Update files.py, speed up model saving and restoring process.

The run() and eval() will run the whole graph from scratch, so combining ops to an array and executing together will result in significant speed-up.

tensorlayer/files.py

@@ -646,14 +646,14 @@ def save_npz(save_list=[], name='model.npz', sess=None):
     """
     ## save params into a list
     save_list_var = []
-    for k, value in enumerate(save_list):
-        if sess:
-            save_list_var.append( sess.run(value) )
-        else:
-            try:
-                save_list_var.append( value.eval() )
-            except:
-                print(" Fail to save model, Hint: pass the session into this function, save_npz(network.all_params, name='model.npz', sess=sess)")
+    if sess:
+        save_list_var = sess.run(save_list)
+    else:
+        try:
+            for k, value in enumerate(save_list):
+                save_list_var.append(value.eval())
+        except:
+            print(" Fail to save model, Hint: pass the session into this function, save_npz(network.all_params, name='model.npz', sess=sess)")
     np.savez(name, params=save_list_var)
     save_list_var = None
     del save_list_var
@@ -734,9 +734,10 @@ def assign_params(sess, params, network):
     ----------
     - `Assign value to a TensorFlow variable <http://stackoverflow.com/questions/34220532/how-to-assign-value-to-a-tensorflow-variable>`_
     """
+    ops = []
     for idx, param in enumerate(params):
-        assign_op = network.all_params[idx].assign(param)
-        sess.run(assign_op)
+        ops.append(network.all_params[idx].assign(param))
+    sess.run(ops)