fix persistable bug

paddle/operators/elementwise_op.h

@@ -34,6 +34,8 @@ class ElementwiseOp : public framework::OperatorWithKernel {
 
     auto x_dim = ctx->GetInputDim("X");
     auto y_dim = ctx->GetInputDim("Y");
+    LOG(INFO) << x_dim;
+    LOG(INFO) << y_dim;
     PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(),
                       "Rank of first input must >= rank of second input.")
     ctx->SetOutputDim("Out", x_dim);

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'])),
+            persistable=False,
+            dtype=dtype)
 
     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

@@ -37,13 +37,18 @@ 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)
+        # print x_data
+        # print type(x_data)
+        # print y_data
 
         tensor_x = core.LoDTensor()
         tensor_x.set(x_data, place)
+        # print tensor_x.get_dims()
 
         tensor_y = core.LoDTensor()
         tensor_y.set(y_data, place)
+        # print tensor_y.get_dims()
         outs = exe.run(program,
                        feed={'x': tensor_x,
                              'y': tensor_y},