modify aa

x2paddle/op_mapper/caffe_custom_layer/register.py

@@ -31,7 +31,6 @@ def register(kind, shape, layer, weights):
             k) is str, 'invalid param "kind" for register, not a list of str'
         assert k not in g_custom_layers, 'this type[%s] has already been registered' % (
             k)
-        print('register layer[%s]' % (k))
         g_custom_layers[k] = {
             'shape': shape,
             'layer': layer,

x2paddle/op_mapper/caffe_op_mapper.py

@@ -124,9 +124,6 @@ class CaffeOpMapper(OpMapper):
 
             data[idx] = np.squeeze(d, axis=sq_axis)
             shape_new = data[idx].shape
-            if len(shape_old) != shape_new:
-                print('squeeze idx:%d, with kind:%s,name:%s' % \
-                        (idx, node.layer_type, node.layer.name))
         return data
 
     def get_kernel_parameters(self, kind, params):
@@ -956,7 +953,6 @@ class CaffeOpMapper(OpMapper):
             input = self.graph.get_bottom_node(node, idx=i, copy=True)
             if i == 1 and op == 'DetectionOutput':
                 input = self.graph.get_bottom_node(node, idx=i, copy=True)
-                print(input.layer_type)
                 while input is not None and input.layer_type != 'Softmax':
                     input = self.graph.get_bottom_node(input, idx=0, copy=True)
                 assert input is not None, 'This kind of DetectionOutput is not supported!'

x2paddle/op_mapper/onnx_custom_layer/register.py

@@ -44,7 +44,6 @@ def register(kind, shape, layer, child_func, weights):
             k) is str, 'invalid param "kind" for register, not a list of str'
         assert k not in g_custom_layers, 'this type[%s] has already been registered' % (
             k)
-        print('register layer[%s]' % (k))
         g_custom_layers[k] = {
             'shape': shape,
             'layer': layer,