LeakyReLU

Quantized lucid.nn.LeakyReLU — leaky_relu(x, slope) then fake-quant.

The inference-time replacement for a calibrated float nn.LeakyReLU, installed by lucid.quantization.convert / from_float. Under the sidecar representation (design B) the quantized layer is the float leaky-ReLU followed by a fake-quantize to the calibrated output grid. Like ELU its range is unbounded on both sides (linear far from the origin), so it is calibrated with a real observer, not a lucid.quantization.FixedQParamsObserver.

The negative_slope — the small gradient applied to $x < 0$ that keeps dead-unit gradients alive — is a parameter of the activation; from_float copies it from the source nn.LeakyReLU (via the internal _configure hook) so the quantized curve matches the float one before the output is snapped to the grid.

with $\operatorname{fake\_quant}(t) = (\operatorname{clamp}( \operatorname{round}(t/S) + Z, q_{\min}, q_{\max}) - Z)\, S$ and the calibrated output (scale, zero_point) $S, Z$.