How to implement Masked Softmax?
3
$begingroup$
input = {1, 2, 3};
mask = {1, 0, 1}
Classic Softmax:
SoftmaxLayer@input
{0.0900306, 0.244728, 0.665241}
Masked Softmax is something like this:
SoftmaxLayer@Pick[input, mask, 1]
{0.119203, 0.880797}
But zeros must be preserved:
{0.119203, 0., 0.880797}
machine-learning neural-networks
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
add a comment |
3
$begingroup$
input = {1, 2, 3};
mask = {1, 0, 1}
Classic Softmax:
SoftmaxLayer@input
{0.0900306, 0.244728, 0.665241}
Masked Softmax is something like this:
SoftmaxLayer@Pick[input, mask, 1]
{0.119203, 0.880797}
But zeros must be preserved:
{0.119203, 0., 0.880797}
machine-learning neural-networks
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
add a comment |
3
3
3
$begingroup$
input = {1, 2, 3};
mask = {1, 0, 1}
Classic Softmax:
SoftmaxLayer@input
{0.0900306, 0.244728, 0.665241}
Masked Softmax is something like this:
SoftmaxLayer@Pick[input, mask, 1]
{0.119203, 0.880797}
But zeros must be preserved:
{0.119203, 0., 0.880797}
machine-learning neural-networks
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
input = {1, 2, 3};
mask = {1, 0, 1}
Classic Softmax:
SoftmaxLayer@input
{0.0900306, 0.244728, 0.665241}
Masked Softmax is something like this:
SoftmaxLayer@Pick[input, mask, 1]
{0.119203, 0.880797}
But zeros must be preserved:
{0.119203, 0., 0.880797}
machine-learning neural-networks
machine-learning neural-networks
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
asked 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
4,9421739
add a comment |
add a comment |
1 Answer
1
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oldest
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2
$begingroup$
MaskedSoftmax = NetGraph[
{
ElementwiseLayer[Exp],
ThreadingLayer[Times],
{SummationLayer, ElementwiseLayer[Max[#, 10^-15] &], ReplicateLayer[Automatic]},
ThreadingLayer[Divide]
},
{
NetPort["Input"] -> 1 -> 2,
NetPort["Mask"] -> 2,
2 -> 3,
{2, 3} -> 4
}
]
MaskedSoftmax[<|"Input" -> {1, 2, 3}, "Mask" -> {1, 0, 1}|>]
{0.119203, 0., 0.880797}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 1, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 1., 0.}}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 0, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 0., 0.}}
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
add a comment |
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1 Answer
1
active
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votes
1 Answer
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active
oldest
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active
oldest
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active
oldest
votes
2
$begingroup$
MaskedSoftmax = NetGraph[
{
ElementwiseLayer[Exp],
ThreadingLayer[Times],
{SummationLayer, ElementwiseLayer[Max[#, 10^-15] &], ReplicateLayer[Automatic]},
ThreadingLayer[Divide]
},
{
NetPort["Input"] -> 1 -> 2,
NetPort["Mask"] -> 2,
2 -> 3,
{2, 3} -> 4
}
]
MaskedSoftmax[<|"Input" -> {1, 2, 3}, "Mask" -> {1, 0, 1}|>]
{0.119203, 0., 0.880797}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 1, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 1., 0.}}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 0, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 0., 0.}}
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
add a comment |
2
$begingroup$
MaskedSoftmax = NetGraph[
{
ElementwiseLayer[Exp],
ThreadingLayer[Times],
{SummationLayer, ElementwiseLayer[Max[#, 10^-15] &], ReplicateLayer[Automatic]},
ThreadingLayer[Divide]
},
{
NetPort["Input"] -> 1 -> 2,
NetPort["Mask"] -> 2,
2 -> 3,
{2, 3} -> 4
}
]
MaskedSoftmax[<|"Input" -> {1, 2, 3}, "Mask" -> {1, 0, 1}|>]
{0.119203, 0., 0.880797}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 1, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 1., 0.}}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 0, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 0., 0.}}
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
add a comment |
2
2
2
$begingroup$
MaskedSoftmax = NetGraph[
{
ElementwiseLayer[Exp],
ThreadingLayer[Times],
{SummationLayer, ElementwiseLayer[Max[#, 10^-15] &], ReplicateLayer[Automatic]},
ThreadingLayer[Divide]
},
{
NetPort["Input"] -> 1 -> 2,
NetPort["Mask"] -> 2,
2 -> 3,
{2, 3} -> 4
}
]
MaskedSoftmax[<|"Input" -> {1, 2, 3}, "Mask" -> {1, 0, 1}|>]
{0.119203, 0., 0.880797}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 1, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 1., 0.}}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 0, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 0., 0.}}
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
$endgroup$
MaskedSoftmax = NetGraph[
{
ElementwiseLayer[Exp],
ThreadingLayer[Times],
{SummationLayer, ElementwiseLayer[Max[#, 10^-15] &], ReplicateLayer[Automatic]},
ThreadingLayer[Divide]
},
{
NetPort["Input"] -> 1 -> 2,
NetPort["Mask"] -> 2,
2 -> 3,
{2, 3} -> 4
}
]
MaskedSoftmax[<|"Input" -> {1, 2, 3}, "Mask" -> {1, 0, 1}|>]
{0.119203, 0., 0.880797}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 1, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 1., 0.}}
MaskedSoftmax[<|"Input" -> {{1, 2, 3}, {1, 2, 3}}, "Mask" -> {{1, 0, 1}, {0, 0, 0}}|>]
{{0.119203, 0., 0.880797}, {0., 0., 0.}}
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
answered 3 hours ago
Alexey GolyshevAlexey Golyshev
4,9421739
4,9421739
add a comment |
add a comment |
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