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Mojo struct

RuntimeLayout

struct RuntimeLayout[layout: Layout, /, *, element_type: DType = DType.int64, linear_idx_type: DType = DType.int64]

A runtime-configurable layout that uses RuntimeTuple for storage.

This struct provides a layout implementation that can be modified at runtime, unlike the static Layout type. It uses RuntimeTuple for shape and stride storage.

The layout must have statically known dimensions at compile time, but the actual shape and stride values can be modified during execution.

Parameters​

  • ​layout (Layout): The static Layout type to base this runtime layout on.
  • ​element_type (DType): The integer type of the each dimension element. Must be signed.
  • ​linear_idx_type (DType): The integer type of the linear index into memory returned by crd2idx. Must be signed.

Fields​

  • ​shape (RuntimeLayout[layout, element_type=element_type, linear_idx_type=linear_idx_type].ShapeType): The shape of the layout as a runtime tuple. Stores the size of each dimension. Uses the specified bitwidth and is unsigned. Must match the static layout's shape dimensions.
  • ​stride (RuntimeLayout[layout, element_type=element_type, linear_idx_type=linear_idx_type].StrideType): The stride of the layout as a runtime tuple. Stores the stride (step size) for each dimension. Uses 64-bit unsigned integers since strides can be large values. Must match the static layout's stride dimensions.

Implemented traits​

AnyType, Copyable, Defaultable, ImplicitlyCopyable, ImplicitlyDeletable, Movable, RegisterPassable, TrivialRegisterPassable, Writable

comptime members​

ShapeType​

comptime ShapeType = RuntimeTuple[layout.shape, element_type=element_type]

Type alias for the runtime shape tuple.

StrideType​

comptime StrideType = RuntimeTuple[layout.stride, element_type=linear_idx_type]

Type alias for the runtime stride tuple.

Methods​

__init__​

def __init__() -> Self

Initialize a RuntimeLayout with default values.

Creates a new RuntimeLayout instance with default shape and stride values. Requires that the static layout has known dimensions at compile time.

Constraints:

The static layout that this runtime layout is based on must have all dimensions known.

def __init__(shape: RuntimeTuple[layout.shape, element_type=element_type], stride: RuntimeTuple[layout.stride, element_type=linear_idx_type]) -> Self

Initialize a RuntimeLayout with specified shape and stride.

Args:

__call__​

def __call__(self, idx: Int) -> Scalar[linear_idx_type]

Convert a single index to a flat linear index.

Args:

  • ​idx (Int): The one-dimensional index to convert.

Returns:

Scalar[linear_idx_type]: The corresponding flat linear index in the layout.

def __call__[t: IntTuple](self, idx: RuntimeTuple[t, element_type=idx.element_type]) -> Scalar[linear_idx_type]

Convert a multi-dimensional index to a flat linear index.

Parameters:

  • ​t (IntTuple): The IntTuple type for the index.

Args:

Returns:

Scalar[linear_idx_type]: The corresponding flat linear index in the layout.

idx2crd​

def idx2crd[t: IntTuple](self, idx: RuntimeTuple[t, element_type=idx.element_type]) -> RuntimeTuple[idx2crd(t, layout.shape, layout.stride), element_type=element_type]

Converts a linear index to logical coordinates.

This is the inverse operation of the call method, mapping from a memory index back to the corresponding logical coordinates.

Parameters:

  • ​t (IntTuple): The IntTuple type for the index.

Args:

Returns:

RuntimeTuple[idx2crd(t, layout.shape, layout.stride), element_type=element_type]: The logical coordinates corresponding to the given index.

size​

def size(self) -> Int

Calculate the total number of elements in the layout.

Returns:

Int: The product of all dimensions in the shape, representing the total number of elements that can be addressed by this layout.

bound_check_required​

def bound_check_required(self) -> Bool

Determine if bounds checking is required for this layout.

Returns:

Bool: True if any dimension in the shape differs from the static layout's shape, False otherwise.

cast​

def cast[_element_type: DType, /, *, target_linear_idx_type: DType = linear_idx_type](self) -> RuntimeLayout[layout, element_type=_element_type, linear_idx_type=target_linear_idx_type]

Cast the layout to use a different element bitwidth.

Parameters:

  • ​_element_type (DType): The target data type.
  • ​target_linear_idx_type (DType): The target linear idx type.

Returns:

RuntimeLayout[layout, element_type=_element_type, linear_idx_type=target_linear_idx_type]: A new RuntimeLayout with the shape cast to the specified type.

row_major​

static def row_major[rank: Int, //](shape: IndexList[rank, element_type=shape.element_type]) -> Self

Create a row-major layout from the given shape.

In row-major layout, elements with adjacent rightmost indices are adjacent in memory.

Parameters:

  • ​rank (Int): The number of dimensions in the layout.

Args:

Returns:

Self: A RuntimeLayout with row-major stride ordering.

col_major​

static def col_major[rank: Int, //](shape: IndexList[rank, element_type=shape.element_type]) -> Self

Create a column-major layout from the given shape.

In column-major layout, elements with adjacent leftmost indices are adjacent in memory.

Parameters:

  • ​rank (Int): The number of dimensions in the layout.

Args:

Returns:

Self: A RuntimeLayout with column-major stride ordering.

write_to​

def write_to(self, mut writer: T)

Write a string representation of the layout to a writer.

Args:

  • ​writer (T): The Writer object to write the layout representation to.

sublayout​

def sublayout[i: Int](self) -> RuntimeLayout[layout[i], element_type=element_type, linear_idx_type=linear_idx_type]

Extract a nested sublayout at the specified index.

Parameters:

  • ​i (Int): The index of the nested layout to extract.

Returns:

RuntimeLayout[layout[i], element_type=element_type, linear_idx_type=linear_idx_type]: A RuntimeLayout representing the nested layout at index i.

dim​

def dim(self, i: Int) -> Int

Get the size of the dimension at the specified index.

Args:

  • ​i (Int): The index of the dimension to retrieve.

Returns:

Int: The size of the dimension at index i.

__len__​

static def __len__() -> Int

Get the number of dimensions in the layout.

Returns:

Int: The number of dimensions (rank) of the layout.

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