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Mojo struct

MaterializedMask

struct MaterializedMask[dtype_: DType, layout_: Layout, origin_: ImmOrigin]

Mask that's backed by a materialized tensor.

Parameters

• ​dtype_ (DType): Element type of the backing mask tensor.
• ​layout_ (Layout): Memory layout of the backing mask tensor.
• ​origin_ (ImmOrigin): Origin (ownership/mutability qualifier) of the backing mask tensor.

Fields

• ​mask_tensor (LayoutTensor[dtype_, layout_, origin_]):
• ​start_pos (OptionalReg[LayoutTensor[DType.uint32, Layout.row_major(Int(-1)), ImmutAnyOrigin]]):
• ​is_multiple_of_2 (Bool):

Implemented traits

AnyType, Copyable, Deinitable, DevicePassable, ImplicitlyCopyable, MHAMask, Movable, RegisterPassable, TrivialRegisterPassable

comptime members

apply_log2e_after_mask

comptime apply_log2e_after_mask = True

check_mask_during_decoding

comptime check_mask_during_decoding = True

device_type

comptime device_type = MaterializedMask[dtype_, layout_, origin_]

mask_out_of_bound

comptime mask_out_of_bound = True

mask_safe_out_of_bounds

comptime mask_safe_out_of_bounds = False

Methods

__init__

def __init__(mask_tensor: LayoutTensor[dtype_, layout_, origin_], start_pos: OptionalReg[LayoutTensor[DType.uint32, Layout.row_major(Int(-1)), ImmutAnyOrigin]] = None) -> Self

get_type_name

static def get_type_name() -> String

Returns:

String

name

static def name() -> String

Returns:

String

get_start_pos

def get_start_pos(self, batch_idx: Int) -> Int

Returns:

Int

mask

def mask[dtype: DType, width: SIMDLength, //, *, element_type: DType = DType.uint32](self, coord: IndexList[Int(4), element_type=element_type], score_vec: SIMD[dtype, width]) -> SIMD[dtype, width]

Returns:

SIMD[dtype, width]

status

def status[*, element_type: DType = DType.uint32](self, seq_id: UInt32, tile_offset: IndexList[Int(2), element_type=element_type], tile_size: IndexList[Int(2), element_type=element_type]) -> TileMaskStatus

Returns:

TileMaskStatus

start_column

def start_column[BM: Int, BN: Int, page_size: Int](self, seq_id: UInt32, row: UInt32) -> UInt32

Returns:

UInt32

start_column_alignment

static def start_column_alignment[BM: Int, BN: Int, page_size: Int]() -> Int

Returns:

Int

total_iters

def total_iters[BM: Int, BN: Int, page_size: Int](self, seq_id: UInt32, row: UInt32, num_cols: UInt32) -> UInt32

Returns:

UInt32

count_nonfull_sets

static def count_nonfull_sets(BM: Int, BN: Int) -> Int

Returns:

Int

last_masked_set_end

def last_masked_set_end[BM: Int, BN: Int, page_size: Int](self, seq_id: UInt32, row: UInt32, num_cols: UInt32) -> UInt32

Returns:

UInt32

masked_set_ends

def masked_set_ends[BM: Int, BN: Int, page_size: Int](self, seq_id: UInt32, row: UInt32, num_cols: UInt32) -> StaticTuple[UInt32, MaterializedMask.count_nonfull_sets(BM, BN)]

Returns:

StaticTuple[UInt32, MaterializedMask.count_nonfull_sets(BM, BN)]

nonfull_sets

static def nonfull_sets[BM: Int, BN: Int]() -> StaticTuple[TileMaskStatus, MaterializedMask.count_nonfull_sets(BM, BN)]

Returns:

StaticTuple[TileMaskStatus, MaterializedMask.count_nonfull_sets(BM, BN)]

mask_strategies

static def mask_strategies[BM: Int, BN: Int]() -> StaticTuple[MaskStrategy, MaterializedMask.count_nonfull_sets(BM, BN)]

Returns:

StaticTuple[MaskStrategy, MaterializedMask.count_nonfull_sets(BM, BN)]

mask_bits

def mask_bits(self, seq_id: UInt32, score_row: Int32, col_start: Int32, num_keys: Int32) -> UInt32

Returns:

UInt32

sliding_window_size

static def sliding_window_size() -> Int

Returns:

Int