net = NetGraph[
  {
   50,
   50,
   CatenateLayer[],
   ReshapeLayer[{2, 50}],
   NetPairEmbeddingOperator[NetChain[{10, Ramp, 2(*embedding dimension*)}]],
   {2, SoftmaxLayer[]},
   {2, SoftmaxLayer[]},
   ContrastiveLossLayer[(*margin*)]
   },
  {
   NetPort["Input1"] -> 1 -> 6,
   NetPort["Input2"] -> 2 -> 7,
   {1, 2} -> 3 -> 4 -> 5 -> 8
   },
  "Input1" -> 10,
  "Input2" -> 10,
  "Output1" -> NetDecoder[{"Class", {0, 1}}],
  "Output2" -> NetDecoder[{"Class", {0, 1}}]
  ]

net = NetGraph[
  {
   50,
   50,
   CatenateLayer[],
   ReshapeLayer[{2, 50}],
   NetPairEmbeddingOperator[NetChain[{10, Ramp, 2(*embedding dimension*)}]],
   {2, SoftmaxLayer[]},
   {2, SoftmaxLayer[]},
   ContrastiveLossLayer[(*margin*)]
   },
  {
   NetPort["Input1"] -> 1 -> 6,
   NetPort["Input2"] -> 2 -> 7,
   {1, 2} -> 3 -> 4 -> 5 -> 8
   },
  "Input1" -> 10,
  "Input2" -> 10,
  "Output1" -> NetDecoder[{"Class", {0, 1}}],
  "Output2" -> NetDecoder[{"Class", {0, 1}}]
  ]

sampler[n_] := Block[
  {r},
  r = Table[RandomSample[Range[1000], 2], n];
  <|
   "Input1" -> X[[r[[;; , 1]]]],
   "Input2" -> X[[r[[;; , 2]]]],
   "Output1" -> Y[[r[[;; , 1]]]],
   "Output2" -> Y[[r[[;; , 2]]]],
   "Target" -> RandomChoice[{True, False}, n]
   |>
  ]

sampler[#BatchSize] &@<|"BatchSize" -> 2|>
netT = NetTrain[net, sampler[#BatchSize] &, BatchSize -> 2, MaxTrainingRounds -> 50]

classifier = NetGraph[
  {
   Take[netT, {1, 6}],
   Take[netT, {2, 7}],
   ThreadingLayer[(#1 + #2)/2 &]
   },
  {
   {1, 2} -> 3
   },
  "Output" -> NetDecoder[{"Class", {0, 1}}]
  ]

classifier = NetGraph[
  {
   Take[netT, {1, 6}],
   Take[netT, {2, 7}],
   ThreadingLayer[(#1 + #2)/2 &]
   },
  {
   {1, 2} -> 3
   },
  "Output" -> NetDecoder[{"Class", {0, 1}}]
  ]

emb1 = NetChain[
  {
   Take[netT, {1, 1}],
   NetExtract[netT, 5][["Net"]]
   }
  ]

nf1 = Nearest[emb1@X -> Range[n]]

emb2 = NetChain[
  {
   Take[netT, {2, 2}],
   NetExtract[netT, 5][["Net"]]
   }
  ];
nf2 = Nearest[emb2@X -> Range[n]];

SeedRandom[0];
data = RandomReal[{-1, 1}, 10];

classifier[<|"Input1" -> data, "Input2" -> data|>, "Probabilities"]

{nf1[emb1@data, 5], nf2[emb2@data, 5]}