[WIP] simplify

.travis.yml

@@ -21,7 +21,7 @@ script:
   - python tests/test_mnist_simple.py
   - python tests/test_reuse_mlp.py
   - python tests/test_layers_basic.py
-  - python tests/test_layers_convolutional.py
+  - python tests/test_layers_convolution.py
   - python tests/test_layers_core.py
   - python tests/test_layers_extend.py
   - python tests/test_layers_flow_control.py

tensorlayer/layers/core.py

@@ -371,24 +371,11 @@ def __init__(self, layer=None, name='layer'):
             self.all_params = list(layer.all_params)
             self.all_drop = dict(layer.all_drop)
         elif isinstance(layer, list):  # 2. for layer have multiply inputs i.e. ConcatLayer
-            # add 1st layer
-            self.all_layers = list(layer[0].all_layers)
-            self.all_params = list(layer[0].all_params)
-            self.all_drop = dict(layer[0].all_drop)
-            # add other layers
-            for i in range(1, len(layer)):
-                self.all_layers.extend(list(layer[i].all_layers))
-                self.all_params.extend(list(layer[i].all_params))
-                self.all_drop.update(dict(layer[i].all_drop))
-            # remove repeated stuff
-            self.all_layers = list_remove_repeat(self.all_layers)
-            self.all_params = list_remove_repeat(self.all_params)
+            self.all_layers = list_remove_repeat(sum([l.all_layers for l in layer], []))
+            self.all_params = list_remove_repeat(sum([l.all_params for l in layer], []))
+            self.all_drop = dict(sum([list(l.all_drop.items()) for l in layer], []))
         elif isinstance(layer, tf.Tensor):
             raise Exception("Please use InputLayer to convert Tensor/Placeholder to TL layer")
-            self.all_layers = []
-            self.all_params = []
-            self.all_drop = {}
-
         elif layer is not None:
             raise Exception("Unsupport layer type %s" % type(layer))
 

tests/requirements.txt

@@ -1,2 +1,3 @@
 yapf==0.20.2
 pydocstyle==2.1.1
+keras==2.1.5