helion.Config

class helion.Config(*, block_sizes=None, loop_orders=None, flatten_loops=None, l2_groupings=None, reduction_loops=None, range_unroll_factors=None, range_warp_specializes=None, range_num_stages=None, range_multi_buffers=None, range_flattens=None, static_ranges=None, load_eviction_policies=None, num_warps=None, num_stages=None, pid_type=None, indexing=None, **kwargs)

Parameters:

• block_sizes (list[int] | None) –

• loop_orders (list[list[int]] | None) –

• flatten_loops (list[bool] | None) –

• l2_groupings (list[int] | None) –

• reduction_loops (list[int | None] | None) –

• range_unroll_factors (list[int] | None) –

• range_warp_specializes (list[bool | None] | None) –

• range_num_stages (list[int] | None) –

• range_multi_buffers (list[bool | None] | None) –

• range_flattens (list[bool | None] | None) –

• static_ranges (list[bool] | None) –

• load_eviction_policies (list[Literal['', 'first', 'last']] | None) –

• num_warps (int | None) –

• num_stages (int | None) –

• pid_type (Optional[Literal['flat', 'xyz', 'persistent_blocked', 'persistent_interleaved']]) –

• indexing (Union[Literal['pointer', 'tensor_descriptor', 'block_ptr'], list[Literal['pointer', 'tensor_descriptor', 'block_ptr']], None]) –

• kwargs (object) –

__init__(*, block_sizes=None, loop_orders=None, flatten_loops=None, l2_groupings=None, reduction_loops=None, range_unroll_factors=None, range_warp_specializes=None, range_num_stages=None, range_multi_buffers=None, range_flattens=None, static_ranges=None, load_eviction_policies=None, num_warps=None, num_stages=None, pid_type=None, indexing=None, **kwargs)

Initialize a Config object.

Parameters:

• block_sizes (list[int] | None) – Controls tile sizes for hl.tile invocations.

• loop_orders (list[list[int]] | None) – Permutes iteration order of tiles.

• l2_groupings (list[int] | None) – Reorders program IDs for L2 cache locality.

• reduction_loops (list[int | None] | None) – Configures reduction loop behavior.

• range_unroll_factors (list[int] | None) – Loop unroll factors for tl.range calls.

• range_warp_specializes (list[bool | None] | None) – Warp specialization for tl.range calls.

• range_num_stages (list[int] | None) – Number of stages for tl.range calls.

• range_multi_buffers (list[bool | None] | None) – Controls disallow_acc_multi_buffer for tl.range calls.

• range_flattens (list[bool | None] | None) – Controls flatten parameter for tl.range calls.

• static_ranges (list[bool] | None) – Whether to use tl.static_range instead tl.range.

• load_eviction_policies (list[Literal['', 'first', 'last']] | None) – Eviction policies for load operations (“”, “first”, “last”).

• num_warps (int | None) – Number of warps per block.

• num_stages (int | None) – Number of stages for software pipelining.

• pid_type (Optional[Literal['flat', 'xyz', 'persistent_blocked', 'persistent_interleaved']]) – Program ID type strategy (“flat”, “xyz”, “persistent_blocked”, “persistent_interleaved”).

• indexing (Union[Literal['pointer', 'tensor_descriptor', 'block_ptr'], list[Literal['pointer', 'tensor_descriptor', 'block_ptr']], None]) –

  Indexing strategy for load and store operations. Can be: - A single strategy string (all loads/stores use this strategy):

  indexing=”block_ptr” # backward compatible

  • A list of strategies (one per load/store operation, must specify all): indexing=[“pointer”, “block_ptr”, “tensor_descriptor”]

  • Empty/omitted (all loads/stores default to “pointer”)

  Valid strategies: “pointer”, “tensor_descriptor”, “block_ptr”

• **kwargs (object) – Additional user-defined configuration parameters.

• flatten_loops (list[bool] | None) –

Methods

__init__(*[, block_sizes, loop_orders, ...])	Initialize a Config object.
from_json(json_str)	Create a Config object from a JSON string.
get(k[,d])
items()
keys()
load(path)	Load a config from a JSON file.
save(path)	Save the config to a JSON file.
to_json()	Convert the config to a JSON string.
values()

Attributes

block_sizes
flatten_loops
indexing
l2_groupings
load_eviction_policies
loop_orders
num_stages
num_warps
pid_type
range_flattens
range_multi_buffers
range_num_stages
range_unroll_factors
range_warp_specializes
reduction_loops
static_ranges
config

__init__(*, block_sizes=None, loop_orders=None, flatten_loops=None, l2_groupings=None, reduction_loops=None, range_unroll_factors=None, range_warp_specializes=None, range_num_stages=None, range_multi_buffers=None, range_flattens=None, static_ranges=None, load_eviction_policies=None, num_warps=None, num_stages=None, pid_type=None, indexing=None, **kwargs)

Initialize a Config object.

Parameters:

• block_sizes (list[int] | None) – Controls tile sizes for hl.tile invocations.

• loop_orders (list[list[int]] | None) – Permutes iteration order of tiles.

• l2_groupings (list[int] | None) – Reorders program IDs for L2 cache locality.

• reduction_loops (list[int | None] | None) – Configures reduction loop behavior.

• range_unroll_factors (list[int] | None) – Loop unroll factors for tl.range calls.

• range_warp_specializes (list[bool | None] | None) – Warp specialization for tl.range calls.

• range_num_stages (list[int] | None) – Number of stages for tl.range calls.

• range_multi_buffers (list[bool | None] | None) – Controls disallow_acc_multi_buffer for tl.range calls.

• range_flattens (list[bool | None] | None) – Controls flatten parameter for tl.range calls.

• static_ranges (list[bool] | None) – Whether to use tl.static_range instead tl.range.

• load_eviction_policies (list[Literal['', 'first', 'last']] | None) – Eviction policies for load operations (“”, “first”, “last”).

• num_warps (int | None) – Number of warps per block.

• num_stages (int | None) – Number of stages for software pipelining.

• pid_type (Optional[Literal['flat', 'xyz', 'persistent_blocked', 'persistent_interleaved']]) – Program ID type strategy (“flat”, “xyz”, “persistent_blocked”, “persistent_interleaved”).

• indexing (Union[Literal['pointer', 'tensor_descriptor', 'block_ptr'], list[Literal['pointer', 'tensor_descriptor', 'block_ptr']], None]) –

  Indexing strategy for load and store operations. Can be: - A single strategy string (all loads/stores use this strategy):

  indexing=”block_ptr” # backward compatible

  • A list of strategies (one per load/store operation, must specify all): indexing=[“pointer”, “block_ptr”, “tensor_descriptor”]

  • Empty/omitted (all loads/stores default to “pointer”)

  Valid strategies: “pointer”, “tensor_descriptor”, “block_ptr”

• **kwargs (object) – Additional user-defined configuration parameters.

• flatten_loops (list[bool] | None) –

config: dict[str, object]

to_json()

Convert the config to a JSON string.

Return type:

str

classmethod from_json(json_str)

Create a Config object from a JSON string.

Parameters:

json_str (str) –

Return type:

Config

save(path)

Save the config to a JSON file.

Parameters:

path (str | Path) –

Return type:

None

classmethod load(path)

Load a config from a JSON file.

Parameters:

path (str | Path) –

Return type:

Config

property block_sizes: list[int]

property loop_orders: list[list[int]]

property flatten_loops: list[bool]

property reduction_loops: list[int | None]

property num_warps: int

property num_stages: int

property l2_groupings: list[int]

property pid_type: Literal['flat', 'xyz', 'persistent_blocked', 'persistent_interleaved']

property range_unroll_factors: list[int]

property range_warp_specializes: list[bool | None]

property range_num_stages: list[int]

property range_multi_buffers: list[bool | None]

property range_flattens: list[bool | None]

property static_ranges: list[bool]

property load_eviction_policies: list[Literal['', 'first', 'last']]

property indexing: Literal['pointer', 'tensor_descriptor', 'block_ptr'] | list[Literal['pointer', 'tensor_descriptor', 'block_ptr']]