Strided Layout — Hurray Format Specification

Layout tag: 0x03 | Tier: 1

This section uses RFC 2119 key words: MUST, MUST NOT, REQUIRED, SHALL, SHALL NOT, SHOULD, SHOULD NOT, RECOMMENDED, MAY, and OPTIONAL.

Description

The strided layout generalises both row-major and column-major by allowing an arbitrary stride value per dimension. It is the most general of the simple (non-tiled, non-curve) layouts.

Additional Descriptor Fields

Stride Semantics

• A positive stride advances forward through the buffer.
• A negative stride advances backward. A negative stride on dimension k reverses that dimension: logical index 0 maps to the highest physical offset along that axis.
• A zero stride on dimension k means all indices along k map to the same physical element — a broadcast (virtual) dimension. Data is not physically replicated.

Negative and zero strides are valid. A conforming implementation MUST support them.

Element Address

The linear element offset of element [i_0, i_1, ..., i_{r-1}] is:

offset = sum(i_k * strides[k] for k = 0, ..., r - 1)

When negative strides are present, the offset may be negative relative to the base address at byte_offset. The byte_offset field MUST be set such that element [0, 0, ..., 0] is addressable within the buffer. The physical address of every valid element MUST lie within the buffer's bounds.

Buffer Size

The minimum buffer size must cover every addressable element:

max_offset = sum(max(0, strides[k] * (shape[k] - 1)) for all k)
min_offset = sum(min(0, strides[k] * (shape[k] - 1)) for all k)
range_elements = max_offset - min_offset + 1

Buffer size in bytes depends on the element type (see memory-layout.md § Element Address Computation).

Validity Constraints

This layout MUST NOT be used for rank-0 (scalar) tensors. See data-model.md § Scalar Tensors.

Contiguity

A strided tensor is dense (contiguous with no gaps) if and only if the absolute values of its strides form a permutation of the row-major strides for the same shape. Implementations SHOULD NOT assume density without verifying this condition.

Example

A rank-2 tensor with shape [3, 4] and strides [-4, 1] represents a row-major matrix with the row order reversed. byte_offset points to what would be element [2, 0] in a non-reversed matrix. Element [2, 3] is at offset 2 * (-4) + 3 * 1 = -5. The buffer MUST be large enough to cover the full range from offset -8 to 0 (9 elements).