flashinfer.rope.apply_llama31_rope_pos_ids_inplace#
- flashinfer.rope.apply_llama31_rope_pos_ids_inplace(q: torch.Tensor, k: torch.Tensor, pos_ids: torch.Tensor, rotary_dim: int | None = None, interleave: bool = False, rope_scale: float = 8, rope_theta: float = 500000.0, low_freq_factor: float = 1, high_freq_factor: float = 4, old_context_len: int = 8192) None #
Apply Llama 3.1 style rotary embedding to a batch of queries/keys (stored as RaggedTensor) inplace. cos/sin values are computed on the fly inside the kernel.
We use
indptr
to denote the start pointer of each segment in the batch, the i-th segment the query of the i-th segment isq[indptr[i]:indptr[i+1]]
and the key of the i-th segment isk[indptr[i]:indptr[i+1]]
, the first element ofindptr
is always 0 and the last element ofindptr
is the total number of queries/keys in the batch. Please see Ragged Tensor tutorial for more details about the ragged tensor.- Parameters:
q (torch.Tensor) – Query ragged tensor, shape:
(nnz, num_q_heads, head_dim)
, wherennz
is the last element ofindptr
.k (torch.Tensor) – Key ragged tensor, shape:
(nnz, num_k_heads, head_dim)
, wherennz
is the last element ofindptr
.pos_ids (torch.Tensor) – Position indices, shape:
(nnz)
.rotary_dim (Optional[int]) – The dimensions to apply RoPE, if
None
, we apply RoPE to the entire head dimension, otherwise, we apply RoPE to the firstrotary_dim
dimensions, default:None
.interleave (bool) –
Whether to use interleaved layout in the last dimension, default:
False
.If
True
, the last dimension of the query/key tensor is interleaved, i.e., we rotate the even dimensions([..., ::2])
and odd dimensions([..., 1::2])
.If
False
, the last dimension of the query/key tensor is not interleaved, i.e., we rorate the first half dimensions([..., :head_dim//2])
and the second half dimensions([..., head_dim//2:])
.
rope_scale (float) – The scaling factor used in the rope embedding, default:
8
.rope_theta (float) – The theta value used in the rope embedding, default:
5e5
.low_freq_factor (float) – The low frequency factor used in Llama 3.1 RoPE, default:
1
.high_freq_factor (float) – The high frequency factor used in Llama 3.1 RoPE, default:
4
.old_context_len (int) – The old context length used in Llama 3.1 RoPE, default:
8192
.
See also