Insufficient GPU Memory? Is it correct?

[my-run]

return self.sess.run(output_names, input_feed, run_options) onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Non-zero status code returned while running Gemm node. Name:'Gemm_128' Status Message: /onnxruntime_src/onnxruntime/core/providers/cuda/cuda_call.cc:121 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, ERRTYPE, const char*, const char*, int) [with ERRTYPE = cudnnStatus_t; bool THRW = true; std::conditional_t<THRW, void, onnxruntime::common::Status> = void] /onnxruntime_src/onnxruntime/core/providers/cuda/cuda_call.cc:114 std::conditional_t<THRW, void, onnxruntime::common::Status> onnxruntime::CudaCall(ERRTYPE, const char*, const char*, ERRTYPE, const char*, const char*, int) [with ERRTYPE = cudnnStatus_t; bool THRW = true; std::conditional_t<THRW, void, onnxruntime::common::Status> = void] CUDNN failure 4: CUDNN_STATUS_INTERNAL_ERROR ; GPU=0 ; hostname=enzo-ThinkPad-P16v-Gen-1 ; file=/onnxruntime_src/onnxruntime/core/providers/cuda/cuda_execution_provider.cc ; line=172 ; expr=cudnnCreate(&cudnn_handle);