⚡ Batch Normalization
Step-by-step · mean · variance · normalize · scale & shift
Batch values (comma‑separated, e.g. 1.2, -0.5, 0.8, 2.1, -1.3)
1.2, -0.5, 0.8, 2.1, -1.3
ε (epsilon)
γ (gamma)
β (beta)
Compute Normalization
📊 Batch mean (μ)
—
📊 Batch variance (σ²)
—
⚙️ Normalized (x - μ)/√(σ²+ε)
—
🎯 Scaled & shifted (γ·norm+β)
—
📋 Input values
—
🔁 Inference mode
— During training, running mean & variance are updated via exponential moving average. At inference, the
running mean
and
running variance
replace batch statistics. This ensures consistent normalization regardless of batch size.