import torch

embed = torch.randn(2, 8192)
x = torch.zeros(8192)

torch._dynamo.mark_dynamic(x, 0)

@torch.compile(backend="aot_eager", fullgraph=True)
def f(embedding_indices, x):
    added_tokens_mask = torch.where(x > 10000, 1, 0)
    ei = torch.narrow(embedding_indices, 1, 0, x.size(0))
    return ei.clone()

f(embed, x)