Print 5D tensors

examples/model-conversion/scripts/causal/run-org-model-multi-token.py

@@ -50,10 +50,14 @@ def summarize(tensor: torch.Tensor, name: str, max_seq: int = 3, max_vals: int =
     - 2D tensors (seq, hidden)
     - 3D tensors (batch, seq, hidden)
     - 4D tensors (batch, seq, heads, dim_per_head) via flattening heads × dim_per_head
+    - 5D tensors
 
     Shows first and last max_vals of each vector per sequence position.
     """
     t = tensor.detach().to(torch.float32).cpu()
+    ten_shape = t.shape
+    while t.ndim > 4:
+        t = t.squeeze(0)
 
     # Determine dimensions
     if t.ndim == 3:
@@ -63,12 +67,11 @@ def summarize(tensor: torch.Tensor, name: str, max_seq: int = 3, max_vals: int =
         t = t.unsqueeze(0)
     elif t.ndim == 4:
         _, s, _, _ = t.shape
+    
     else:
         print(f"Skipping tensor due to unsupported dimensions: {t.ndim}")
         return
 
-    ten_shape = t.shape
-
     print(f"ggml_debug: {name} = (f32)  ... = {{{ten_shape}}}")
     print("                                     [")
     print("                                      [")