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ConsciousnessLearn · Explore · Joseph Anady

Gaussian error linear unit

GELU multiplies x by the standard normal cumulative probability at x. The function implements it with erf, giving a smooth activation that attenuates many negative values and approaches x for large positive values. The Φ in this formula is a Gaussian CDF, not the…

Implementation mathematicsSource recovered; runtime not executed
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gh-eq-0420143023a3d934source-comment-equation
GELU(x)=x⋅Φ(x)whereΦistheCDFofN(0,1)GELU(x) = x · Φ(x) where Φ is the CDF of N(0,1)

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GELU multiplies x by the standard normal cumulative probability at x. The function implements it with erf, giving a smooth activation that attenuates many negative values and approaches x for large positive values. The Φ in this formula is a Gaussian CDF, not the project’s unity score or an IIT quantity.

Terms & definitions

TermMeaning in this source
x

Activation input

Phi

Standard normal cumulative distribution function

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Original context

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		result[i] = (v-mean)/std*gamma + beta
	}

	return result
}

// GELU computes Gaussian Error Linear Unit
// GELU(x) = x · Φ(x) where Φ is the CDF of N(0,1)
func GELU(x float64) float64 {
	return 0.5 * x * (1.0 + math.Erf(x/math.Sqrt(2.0)))
}

// SwiGLU computes SwiGLU activation
// SwiGLU(x, W, V, b, c) = Swish(xW + b) ⊗ (xV + c)
func SwiGLU(x []float64, gate, linear []float64) []float64 {
	n := len(x)
	if n == 0 || len(gate) != n || len(linear) != n {
		return x
Exact original notation
GELU(x) = x · Φ(x) where Φ is the CDF of N(0,1)

Related builds

Sources & provenance

01
Go mathematical helpers
Lines 493–493 · 33aa84f2aa61
02
Go mathematical helpers
Lines 493–493 · 33aa84f2aa61

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