diff --git a/paddle/operators/batch_norm_op.cc b/paddle/operators/batch_norm_op.cc
index 98db28ddee7c6cdb37fe7732649d4fc38de7b873..dd7b038b00813b192177c05dc06aa165a60b5156 100644
--- a/paddle/operators/batch_norm_op.cc
+++ b/paddle/operators/batch_norm_op.cc
@@ -64,7 +64,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE(x_dims.size() >= 2 && x_dims.size() <= 5,
                    "Input X must have 2 to 5 dimensions.");
 
-    const int C =
+    const int64_t C =
         (data_layout == DataLayout::kNCHW ? x_dims[1]
                                           : x_dims[x_dims.size() - 1]);
 
@@ -78,6 +78,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
     ctx->SetOutputDim("VarianceOut", {C});
     ctx->SetOutputDim("SavedMean", {C});
     ctx->SetOutputDim("SavedVariance", {C});
+    ctx->ShareLoD("X", "Y");
   }
 };
 
diff --git a/paddle/operators/conv_op.cc b/paddle/operators/conv_op.cc
index e65a5dce52c3c51d3d6bee1684c1e97230203d38..ad84524e1785e3b6b4586c83001852b6dba7afe8 100644
--- a/paddle/operators/conv_op.cc
+++ b/paddle/operators/conv_op.cc
@@ -44,14 +44,12 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
       paddings.size(), strides.size(),
       "Conv paddings dimension and Conv strides dimension should be the same.");
 
-  int input_channels = in_dims[1];
-  PADDLE_ENFORCE_EQ(input_channels, filter_dims[1] * groups,
+  PADDLE_ENFORCE_EQ(in_dims[1], filter_dims[1] * groups,
                     "The number of input channels should be equal to filter "
                     "channels * groups.");
 
-  int output_channels = filter_dims[0];
   PADDLE_ENFORCE_EQ(
-      output_channels % groups, 0,
+      filter_dims[0] % groups, 0,
       "The number of output channels should be divided by groups.");
 
   std::vector<int64_t> output_shape({in_dims[0], filter_dims[0]});
@@ -66,6 +64,7 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
                                       dilations[i], paddings[i], strides[i]));
   }
   ctx->SetOutputDim("Output", framework::make_ddim(output_shape));
+  ctx->ShareLoD("Input", "Output");
 }
 
 Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
diff --git a/paddle/operators/pool_op.cc b/paddle/operators/pool_op.cc
index 50057eb6483e9c9e745bc07dee26a0bbbbb5a48c..d3cf5fa638c53dfdfacec153211f447a1e2fa3bf 100644
--- a/paddle/operators/pool_op.cc
+++ b/paddle/operators/pool_op.cc
@@ -58,6 +58,7 @@ void PoolOp::InferShape(framework::InferShapeContext *ctx) const {
         OutputSizePool(in_x_dims[i + 2], ksize[i], paddings[i], strides[i]));
   }
   ctx->SetOutputDim("Out", framework::make_ddim(output_shape));
+  ctx->ShareLoD("X", "Out");
 }
 
 void PoolOpGrad::InferShape(framework::InferShapeContext *ctx) const {