coreai_opt.quantization.spec.RunningRangeMixin

class coreai_opt.quantization.spec.RunningRangeMixin(*args, **kwargs)

Bases: object

Mixin for calculators that maintain running min/max range buffers.

Provides running_min and running_max buffers, first-forward initialization via _initialize_state, and a compute_qparams implementation that delegates the range-update rule to the abstract update_running_range hook.

Subclasses that want to re-use the logic of computing quantization parameters but with different ways of updating the running statistics can override the update_running_range method.

Must appear before QParamsCalculatorBase in the MRO so that its compute_qparams and _initialize_state take precedence over the base-class defaults.

Parameters:

• args (object)

• kwargs (object)

__init__(*args, **kwargs)

Parameters:

• args (object)

• kwargs (object)

Return type:

None

Methods

compute_qparams(tensor, min_val, max_val)	Update running range, persist to buffers, then compute qparams.
extra_repr()
update_running_range(min_val, max_val)	Return (updated_min, updated_max) using subclass-specific rule.

compute_qparams(tensor, min_val, max_val)

Update running range, persist to buffers, then compute qparams.

Parameters:

• tensor (Tensor)

• min_val (Tensor)

• max_val (Tensor)

Return type:

tuple[Tensor, Tensor | None, Tensor | None]

extra_repr()

Return type:

str

abstract update_running_range(min_val, max_val)

Return (updated_min, updated_max) using subclass-specific rule.

Parameters:

• min_val (Tensor)

• max_val (Tensor)

Return type:

tuple[Tensor, Tensor]

running_max: Tensor

running_min: Tensor