[torchlib] Fix repeat_interleave when repeats is a symbolic tensor

onnxscript/function_libs/torch_lib/ops/core.py

@@ -7327,9 +7327,18 @@ def aten_repeat_interleave_self_int(
     self_rank = len(self.shape)
     pos_dim = (dim + self_rank) % self_rank
     unsqueezed = op.Unsqueeze(self, [pos_dim + 1])
-    tiles = [1] * (self_rank + 1)
-    tiles[pos_dim + 1] = repeats
-    tile_repeat = op.Constant(value=ir.tensor(tiles, dtype=INT64.dtype))
+    if isinstance(repeats, int):
+        tiles = [1] * (self_rank + 1)
+        tiles[pos_dim + 1] = repeats
+        tile_repeat = op.Constant(value=ir.tensor(tiles, dtype=INT64.dtype))
+    else:
+        # repeats is a symbolic tensor
+        tile_repeat = op.Concat(
+            op.Constant(value=ir.tensor([1] * pos_dim, dtype=INT64.dtype)),
+            op.Reshape(repeats, op.Constant(value=ir.tensor([-1], dtype=INT64.dtype))),
+            op.Constant(value=ir.tensor([1] * (self_rank - pos_dim), dtype=INT64.dtype)),
+            axis=0,
+        )
     tiled = op.Tile(unsqueezed, tile_repeat)
     if self_rank == 1:
         return op.Identity(tiled)