[XPU]. Modified based on comment.

PaddlePaddle · Jul 29, 2022 · 233ffec · 233ffec
1 parent 5fc47d6
commit 233ffec
Show file tree

Hide file tree

Showing 2 changed files with 8 additions and 10 deletions.
diff --git a/lite/kernels/xpu/generate_proposals_v2_compute.cc b/lite/kernels/xpu/generate_proposals_v2_compute.cc
@@ -62,9 +62,9 @@ void GenerateProposalsV2Compute::Run() {
   float min_size = param.min_size;
   float eta = param.eta;
   bool pixel_offset = param.pixel_offset;
-  if (std::fabs(eta - 1.0f) > 1e-7) {
-    LOG(FATAL) << "XPU Generate Proposals Don't Support Adaptive NMS.";
-  }
+
+  // XPU Generate Proposals Don't Support Adaptive NMS.
+  CHECK_LT(std::fabs(eta - 1.0f), 1e-7);
 
   auto& scores_dim = scores->dims();
   int num = static_cast<int>(scores_dim[0]);

diff --git a/lite/tests/kernels/generate_proposals_v2_compute_test.cc b/lite/tests/kernels/generate_proposals_v2_compute_test.cc
@@ -156,18 +156,17 @@ class GenerateProposalsV2ComputeTester : public arena::TestCase {
   template <typename T, typename IndexT = int>
   void CPUGather(const Tensor& src, const Tensor& index, Tensor* output) {
     if (index.dims().size() == 2) {
+      // index.dims()[1] should be 1 when index.dims().size() = 2
+      CHECK_NE(index.dims()[1], 1);
       if (index.dims()[1] != 1) {
-        LOG(FATAL) << "index.dims()[1] should be 1 when index.dims().size() = 2"
+        LOG(FATAL) << "i"
                       "in gather_op, but received value is "
                    << index.dims()[1];
       }
 
     } else {
-      if (index.dims().size() != 1) {
-        LOG(FATAL) << "index.dims().size() should be 1 or 2 in gather_op,"
-                      "but received shape's size is "
-                   << index.dims().size();
-      }
+      // index.dims().size() should be 1 or 2 in gather_op
+      CHECK_NE(index.dims().size(), 1);
     }
     int64_t index_size = index.dims()[0];
 
@@ -702,7 +701,6 @@ class GenerateProposalsV2ComputeTester : public arena::TestCase {
     SetCommonTensor(Anchors_, anchors.dims(), anchors.data<float>());
 
     // Variances
-
     SetCommonTensor(Variances_, variances.dims(), variances.data<float>());
 
     // Scores