polish the code

test=develop

paddle/fluid/operators/affine_channel_op.cc

@@ -80,14 +80,11 @@ class AffineChannelOp : public framework::OperatorWithKernel {
 
     PADDLE_ENFORCE_EQ(scale_dims.size(), 1UL);
     PADDLE_ENFORCE_EQ(b_dims.size(), 1UL);
-    if (ctx->IsRuntime()) {
+    if (ctx->IsRuntime() || scale_dims[0] > 0) {
       PADDLE_ENFORCE_EQ(scale_dims[0], C);
-      PADDLE_ENFORCE_EQ(b_dims[0], C);
-    } else {
-      if (scale_dims[0] > 0 && b_dims[0] > 0) {
-        PADDLE_ENFORCE_EQ(scale_dims[0], C);
-        PADDLE_ENFORCE_EQ(b_dims[0], C);
     }
+    if (ctx->IsRuntime() || b_dims[0] > 0) {
+      PADDLE_ENFORCE_EQ(b_dims[0], C);
     }
 
     ctx->SetOutputDim("Out", ctx->GetInputDim("X"));

paddle/fluid/operators/conv_op.cc

@@ -69,7 +69,7 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
   std::vector<int64_t> output_shape({in_dims[0], filter_dims[0]});
   for (size_t i = 0; i < strides.size(); ++i) {
     if ((!ctx->IsRuntime()) &&
-        (in_dims[i + 2] == -1 || filter_dims[i + 2] == -1)) {
+        (in_dims[i + 2] <= 0 || filter_dims[i + 2] <= 0)) {
       output_shape.push_back(-1);
     } else {
       output_shape.push_back(ConvOutputSize(in_dims[i + 2], filter_dims[i + 2],

paddle/fluid/operators/roi_pool_op.cc

@@ -50,14 +50,12 @@ class ROIPoolOp : public framework::OperatorWithKernel {
     int pooled_width = ctx->Attrs().Get<int>("pooled_width");
     float spatial_scale = ctx->Attrs().Get<float>("spatial_scale");
 
-    if (ctx->IsRuntime()) {
     PADDLE_ENFORCE_GT(pooled_height, 0,
                       "The pooled output height must greater than 0");
     PADDLE_ENFORCE_GT(pooled_width, 0,
                       "The pooled output width must greater than 0");
     PADDLE_ENFORCE_GT(spatial_scale, 0.0f,
                       "The spatial scale must greater than 0");
-    }
 
     auto out_dims = input_dims;
     out_dims[0] = rois_dims[0];

paddle/fluid/operators/row_conv_op.cc

@@ -45,16 +45,10 @@ class RowConvOp : public framework::OperatorWithKernel {
     auto filter_dims = ctx->GetInputDim("Filter");
     PADDLE_ENFORCE_EQ(x_dims.size(), 2, "Input(X)'s rank should be 2.");
     PADDLE_ENFORCE_EQ(filter_dims.size(), 2, "Input(Y)'s rank should be 2.");
-    if (ctx->IsRuntime()) {
+    if (ctx->IsRuntime() || (x_dims[1] > 0 && filter_dims[1] > 0)) {
       PADDLE_ENFORCE_EQ(
           x_dims[1], filter_dims[1],
           "The 2nd dimension of Input(X) and Input(Filter) should be same.");
-    } else {
-      if (x_dims[1] > 0 && filter_dims[1] > 0) {
-        PADDLE_ENFORCE_EQ(
-            x_dims[1], filter_dims[1],
-            "The 2nd dimension of Input(X) and Input(Filter) should be same.");
-      }
     }
 
     ctx->SetOutputDim("Out", x_dims);

paddle/fluid/operators/unpool_op.cc

@@ -102,7 +102,7 @@ class UnpoolOp : public framework::OperatorWithKernel {
 
     std::vector<int64_t> output_shape({in_x_dims[0], in_x_dims[1]});
     for (size_t i = 0; i < ksize.size(); ++i) {
-      if (!ctx->IsRuntime() && in_x_dims[i + 2] == -1) {
+      if (!ctx->IsRuntime() && in_x_dims[i + 2] <= 0) {
         output_shape.push_back(-1);
       } else {
         output_shape.push_back(UnpoolOutputSize(in_x_dims[i + 2], ksize[i],