32 lines
1015 B
Go
32 lines
1015 B
Go
package tensor
|
|
|
|
// Other tensor methods
|
|
|
|
import (
|
|
"github.com/sugarme/gotch"
|
|
)
|
|
|
|
// CrossEntropyForLogits computes the cross-entropy loss based on some logits and targets.
|
|
func (ts Tensor) CrossEntropyForLogits(targets Tensor) (retVal Tensor) {
|
|
weight := NewTensor()
|
|
reduction := int64(1) // Mean of loss
|
|
ignoreIndex := int64(-100)
|
|
|
|
logSm := ts.MustLogSoftmax(-1, gotch.Float, true)
|
|
return logSm.MustNllLoss(targets, weight, reduction, ignoreIndex, true)
|
|
}
|
|
|
|
// AccuracyForLogits returns the average accuracy for some given logits assuming that
|
|
// targets represent ground-truth.
|
|
func (ts Tensor) AccuracyForLogits(targets Tensor) (retVal Tensor) {
|
|
argmax := ts.MustArgmax(-1, false, true)
|
|
eq1 := argmax.MustEq1(targets, true)
|
|
return eq1.MustTotype(gotch.Float, true).MustMean(gotch.Float, true)
|
|
}
|
|
|
|
func (ts Tensor) MaxPool2DDefault(ksize int64, del bool) (retVal Tensor) {
|
|
return ts.MustMaxPool2d([]int64{ksize, ksize}, []int64{ksize, ksize}, []int64{0, 0}, []int64{1, 1}, false, del)
|
|
}
|
|
|
|
// TODO: continue
|