Module pooling 

Quantum pooling layers for dimensionality reduction

This module provides quantum pooling operations that reduce the number of qubits while preserving important quantum features, analogous to pooling in classical CNNs.

Layers

• QMaxPool: Select qubits with highest measurement probability
• QAvgPool: Average measurements over pooling regions

Features

• Configurable pool size and stride
• Non-trainable dimensionality reduction
• Compatible with TorchQuantum training framework

Example

use quantrs2_ml::torchquantum::pooling::QMaxPool;

// Create pooling layer: 8 qubits, pool size 2, stride 2
let pool = QMaxPool::new(8, 2, 2)?;
println!("Output qubits: {}", pool.output_wires());

Structs

QAvgPool

Quantum average pooling layer

QMaxPool

Quantum pooling layer using maximum measurement probability