shape_quantization.h#

Shape-inference functions for ONNX operators in the quantization family.

namespace ONNX_LIGHT_NAMESPACE
namespace onnx_optim
namespace shapes
namespace quantization#

Functions

void ComputeShapeQuantizeLinear(ShapesContext &ctx, const NodeProto &node, const char *x, const char *y_zero_point)#

Computes the output :cpp:class:OptimTensor of a QuantizeLinear node and stores it in ctx.

QuantizeLinear produces an output y that always has the same shape as the input x. The output element type is resolved as follows:

  • when y_zero_point is supplied (third input, non-empty name) the output dtype is the dtype of y_zero_point;

  • otherwise, when the output_dtype integer attribute is set (opset 23+), it is interpreted as a TensorProto::DataType and mapped to the matching :cpp:enum:TensorType;

  • otherwise the output dtype defaults to uint8.

The axis, saturate, block_size, and precision attributes do not affect the output shape and are therefore not inspected by this function.

Parameters:

  • ctx – In/out context. Must already contain entries for x, y_scale, and y_zero_point when the latter is provided; on return it also contains an entry for node.output(0).

  • node – The QuantizeLinear NodeProto whose output should be described. node.op_type() must be "QuantizeLinear" and node must declare at least one output.

  • x – Name of the input value to read from ctx. Must be present in ctx.

  • y_zero_point – Name of the y_zero_point input value, or nullptr / empty string when the input is omitted. When non-empty it must be present in ctx.

Throws:

  • std::invalid_argument – if node.op_type() is not "QuantizeLinear", if node has no output, or if output_dtype is set to a value that does not map to a supported :cpp:enum:TensorType.

  • std::out_of_range – if x (or y_zero_point when non-empty) is not present in ctx.