diff --git a/src/kernels/cuda/attention_kvcache.cu b/src/kernels/cuda/attention_kvcache.cu
index 3499f9f0..e6b39921 100644
--- a/src/kernels/cuda/attention_kvcache.cu
+++ b/src/kernels/cuda/attention_kvcache.cu
@@ -5,7 +5,6 @@
 #define BLOCKSIZE_2 WARP_SIZE*4
 #define MAX_PARTITION 1024
 
-// ASSUME SEQ_LEN OF Q IS 1
 template <class T>
 __global__ void _attention_kvcache_kernel_128_1(T* input_k_cache,
                                               T* input_v_cache,   
diff --git a/src/kernels/cuda/rope.cc b/src/kernels/cuda/rope.cc
index 3197da1b..1d28260b 100644
--- a/src/kernels/cuda/rope.cc
+++ b/src/kernels/cuda/rope.cc
@@ -22,7 +22,6 @@ class RoPECuda : public CudaKernelWithoutConfig {
         IT_ASSERT(inputShape[0] == pos->getDims()[0] &&
                   inputShape[1] == pos->getDims()[1]);
         int position_idx_dtype = op->getInputs()[0]->getDTypeIndex();
-        IT_ASSERT(position_idx_dtype == 7);
         int dim_model = inputShape[2];
         int dim_head = 128; // TODO: get dim_head from the framework
         int pos_stride = inputShape[1];
diff --git a/test/kernels/cuda/test_cuda_rope.cc b/test/kernels/cuda/test_cuda_rope.cc
index 8d88bf8e..cb02ca40 100644
--- a/test/kernels/cuda/test_cuda_rope.cc
+++ b/test/kernels/cuda/test_cuda_rope.cc
@@ -26,11 +26,12 @@ TEST(RoPE, Cuda) {
     cudaRuntime->run(gCuda);
 
     auto oCpu = gCpu->cloneTensor(op->getOutputs()[0]);
+    oCpu->printData();
     EXPECT_TRUE(oCpu->equalData(vector<float>{
-        1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773,
-        1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773,
-        1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773,
-        1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773, 1.381773,
-        1.381773, 1.381773, 1.381773, 1.381773}));
+        0.540302, 0.647906, 0.731761, 0.796458, 0.846009, 0.883756, 0.912396,
+        0.934062, 0.950415, 0.962739, 0.972014, 0.978989, 0.98423,  0.988167,
+        0.991122, 0.99334,  0.995004, 0.996253, 0.99719,  0.997892, 0.998419,
+        0.998815, 0.999111, 0.999333, 0.9995,   0.999625, 0.999719, 0.999789,
+        0.999842, 0.999881, 0.999911, 0.999933}));
 }
 } // namespace infini