I think so.  I would also like to know why the backward propagation for max pooling does not use the cuDNN API.

extern "C" void forward_local_avgpool_layer_gpu(maxpool_layer layer, network_state state)
{

#ifdef CUDNN_DISABLED
    if (!state.train && layer.stride == layer.size) {
        // cudnnPoolingBackward
        cudnnStatus_t maxpool_status;

        float alpha = 1, beta = 0;
        maxpool_status = cudnnPoolingForward(
            cudnn_handle(),
            layer.poolingDesc,
            &alpha,
            layer.srcTensorDesc,
            state.input,
            &beta,
            layer.dstTensorDesc,
            layer.output_gpu);

        //maxpool_status = cudnnDestroyPoolingDescriptor(poolingDesc);
        //cudnnDestroyTensorDescriptor(layer.srcTensorDesc);
        //cudnnDestroyTensorDescriptor(layer.dstTensorDesc);

    }
    else
#endif
    {
        int h = layer.out_h;
        int w = layer.out_w;
        int c = layer.out_c;

        size_t n = h*w*c*layer.batch;

        forward_local_avgpool_layer_kernel <<<cuda_gridsize(n), BLOCK, 0, get_cuda_stream() >>> (n, layer.h, layer.w, layer.c, layer.stride_x, layer.stride_y, layer.size, layer.pad, state.input, layer.output_gpu);
        CHECK_CUDA(cudaPeekAtLastError());
    }
}