Update

python/paddle/v2/framework/framework.py

@@ -15,7 +15,7 @@ class Variable(object):
                  shape=None,
                  dtype=None,
                  lod_level=None,
-                 persistable=False,
+                 persistable=None,
                  **kwargs):
         self.block = block
 

python/paddle/v2/framework/layer_helper.py

@@ -121,10 +121,13 @@ class LayerHelper(object):
 
     def create_tmp_variable(self, dtype):
         return self.program.current_block().create_var(
-            name=unique_name(".".join([self.name, 'tmp'])), dtype=dtype)
+            name=unique_name(".".join([self.name, 'tmp'])),
+            dtype=dtype,
+            persistable=False)
 
     def create_global_variable(self, *args, **kwargs):
-        return self.program.global_block().create_var(*args, **kwargs)
+        return self.program.global_block().create_var(
+            *args, persistable=False, **kwargs)
 
     def append_bias_op(self, input_var):
         size = list(input_var.shape[1:])

python/paddle/v2/framework/tests/test_fit_a_line.py

@@ -20,9 +20,12 @@ avg_cost = layers.mean(x=cost, program=program)
 sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.01)
 opts = sgd_optimizer.minimize(avg_cost)
 
-# print str(program)
+print str(program)
 
-BATCH_SIZE = 2
+import pdb
+pdb.set_trace()
+
+BATCH_SIZE = 100
 
 train_reader = paddle.batch(
     paddle.reader.shuffle(
@@ -32,12 +35,12 @@ train_reader = paddle.batch(
 place = core.CPUPlace()
 exe = Executor(place)
 
-PASS_NUM = 1
+PASS_NUM = 200
 for pass_id in range(PASS_NUM):
     for data in train_reader():
         x_data = np.array(map(lambda x: x[0], data)).astype("float32")
         y_data = np.array(map(lambda x: x[1], data)).astype("float32")
-        y_data = np.expand_dims(y_data, axis=1)
+        #y_data = np.expand_dims(y_data, axis=1)
 
         tensor_x = core.LoDTensor()
         tensor_x.set(x_data, place)