diff --git a/mamba_ssm/ops/selective_scan_interface.py b/mamba_ssm/ops/selective_scan_interface.py
index c3596bfe..503634b6 100644
--- a/mamba_ssm/ops/selective_scan_interface.py
+++ b/mamba_ssm/ops/selective_scan_interface.py
@@ -13,7 +13,10 @@
     causal_conv1d_fn = None
     causal_conv1d_cuda = None
 
-import selective_scan_cuda
+try:
+    import selective_scan_cuda
+except ImportError:
+    selective_scan_cuda = None
 
 
 class SelectiveScanFn(torch.autograd.Function):
@@ -85,7 +88,10 @@ def selective_scan_fn(u, delta, A, B, C, D=None, z=None, delta_bias=None, delta_
     last_state has shape (batch, dim, dstate). Note that the gradient of the last state is
     not considered in the backward pass.
     """
-    return SelectiveScanFn.apply(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
+    if selective_scan_cuda is None:
+        return selective_scan_ref(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
+    else:
+        return SelectiveScanFn.apply(u, delta, A, B, C, D, z, delta_bias, delta_softplus, return_last_state)
 
 
 def selective_scan_ref(u, delta, A, B, C, D=None, z=None, delta_bias=None, delta_softplus=False,
@@ -314,11 +320,17 @@ def mamba_inner_fn(
     A, B=None, C=None, D=None, delta_bias=None, B_proj_bias=None,
     C_proj_bias=None, delta_softplus=True
 ):
-    return MambaInnerFn.apply(xz, conv1d_weight, conv1d_bias, x_proj_weight, delta_proj_weight,
+    if causal_conv1d_cuda is None:
+        return mamba_inner_ref(xz, conv1d_weight, conv1d_bias, x_proj_weight, delta_proj_weight,
+                               out_proj_weight, out_proj_bias,
+                               A, B, C, D, delta_bias, B_proj_bias, C_proj_bias, delta_softplus)
+    else:
+        return MambaInnerFn.apply(xz, conv1d_weight, conv1d_bias, x_proj_weight, delta_proj_weight,
                               out_proj_weight, out_proj_bias,
                               A, B, C, D, delta_bias, B_proj_bias, C_proj_bias, delta_softplus)
 
 
+
 def mamba_inner_ref(
     xz, conv1d_weight, conv1d_bias, x_proj_weight, delta_proj_weight,
     out_proj_weight, out_proj_bias,