Mojo function

generic_fused_qk_rope_bshd_paged

generic_fused_qk_rope_bshd_paged[dtype: DType, //, *, interleaved: Bool, target: StringSlice[StaticConstantOrigin]](q_proj: TileTensor[dtype, address_space=q_proj.address_space, linear_idx_type=q_proj.linear_idx_type, element_size=q_proj.element_size], kv_collection: PagedKVCacheCollection, freqs_cis: TileTensor[dtype, address_space=freqs_cis.address_space, linear_idx_type=freqs_cis.linear_idx_type, element_size=freqs_cis.element_size], layer_idx: UInt32, valid_lengths: TileTensor[DType.uint32, address_space=valid_lengths.address_space, linear_idx_type=valid_lengths.linear_idx_type, element_size=valid_lengths.element_size], output: TileTensor[dtype, address_space=output.address_space, linear_idx_type=output.linear_idx_type, element_size=output.element_size], context: DeviceContextPtr = DeviceContextPtr())

Performs a fused RoPE projection for Q and K with paged KV cache.

This is the paged equivalent of generic_fused_qk_rope_bshd_continuous_batch. It applies RoPE to both Q (returned) and K (in paged cache) to ensure proper dependency ordering after fused_qkv_padded_matmul.

Args:

q_proj (TileTensor[dtype, address_space=q_proj.address_space, linear_idx_type=q_proj.linear_idx_type, element_size=q_proj.element_size]): Query projection tensor of shape [batch, seq_len, n_heads, head_dim].
kv_collection (PagedKVCacheCollection): The paged KV cache collection.
freqs_cis (TileTensor[dtype, address_space=freqs_cis.address_space, linear_idx_type=freqs_cis.linear_idx_type, element_size=freqs_cis.element_size]): Frequency tensor for RoPE of shape [max_seq_len, head_dim].
layer_idx (UInt32): The layer index for accessing the correct cache.
valid_lengths (TileTensor[DType.uint32, address_space=valid_lengths.address_space, linear_idx_type=valid_lengths.linear_idx_type, element_size=valid_lengths.element_size]): Tensor of shape [batch] containing the valid length for each sequence. RoPE is only applied to positions within these lengths.
output (TileTensor[dtype, address_space=output.address_space, linear_idx_type=output.linear_idx_type, element_size=output.element_size]): Output tensor for Q with RoPE applied, same shape as q_proj.
context (DeviceContextPtr): Device context pointer for execution.