com/jernsting/keras-drop-connect.svg?branch=master)](https://travis-ci.com/jernsting/keras-drop-connect)
 
 ![](https://img.shields.io/badge/keras-tensorflow-blue.svg)
-![](https://img.shields.io/badge/keras-tf.keras-blue.svg)
-![](https://img.shields.io/badge/keras-tf.keras/eager-blue.svg)
 ![](https://img.shields.io/badge/keras-tf.keras/2.0.0_beta-blue.svg)
 
 

diff --git a/keras_drop_connect/wrappers.py b/keras_drop_connect/wrappers.py
@@ -55,17 +55,16 @@ def _dropped_weight():
                     raise Exception("Unknown name: {}".format(name))
         else:
             pass
-            for name in names:
-                name = name.split("/")[1].split(":")[0]  # this is not nice, but it works for now with all Versions
+            for name in dir(self.layer):
                 try:
                     w = getattr(self.layer, name)
-                    origins[name] = w
-                    if 0. < self.rate < 1.:
-                        setattr(self.layer, name, K.in_train_phase(dropped_weight(w, self.rate), w,
-                                                                   training=training))
+                    if K.is_keras_tensor(w) and w.name in names:
+                        origins[name] = w
+                        if 0. < self.rate < 1.:
+                            setattr(self.layer, name, K.in_train_phase(dropped_weight(w, self.rate), w,
+                                                                       training=training))
                 except Exception as e:
                     continue
-
         outputs = self.layer.call(inputs, **kwargs)
         for name, w in origins.items():
             setattr(self.layer, name, w)