tx · CXUCY6BFNDgxCV1w6Nf7Fr4orN2Bkr9Wh7ojEq82S228 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY: -0.01000000 Waves 2024.03.24 15:18 [3032123] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves
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"height": 3032123, "applicationStatus": "succeeded", "spentComplexity": 0 } View: original | compacted Prev: 8hzRtKV4pz9FhxiF6znTWecbvi8wMaitg8Z4WWFgBEMK Next: J63xWbm4vHe8K69nUjTn84N9HuR4NGt6i3fVHent4GN Diff:
Old | New | Differences | |
---|---|---|---|
1 | 1 | {-# STDLIB_VERSION 5 #-} | |
2 | 2 | {-# SCRIPT_TYPE ACCOUNT #-} | |
3 | 3 | {-# CONTENT_TYPE DAPP #-} | |
4 | - | let layer1Weights = [[ | |
4 | + | let layer1Weights = [[-9275240, 6222139], [-9201827, -6516189], [-1528731, 11450396], [-7524843, -6044814]] | |
5 | 5 | ||
6 | - | let layer1Biases = [- | |
6 | + | let layer1Biases = [-2569627, 2312524, -4752973, 1895166] | |
7 | 7 | ||
8 | - | let layer2Weights = [[ | |
8 | + | let layer2Weights = [[-7575203, 5523326, 6581110, 3773202], [6861028, -5706216, -6035509, -3323542]] | |
9 | 9 | ||
10 | - | let layer2Biases = [-3811788] | |
10 | + | let layer2Biases = [-3161622, 2945010] | |
11 | + | ||
12 | + | let layer3Weights = [[-8939640, 9517362]] | |
13 | + | ||
14 | + | let layer3Biases = [-192349] | |
11 | 15 | ||
12 | 16 | func sigmoid (z,debugPrefix) = { | |
13 | 17 | let e = 2718281 | |
22 | 26 | ||
23 | 27 | ||
24 | 28 | func forwardPassLayer1 (input,weights,biases,debugPrefix) = { | |
29 | + | let sum0 = ((((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + fraction(input[2], weights[0][2], 1000000)) + fraction(input[3], weights[0][3], 1000000)) + biases[0]) | |
30 | + | let sum1 = ((((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + fraction(input[2], weights[1][2], 1000000)) + fraction(input[3], weights[1][3], 1000000)) + biases[1]) | |
31 | + | let sum2 = ((((fraction(input[0], weights[2][0], 1000000) + fraction(input[1], weights[2][1], 1000000)) + fraction(input[2], weights[2][2], 1000000)) + fraction(input[3], weights[2][3], 1000000)) + biases[2]) | |
32 | + | let sum3 = ((((fraction(input[0], weights[3][0], 1000000) + fraction(input[1], weights[3][1], 1000000)) + fraction(input[2], weights[3][2], 1000000)) + fraction(input[3], weights[3][3], 1000000)) + biases[3]) | |
33 | + | let $t019832039 = sigmoid(sum0, (debugPrefix + "L1N0")) | |
34 | + | let debug0 = $t019832039._1 | |
35 | + | let sig0 = $t019832039._2 | |
36 | + | let $t020442100 = sigmoid(sum1, (debugPrefix + "L1N1")) | |
37 | + | let debug1 = $t020442100._1 | |
38 | + | let sig1 = $t020442100._2 | |
39 | + | let $t021052161 = sigmoid(sum2, (debugPrefix + "L1N2")) | |
40 | + | let debug2 = $t021052161._1 | |
41 | + | let sig2 = $t021052161._2 | |
42 | + | let $t021662222 = sigmoid(sum3, (debugPrefix + "L1N3")) | |
43 | + | let debug3 = $t021662222._1 | |
44 | + | let sig3 = $t021662222._2 | |
45 | + | $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3)) | |
46 | + | } | |
47 | + | ||
48 | + | ||
49 | + | func forwardPassLayer2 (input,weights,biases,debugPrefix) = { | |
25 | 50 | let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0]) | |
26 | 51 | let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1]) | |
27 | - | let $ | |
28 | - | let debug0 = $ | |
29 | - | let sig0 = $ | |
30 | - | let $ | |
31 | - | let debug1 = $ | |
32 | - | let sig1 = $ | |
52 | + | let $t026382694 = sigmoid(sum0, (debugPrefix + "L2N0")) | |
53 | + | let debug0 = $t026382694._1 | |
54 | + | let sig0 = $t026382694._2 | |
55 | + | let $t026992755 = sigmoid(sum1, (debugPrefix + "L2N1")) | |
56 | + | let debug1 = $t026992755._1 | |
57 | + | let sig1 = $t026992755._2 | |
33 | 58 | $Tuple2([sig0, sig1], (debug0 ++ debug1)) | |
34 | 59 | } | |
35 | 60 | ||
36 | 61 | ||
37 | - | func | |
62 | + | func forwardPassLayer3 (input,weights,biases,debugPrefix) = { | |
38 | 63 | let sum0 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases) | |
39 | 64 | let sum1 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases) | |
40 | - | let $ | |
41 | - | let debug0 = $ | |
42 | - | let sig0 = $ | |
43 | - | let $ | |
44 | - | let debug1 = $ | |
45 | - | let sig1 = $ | |
65 | + | let $t031093165 = sigmoid(sum0, (debugPrefix + "L3N0")) | |
66 | + | let debug0 = $t031093165._1 | |
67 | + | let sig0 = $t031093165._2 | |
68 | + | let $t031703226 = sigmoid(sum1, (debugPrefix + "L3N1")) | |
69 | + | let debug1 = $t031703226._1 | |
70 | + | let sig1 = $t031703226._2 | |
46 | 71 | $Tuple2(sig0, (debug0 ++ debug1)) | |
47 | 72 | } | |
48 | 73 | ||
56 | 81 | then 1000000 | |
57 | 82 | else 0 | |
58 | 83 | let inputs = [scaledInput1, scaledInput2] | |
59 | - | let $t020302128 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1") | |
60 | - | let layer1Output = $t020302128._1 | |
61 | - | let debugLayer1 = $t020302128._2 | |
62 | - | let $t021332243 = forwardPassLayer2(layer1Output, layer2Weights[0], layer2Biases[0], "Layer2") | |
63 | - | let layer2Output = $t021332243._1 | |
64 | - | let debugLayer2 = $t021332243._2 | |
65 | - | (([IntegerEntry("result", layer2Output)] ++ debugLayer1) ++ debugLayer2) | |
84 | + | let $t034873585 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1") | |
85 | + | let layer1Output = $t034873585._1 | |
86 | + | let debugLayer1 = $t034873585._2 | |
87 | + | let $t035903694 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2") | |
88 | + | let layer2Output = $t035903694._1 | |
89 | + | let debugLayer2 = $t035903694._2 | |
90 | + | let $t036993809 = forwardPassLayer3(layer2Output, layer3Weights[0], layer3Biases[0], "Layer3") | |
91 | + | let layer3Output = $t036993809._1 | |
92 | + | let debugLayer3 = $t036993809._2 | |
93 | + | ((([IntegerEntry("result", layer3Output)] ++ debugLayer1) ++ debugLayer2) ++ debugLayer3) | |
66 | 94 | } | |
67 | 95 | ||
68 | 96 |
Old | New | Differences | |
---|---|---|---|
1 | 1 | {-# STDLIB_VERSION 5 #-} | |
2 | 2 | {-# SCRIPT_TYPE ACCOUNT #-} | |
3 | 3 | {-# CONTENT_TYPE DAPP #-} | |
4 | - | let layer1Weights = [[ | |
4 | + | let layer1Weights = [[-9275240, 6222139], [-9201827, -6516189], [-1528731, 11450396], [-7524843, -6044814]] | |
5 | 5 | ||
6 | - | let layer1Biases = [- | |
6 | + | let layer1Biases = [-2569627, 2312524, -4752973, 1895166] | |
7 | 7 | ||
8 | - | let layer2Weights = [[ | |
8 | + | let layer2Weights = [[-7575203, 5523326, 6581110, 3773202], [6861028, -5706216, -6035509, -3323542]] | |
9 | 9 | ||
10 | - | let layer2Biases = [-3811788] | |
10 | + | let layer2Biases = [-3161622, 2945010] | |
11 | + | ||
12 | + | let layer3Weights = [[-8939640, 9517362]] | |
13 | + | ||
14 | + | let layer3Biases = [-192349] | |
11 | 15 | ||
12 | 16 | func sigmoid (z,debugPrefix) = { | |
13 | 17 | let e = 2718281 | |
14 | 18 | let base = 1000000 | |
15 | 19 | let positiveZ = if ((0 > z)) | |
16 | 20 | then -(z) | |
17 | 21 | else z | |
18 | 22 | let expPart = fraction(e, base, positiveZ) | |
19 | 23 | let sigValue = fraction(base, base, (base + expPart)) | |
20 | 24 | $Tuple2([IntegerEntry((debugPrefix + "positiveZ"), positiveZ), IntegerEntry((debugPrefix + "expPart"), expPart), IntegerEntry((debugPrefix + "sigValue"), sigValue)], sigValue) | |
21 | 25 | } | |
22 | 26 | ||
23 | 27 | ||
24 | 28 | func forwardPassLayer1 (input,weights,biases,debugPrefix) = { | |
29 | + | let sum0 = ((((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + fraction(input[2], weights[0][2], 1000000)) + fraction(input[3], weights[0][3], 1000000)) + biases[0]) | |
30 | + | let sum1 = ((((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + fraction(input[2], weights[1][2], 1000000)) + fraction(input[3], weights[1][3], 1000000)) + biases[1]) | |
31 | + | let sum2 = ((((fraction(input[0], weights[2][0], 1000000) + fraction(input[1], weights[2][1], 1000000)) + fraction(input[2], weights[2][2], 1000000)) + fraction(input[3], weights[2][3], 1000000)) + biases[2]) | |
32 | + | let sum3 = ((((fraction(input[0], weights[3][0], 1000000) + fraction(input[1], weights[3][1], 1000000)) + fraction(input[2], weights[3][2], 1000000)) + fraction(input[3], weights[3][3], 1000000)) + biases[3]) | |
33 | + | let $t019832039 = sigmoid(sum0, (debugPrefix + "L1N0")) | |
34 | + | let debug0 = $t019832039._1 | |
35 | + | let sig0 = $t019832039._2 | |
36 | + | let $t020442100 = sigmoid(sum1, (debugPrefix + "L1N1")) | |
37 | + | let debug1 = $t020442100._1 | |
38 | + | let sig1 = $t020442100._2 | |
39 | + | let $t021052161 = sigmoid(sum2, (debugPrefix + "L1N2")) | |
40 | + | let debug2 = $t021052161._1 | |
41 | + | let sig2 = $t021052161._2 | |
42 | + | let $t021662222 = sigmoid(sum3, (debugPrefix + "L1N3")) | |
43 | + | let debug3 = $t021662222._1 | |
44 | + | let sig3 = $t021662222._2 | |
45 | + | $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3)) | |
46 | + | } | |
47 | + | ||
48 | + | ||
49 | + | func forwardPassLayer2 (input,weights,biases,debugPrefix) = { | |
25 | 50 | let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0]) | |
26 | 51 | let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1]) | |
27 | - | let $ | |
28 | - | let debug0 = $ | |
29 | - | let sig0 = $ | |
30 | - | let $ | |
31 | - | let debug1 = $ | |
32 | - | let sig1 = $ | |
52 | + | let $t026382694 = sigmoid(sum0, (debugPrefix + "L2N0")) | |
53 | + | let debug0 = $t026382694._1 | |
54 | + | let sig0 = $t026382694._2 | |
55 | + | let $t026992755 = sigmoid(sum1, (debugPrefix + "L2N1")) | |
56 | + | let debug1 = $t026992755._1 | |
57 | + | let sig1 = $t026992755._2 | |
33 | 58 | $Tuple2([sig0, sig1], (debug0 ++ debug1)) | |
34 | 59 | } | |
35 | 60 | ||
36 | 61 | ||
37 | - | func | |
62 | + | func forwardPassLayer3 (input,weights,biases,debugPrefix) = { | |
38 | 63 | let sum0 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases) | |
39 | 64 | let sum1 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases) | |
40 | - | let $ | |
41 | - | let debug0 = $ | |
42 | - | let sig0 = $ | |
43 | - | let $ | |
44 | - | let debug1 = $ | |
45 | - | let sig1 = $ | |
65 | + | let $t031093165 = sigmoid(sum0, (debugPrefix + "L3N0")) | |
66 | + | let debug0 = $t031093165._1 | |
67 | + | let sig0 = $t031093165._2 | |
68 | + | let $t031703226 = sigmoid(sum1, (debugPrefix + "L3N1")) | |
69 | + | let debug1 = $t031703226._1 | |
70 | + | let sig1 = $t031703226._2 | |
46 | 71 | $Tuple2(sig0, (debug0 ++ debug1)) | |
47 | 72 | } | |
48 | 73 | ||
49 | 74 | ||
50 | 75 | @Callable(i) | |
51 | 76 | func predict (input1,input2) = { | |
52 | 77 | let scaledInput1 = if ((input1 == 1)) | |
53 | 78 | then 1000000 | |
54 | 79 | else 0 | |
55 | 80 | let scaledInput2 = if ((input2 == 1)) | |
56 | 81 | then 1000000 | |
57 | 82 | else 0 | |
58 | 83 | let inputs = [scaledInput1, scaledInput2] | |
59 | - | let $t020302128 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1") | |
60 | - | let layer1Output = $t020302128._1 | |
61 | - | let debugLayer1 = $t020302128._2 | |
62 | - | let $t021332243 = forwardPassLayer2(layer1Output, layer2Weights[0], layer2Biases[0], "Layer2") | |
63 | - | let layer2Output = $t021332243._1 | |
64 | - | let debugLayer2 = $t021332243._2 | |
65 | - | (([IntegerEntry("result", layer2Output)] ++ debugLayer1) ++ debugLayer2) | |
84 | + | let $t034873585 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1") | |
85 | + | let layer1Output = $t034873585._1 | |
86 | + | let debugLayer1 = $t034873585._2 | |
87 | + | let $t035903694 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2") | |
88 | + | let layer2Output = $t035903694._1 | |
89 | + | let debugLayer2 = $t035903694._2 | |
90 | + | let $t036993809 = forwardPassLayer3(layer2Output, layer3Weights[0], layer3Biases[0], "Layer3") | |
91 | + | let layer3Output = $t036993809._1 | |
92 | + | let debugLayer3 = $t036993809._2 | |
93 | + | ((([IntegerEntry("result", layer3Output)] ++ debugLayer1) ++ debugLayer2) ++ debugLayer3) | |
66 | 94 | } | |
67 | 95 | ||
68 | 96 |
github/deemru/w8io/c3f4982 27.15 ms ◑