Mojo function

k_matmul_ragged_paged

k_matmul_ragged_paged[dtype: DType, params: KVCacheStaticParams, page_size: Int, //, target: StringSlice[StaticConstantOrigin]](hidden_state: LayoutTensor[dtype, layout, origin, element_layout=element_layout, layout_int_type=layout_int_type, linear_idx_type=linear_idx_type, masked=masked, alignment=alignment], input_row_offsets: LayoutTensor[DType.uint32, layout, origin, element_layout=element_layout, layout_int_type=layout_int_type, linear_idx_type=linear_idx_type, masked=masked, alignment=alignment], weight: LayoutTensor[dtype, layout, origin, element_layout=element_layout, layout_int_type=layout_int_type, linear_idx_type=linear_idx_type, masked=masked, alignment=alignment], kv_collection: PagedKVCacheCollection[dtype, params, page_size], layer_idx: UInt32, ctx: DeviceContextPtr)

Performs a matmul, writing the output into a mutable PagedKVCacheCollection object.

Args:

hidden_state (LayoutTensor): Tensor with shape (sum(seq_lens), num_heads * head_size).
input_row_offsets (LayoutTensor): Tensor with shape (batch_size + 1,) denoting the start of each sequence along the seq_len dimension.
weight (LayoutTensor): Tensor with shape (num_heads * head_size, num_kv_heads * head_size).
kv_collection (PagedKVCacheCollection): The historical KVCache for keys and values. The KVCache for this layer is retrieved via layer_idx.
layer_idx (UInt32): The index of the layer being executed. Used to retrieve the KVCache for the given layer from kv_collection.
ctx (DeviceContextPtr): The call context pointer, passed by the graph compiler.