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Mojo module

functional

Implements higher-order functions.

You can import these APIs from the algorithm package. For example:

from algorithm import map
from algorithm import map

Aliases​

  • ​BinaryTile1DTileUnitFunc = fn[Int](Int, Int) capturing -> None: Signature of a tiled function that performs some work with a dynamic tile size and a secondary static tile size.
  • ​Dynamic1DTileUnitFunc = fn(Int, Int) capturing -> None: Signature of a 1d tiled function that performs some work with a dynamic tile size and an offset. i.e. func(offset: Int, tile_size: Int)
  • ​Dynamic1DTileUnswitchUnitFunc = fn[Bool](Int, Int, Int) capturing -> None:
  • ​Static1DTileUnitFunc = fn[Int](Int) capturing -> None: Signature of a 1d tiled function that performs some work with a static tile size and an offset. i.e. func<tile_size: Int> (offset: Int)
  • ​Static1DTileUnitFuncWithFlag = fn[Int, Bool](Int) capturing -> None:
  • ​Static1DTileUnitFuncWithFlags = fn[Int, Bool, Bool](Int) capturing -> None:
  • ​Static1DTileUnswitchUnitFunc = fn[Int, Bool](Int, Int) capturing -> None: Signature of a tiled function that performs some work with a static tile size and an offset. i.e. func<tile_size: Int> (offset: Int)
  • ​Static2DTileUnitFunc = fn[Int, Int](Int, Int) capturing -> None: Signature of a 2d tiled function that performs some work with a static tile size and an offset. i.e. func<tile_size_x: Int, tile_size_y: Int> (offset_x: Int, offset_y: Int)
  • ​stencil = _stencil_impl_cpu[__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,::Int,::Int,stdlib::utils::index::IndexList[$7, Int:
  • ​stencil_gpu = _stencil_impl_gpu[__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,__mlir_type.!lit.origin.set,::Int,::Int,stdlib::utils::index::IndexList[$7, Int:
  • ​SwitchedFunction = fn[Bool]() raises capturing -> None:
  • ​SwitchedFunction2 = fn[Bool, Bool]() capturing -> None:

Functions​

  • ​elementwise: Executes func[width, rank](indices), possibly as sub-tasks, for a suitable combination of width and indices so as to cover shape. Returns when all sub-tasks have completed.
  • ​map: Maps a function over a range from 0 to size.
  • ​parallelize: Executes func(0) ... func(num_work_items-1) as sub-tasks in parallel, and returns when all are complete.
  • ​parallelize_over_rows: Parallelize func over non-axis dims of shape.
  • ​sync_parallelize: Executes func(0) ... func(num_work_items-1) as parallel sub-tasks, and returns when all are complete.
  • ​tile: A generator that launches work groups in specified list of tile sizes.
  • ​tile_and_unswitch: Performs time and unswitch functional transformation.
  • ​tile_middle_unswitch_boundaries: Divides 1d iteration space into three parts and tiles them with different steps.
  • ​unswitch: Performs a functional unswitch transformation.
  • ​vectorize: Simplifies SIMD optimized loops by mapping a function across a range from 0 to size, incrementing by simd_width at each step. The remainder of size % simd_width will run in separate iterations.