defines

Classes

TensorLifetime

Tensor operator lifetime.

Attributes:

• tensor_id (TensorId) –

  Unique identifier for the tensor

• start_op (int) –

  Index of the first operator that uses/defines it

• end_op (int) –

  Index of the last operator that uses it

Functions

add_op

add_op(op_idx: int)

Add an operator index to the lifetime.

Parameters:

• op_idx

  (int) –

  Operator index to add

merge

merge(other: TensorLifetime)

Merge another lifetime into this one.

This updates the start and end operators to encompass both lifetimes. Useful when tensors have aliases.

Parameters:

• other

  (TensorLifetime) –

  Another tensor lifetime to merge

TensorAllocation

Metadata for a tensor allocation.

Attributes:

• tensor_id (TensorId) –

  Unique identifier for the tensor

• memory (MemoryType) –

  Memory type for the allocation

• offset (int) –

  Offset within the memory arena

• size (int) –

  Size of the allocation in bytes

ArenaUsage

Metadata for a memory arena.

Attributes:

• memory (MemoryType) –

  Memory type (e.g., DTCM, ITCM)

• total_size (int) –

  Total bytes in this arena

• used (int) –

  Bytes actually used

Functions

allocate

allocate(size: int) -> int

Allocate a segment of the arena and return its offset

MemoryConstraint

User-defined memory constraint

Attributes:

• name (MemoryType) –

  Memory type (e.g., DTCM, ITCM)

• max_size (int | None) –

  Maximum size in bytes, or None for no limit

MemoryPlan

Top-level memory plan for tensors.

Attributes:

• tensor_allocs (dict[str, TensorAllocation]) –

  Tensor allocations

• arena_usages (dict[MemoryType, ArenaUsage]) –

  Memory arena usages

• tensor_lifetimes (dict[TensorId, TensorLifetime]) –

  Tensor lifetimes

Functions

get_allocation

get_allocation(tensor_id: str) -> TensorAllocation

Get the allocation metadata for a given tensor ID.

Parameters:

• tensor_id

  (str) –

  The tensor ID to look up.

Raises:

• KeyError –

  If the tensor ID is not found in the allocations.

Returns:

• TensorAllocation ( TensorAllocation ) –

  The allocation metadata for the tensor.

MemoryPlannerType

Memory planner type

Attributes:

• greedy (str) –

  Greedy memory planner

TensorAttributes

This class provides the baseline set of tensor attribute rules.

Attributes:

• memory (MemoryType) –

  Memory placement for tensors

MemoryFreeBlock

Metadata for a free memory block.

Attributes:

• offset (int) –

  Offset of the free block

• size (int) –

  Size of the free block

MemoryActiveBlock

Metadata for an active memory block.

Attributes:

• end_time (int) –

  End time of the active block

• offset (int) –

  Offset of the active block

• size (int) –

  Size of the active block