shape_broadcast.h#

Shared helpers for shape-inference functions of binary ONNX operators that support numpy-style (multidirectional) broadcasting.

namespace ONNX_LIGHT_NAMESPACE
namespace onnx_optim
namespace shapes

Functions

OptimShape BroadcastShapes(const OptimShape &a, const OptimShape &b)#

Computes the broadcast result shape of two :cpp:class:OptimShape operands following the ONNX (numpy-style) multidirectional broadcasting rules.

The shapes are right-aligned and the dimensions are paired starting from the trailing axis (missing leading dimensions are treated as 1). For each paired dimension (d_a, d_b) the resulting dimension is computed as follows:

  • if both are concrete integers: standard broadcasting rules are enforced — equal dimensions or a dimension of 1 paired with anything are accepted; mismatching non-unit integers throw std::invalid_argument;

  • if either is the integer 1: the result is the other dimension;

  • if both are equal (same integer or same symbolic expression): the result is that dimension;

  • if one is a concrete integer (different from 1) and the other is symbolic: the concrete integer wins (it is the only value compatible with broadcasting against itself);

  • if both are different symbolic expressions: a fresh symbolic dimension is produced, encoding the broadcast as "broadcast(<a>, <b>)" so that the symbolic information is preserved.

Throws:

std::invalid_argument – when two concrete integer dimensions are incompatible under broadcasting.

void ComputeShapeBinaryBroadcast(ShapesContext &ctx, const NodeProto &node, const char *input_a, const char *input_b, const char *expected_op_type, TensorType output_dtype)#

Generic shape-inference helper for binary ONNX operators that support numpy-style broadcasting. Reads the descriptors of input_a and input_b from ctx, computes the broadcast output shape and stores a new entry under node.output(0) with the given output_dtype.

The helper enforces the following preconditions:

  • node.op_type() must equal expected_op_type;

  • node must declare at least one output;

  • both input_a and input_b must be present in ctx.

Throws:

  • std::invalid_argument – if node.op_type() differs from expected_op_type or if node has no output, or if the two input shapes are not broadcast-compatible.

  • std::out_of_range – if either input name is missing from ctx.