sample: separate softmax and temperature transforms (#9732)

This commit is contained in:
Parth Sareen 2025-03-13 09:53:27 -07:00 committed by GitHub
parent 4aeb67ef4c
commit 5c0b663969
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
3 changed files with 98 additions and 25 deletions

View File

@ -87,8 +87,8 @@ func (s *Sampler) sample(tokens []token) (token, error) {
// topK also sorts the tokens in descending order of logits
tokens = topK(tokens, s.topK)
// token logit values are updated to probabilities
tokens = temperature(tokens, s.temperature)
tokens = softmax(tokens)
tokens = topP(tokens, s.topP)
tokens = minP(tokens, s.minP)

View File

@ -25,8 +25,18 @@ func (h *tokenHeap) Pop() any {
return x
}
// temperature applies scaling and softmax to the logits
// temperature applies scaling to the logits
func temperature(ts []token, temp float32) []token {
// Ensure temperature clipping near 0 to avoid numerical instability
temp = max(temp, 1e-7)
for i := range ts {
ts[i].value = ts[i].value / temp
}
return ts
}
// softmax applies normalization to the logits
func softmax(ts []token) []token {
// Find max logit for numerical stability
maxLogit := float32(math.Inf(-1))
for _, t := range ts {
@ -35,15 +45,14 @@ func temperature(ts []token, temp float32) []token {
}
}
// Apply temperature and compute exp(x - max)
temp = max(temp, 1e-7)
// Compute exp(x - max)
var sum float32
for i, v := range ts {
ts[i].value = float32(math.Exp(float64((v.value - maxLogit) / temp)))
ts[i].value = float32(math.Exp(float64(v.value - maxLogit)))
sum += ts[i].value
}
// Normalize
// exp(x - max) / sum(exp(x - max))
for i := range ts {
ts[i].value /= sum
}

View File

@ -32,27 +32,83 @@ func compareLogits(t *testing.T, name string, want []float32, got []token) {
}
}
func TestTemperatureAndSoftmax(t *testing.T) {
input := []float32{1, 4, -2, 0}
func TestTemperature(t *testing.T) {
input := []float32{1.0, 4.0, -2.0, 0.0}
got := temperature(toTokens(input), 0.5)
want := []float32{2.0, 8.0, -4.0, 0.0}
compareLogits(t, "temperature(0.5)", want, got)
// Check probabilities sum to 1
var sum float32
for _, token := range got {
sum += token.value
}
if math.Abs(float64(sum-1.0)) > 1e-6 {
t.Errorf("probabilities don't sum to 1: got %f", sum)
got = temperature(toTokens(input), 1.0)
want = []float32{1.0, 4.0, -2.0, 0.0}
compareLogits(t, "temperature(1)", want, got)
got = temperature(toTokens(input), 0.0)
want = []float32{1e7, 4e7, -2e7, 0.0}
compareLogits(t, "temperature(0)", want, got)
}
func TestSoftmax(t *testing.T) {
tests := []struct {
name string
input []float32
expected []float32
}{
{
name: "correctness softmax",
input: []float32{1, -2, 3, 0},
expected: []float32{0.113550, 0.005653, 0.839024, 0.041773},
},
{
name: "normal distribution",
input: []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367},
},
{
name: "single value",
input: []float32{1.0},
},
{
name: "identical values",
input: []float32{0.9, 0.9, 0.9},
},
{
name: "large values",
input: []float32{1000.0, 2000.0, 3000.0},
},
{
name: "small values",
input: []float32{1e-6, 2e-6, 3e-6},
},
{
name: "negative values",
input: []float32{-1.0, -2.0, -3.0},
},
{
name: "mixed values",
input: []float32{-100.0, 0.0, 100.0},
},
}
got = temperature(toTokens(input), 1)
// Check probabilities sum to 1
sum = 0.0
for _, token := range got {
sum += token.value
}
if math.Abs(float64(sum-1.0)) > 1e-6 {
t.Errorf("probabilities don't sum to 1: got %f", sum)
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := softmax(toTokens(tt.input))
if tt.expected != nil {
compareLogits(t, tt.name, tt.expected, got)
return
}
// Check probabilities sum to 1
var sum float32
for _, token := range got {
sum += token.value
if token.value < 0 || token.value > 1 {
t.Errorf("probability out of range [0,1]: got %f", token.value)
}
}
if math.Abs(float64(sum-1.0)) > 1e-6 {
t.Errorf("probabilities don't sum to 1: got %f", sum)
}
})
}
}
@ -97,7 +153,7 @@ func TestTopP(t *testing.T) {
tokens := toTokens(input)
// First apply temperature and softmax to get probabilities
tokens = temperature(tokens, 1)
tokens = softmax(tokens)
tokens = topK(tokens, 20)
// Then apply topP
@ -115,7 +171,7 @@ func TestMinP(t *testing.T) {
tokens := toTokens(input)
// First apply temperature and softmax
tokens = temperature(tokens, 1)
tokens = softmax(tokens)
// Then apply minP
got := minP(tokens, 0.2)
@ -163,6 +219,14 @@ func BenchmarkTransforms(b *testing.B) {
}
})
b.Run("Softmax", func(b *testing.B) {
b.ResetTimer()
for b.Loop() {
copy(tokensCopy, tokens)
softmax(tokensCopy)
}
})
b.Run("TopK", func(b *testing.B) {
b.ResetTimer()
for b.Loop() {