diff --git a/torch_geometric/nn/conv/hypergraph_conv.py b/torch_geometric/nn/conv/hypergraph_conv.py
index de1c00180ed75..3894def04bc2f 100644
--- a/torch_geometric/nn/conv/hypergraph_conv.py
+++ b/torch_geometric/nn/conv/hypergraph_conv.py
@@ -5,6 +5,7 @@
 from torch import Tensor
 from torch.nn import Parameter
 
+from torch_geometric.experimental import disable_dynamic_shapes
 from torch_geometric.nn.conv import MessagePassing
 from torch_geometric.nn.dense.linear import Linear
 from torch_geometric.nn.inits import glorot, zeros
@@ -107,9 +108,11 @@ def reset_parameters(self):
             glorot(self.att)
         zeros(self.bias)
 
+    @disable_dynamic_shapes(required_args=['num_edges'])
     def forward(self, x: Tensor, hyperedge_index: Tensor,
                 hyperedge_weight: Optional[Tensor] = None,
-                hyperedge_attr: Optional[Tensor] = None) -> Tensor:
+                hyperedge_attr: Optional[Tensor] = None,
+                num_edges: Optional[int] = None) -> Tensor:
         r"""Runs the forward pass of the module.
 
         Args:
@@ -125,10 +128,15 @@ def forward(self, x: Tensor, hyperedge_index: Tensor,
                 in :math:`\mathbb{R}^{M \times F}`.
                 These features only need to get passed in case
                 :obj:`use_attention=True`. (default: :obj:`None`)
+            num_edges (int, optional) : Number of edges. (default: :obj:`None`)
         """
-        num_nodes, num_edges = x.size(0), 0
-        if hyperedge_index.numel() > 0:
-            num_edges = int(hyperedge_index[1].max()) + 1
+        num_nodes = x.size(0)
+
+        if num_edges is None:
+            if hyperedge_index.numel() > 0:
+                num_edges = int(hyperedge_index[1].max()) + 1
+            else:
+                num_edges = 0
 
         if hyperedge_weight is None:
             hyperedge_weight = x.new_ones(num_edges)