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Mojo function

top_k

def top_k[dtype: DType, out_idx_type: DType, //, largest: Bool = True, target: StringSlice[StaticConstantOrigin] = StringSlice("cpu")](input: TileTensor[dtype, address_space=input.address_space, linear_idx_type=input.linear_idx_type, element_size=input.element_size], max_k: Int, axis: Int, out_vals: TileTensor[dtype, address_space=out_vals.address_space, linear_idx_type=out_vals.linear_idx_type, element_size=out_vals.element_size], out_idxs: TileTensor[out_idx_type, address_space=out_idxs.address_space, linear_idx_type=out_idxs.linear_idx_type, element_size=out_idxs.element_size], sorted: Bool, ctx: DeviceContext, k: Optional[TileTensor[DType.int64, Layout[*?, *?], ImmutAnyOrigin]] = None)

Implementation of the Top K algorithm. Returns the top or bottom K elements and their index along a specified axis.

Parameters:

dtype (DType): Data type of the input buffer.
out_idx_type (DType): The data dtype of the output indices (default == DType.int64).
largest (Bool): Whether to find the maximum (top k) or minimum value (bottom k).
target (StringSlice[StaticConstantOrigin]): The target to run on.

Args:

input (TileTensor[dtype, address_space=input.address_space, linear_idx_type=input.linear_idx_type, element_size=input.element_size]): The input tensor.
max_k (Int): The largest number of top elements.
axis (Int): The axis along which to operate.
out_vals (TileTensor[dtype, address_space=out_vals.address_space, linear_idx_type=out_vals.linear_idx_type, element_size=out_vals.element_size]): Output values.
out_idxs (TileTensor[out_idx_type, address_space=out_idxs.address_space, linear_idx_type=out_idxs.linear_idx_type, element_size=out_idxs.element_size]): Output indices.
sorted (Bool): Indicates if the top/bottom K elements are in (stable) sorted order.
ctx (DeviceContext): The device call context.
k (Optional[TileTensor[DType.int64, Layout[*?, *?], ImmutAnyOrigin]]): Per batch element k value.