leras ModelBase.summary()

core/leras/layers.py

@@ -270,6 +270,81 @@ def initialize_layers(nn):
 
             return nn.tf_sess.run ( self.run_output, feed_dict=feed_dict)
 
+        def summary(self):
+            layers = self.get_layers()
+            layers_names = []
+            layers_params = []
+
+            max_len_str = 0
+            max_len_param_str = 0
+            delim_str = "-"
+
+            total_params = 0
+
+            #Get layers names and str lenght for delim
+            for l in layers:
+                if len(str(l))>max_len_str:
+                    max_len_str = len(str(l))
+                layers_names+=[str(l).capitalize()]
+
+            #Get params for each layer
+            layers_params = [ int(np.sum(np.prod(w.shape) for w in l.get_weights())) for l in layers ]
+            total_params = np.sum(layers_params)
+
+            #Get str lenght for delim
+            for p in layers_params:
+                if len(str(p))>max_len_param_str:
+                    max_len_param_str=len(str(p))
+
+            #Set delim
+            for i in range(max_len_str+max_len_param_str+3):
+                delim_str += "-"
+
+            output = "\n"+delim_str+"\n"
+
+            #Format model name str
+            model_name_str = "| "+self.name.capitalize()
+            len_model_name_str = len(model_name_str)
+            for i in range(len(delim_str)-len_model_name_str):
+                model_name_str+= " " if i!=(len(delim_str)-len_model_name_str-2) else " |"
+
+            output += model_name_str +"\n"
+            output += delim_str +"\n"
+
+
+            #Format layers table
+            for i in range(len(layers_names)):
+                output += delim_str +"\n"
+
+                l_name = layers_names[i]
+                l_param = str(layers_params[i])
+                l_param_str = ""
+                if len(l_name)<=max_len_str:
+                    for i in range(max_len_str - len(l_name)):
+                        l_name+= " "
+
+                if len(l_param)<=max_len_param_str:
+                    for i in range(max_len_param_str - len(l_param)):
+                        l_param_str+= " "
+
+                l_param_str += l_param
+
+
+                output +="| "+l_name+"|"+l_param_str+"| \n"
+
+            output += delim_str +"\n"
+
+            #Format sum of params
+            total_params_str = "| Total params count: "+str(total_params)
+            len_total_params_str = len(total_params_str)
+            for i in range(len(delim_str)-len_total_params_str):
+                total_params_str+= " " if i!=(len(delim_str)-len_total_params_str-2) else " |"
+
+            output += total_params_str +"\n"
+            output += delim_str +"\n"
+
+            io.log_info(output)
+
     nn.ModelBase = ModelBase
 
     class Conv2D(LayerBase):
@@ -284,7 +359,7 @@ def initialize_layers(nn):
             if not isinstance(dilations, int):
                 raise ValueError ("dilations must be an int type")
             kernel_size = int(kernel_size)
-            
+
             if dtype is None:
                 dtype = nn.tf_floatx
 
@@ -388,7 +463,7 @@ def initialize_layers(nn):
             if not isinstance(strides, int):
                 raise ValueError ("strides must be an int type")
             kernel_size = int(kernel_size)
-            
+
             if dtype is None:
                 dtype = nn.tf_floatx