2024.04.16 23:30 [3065797] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

{
    "type": 13,
    "id": "63HL2ET9udUcXr31RyWXVSbexg4dmVv2RJVheQd1HjGm",
    "fee": 1000000,
    "feeAssetId": null,
    "timestamp": 1713299503939,
    "version": 2,
    "chainId": 84,
    "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY",
    "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc",
    "proofs": [
        "5djkcFQ8wp8YHeTXssn5irgfBH5NTLyUXyou19PcU1PP4g7kRx6ekvvW4bomCkWTS5iT8TCJ2DiQs6GbwJSFjxoJ"
    ],
    "script": "base64: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",
    "height": 3065797,
    "applicationStatus": "succeeded",
    "spentComplexity": 0
}

View: original | compacted
Prev: GrYgFiPFtYBHK5z9HdzqdS27NYqqNRNR7QHf3AxwJu1z
Next: 2EAsscTWTcXLbZe4WsBMSSeTj11Qf1Abr2c6XurS2kqL

Diff: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
-
let layer1Weights = [[600496, 600732], [414197, 414252]]
4
+
let layer1Weights = [[-927524, 622214], [-920182, -651619], [-152874, 1145040], [-752484, -604481]]
5
5
 
6
-
let layer1Biases = [-259050, -635637]
6
+
let layer1Biases = [-256962, 231253, -475298, 189517]
7
7
 
8
-
let layer2Weights = [[832966, -897142]]
8
+
let layer2Weights = [[-757521, 552333, 658111, 377320], [686102, -570621, -603550, -332354]]
9
9
 
10
-
let layer2Biases = [-381178]
10
+
let layer2Biases = [-316162, 294501]
11
+
12
+
let layer3Weights = [[-893964, 951736]]
13
+
14
+
let layer3Biases = [-19235]
11
15
 
12
16
 
func sigmoid (z,debugPrefix) = {
13
17
 
    let e = 2718281
24
28
 
func forwardPassLayer1 (input,weights,biases,debugPrefix) = {
25
29
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
26
30
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
27
-
    let $t010671113 = sigmoid(sum0, "Layer1N0")
28
-
    let debug0 = $t010671113._1
29
-
    let sig0 = $t010671113._2
30
-
    let $t011181164 = sigmoid(sum1, "Layer1N1")
31
-
    let debug1 = $t011181164._1
32
-
    let sig1 = $t011181164._2
31
+
    let sum2 = ((fraction(input[0], weights[2][0], 1000000) + fraction(input[1], weights[2][1], 1000000)) + biases[2])
32
+
    let sum3 = ((fraction(input[0], weights[3][0], 1000000) + fraction(input[1], weights[3][1], 1000000)) + biases[3])
33
+
    let $t014931539 = sigmoid(sum0, "Layer1N0")
34
+
    let debug0 = $t014931539._1
35
+
    let sig0 = $t014931539._2
36
+
    let $t015441590 = sigmoid(sum1, "Layer1N1")
37
+
    let debug1 = $t015441590._1
38
+
    let sig1 = $t015441590._2
39
+
    let $t015951641 = sigmoid(sum2, "Layer1N2")
40
+
    let debug2 = $t015951641._1
41
+
    let sig2 = $t015951641._2
42
+
    let $t016461692 = sigmoid(sum3, "Layer1N3")
43
+
    let debug3 = $t016461692._1
44
+
    let sig3 = $t016461692._2
45
+
    $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3))
46
+
    }
47
+
48
+
49
+
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
50
+
    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])
51
+
    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])
52
+
    let $t022882334 = sigmoid(sum0, "Layer2N0")
53
+
    let debug0 = $t022882334._1
54
+
    let sig0 = $t022882334._2
55
+
    let $t023392385 = sigmoid(sum1, "Layer2N1")
56
+
    let debug1 = $t023392385._1
57
+
    let sig1 = $t023392385._2
33
58
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
34
59
 
    }
35
60
 
36
61
 
37
-
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
62
+
func forwardPassLayer3 (input,weights,biases,debugPrefix) = {
38
63
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
39
-
    let $t014331479 = sigmoid(sum0, "Layer2N0")
40
-
    let debug0 = $t014331479._1
41
-
    let sig0 = $t014331479._2
64
+
    let $t026542700 = sigmoid(sum0, "Layer3N0")
65
+
    let debug0 = $t026542700._1
66
+
    let sig0 = $t026542700._2
42
67
 
    $Tuple2(sig0, debug0)
43
68
 
    }
44
69
 
52
77
 
        then 1000000
53
78
 
        else 0
54
79
 
    let inputs = [scaledInput1, scaledInput2]
55
-
    let $t017301828 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
56
-
    let layer1Output = $t017301828._1
57
-
    let debugLayer1 = $t017301828._2
58
-
    let $t018331937 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
59
-
    let layer2Output = $t018331937._1
60
-
    let debugLayer2 = $t018331937._2
61
-
    (([IntegerEntry("result", layer2Output)] ++ debugLayer1) ++ debugLayer2)
80
+
    let $t029513049 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
81
+
    let layer1Output = $t029513049._1
82
+
    let debugLayer1 = $t029513049._2
83
+
    let $t030543158 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
84
+
    let layer2Output = $t030543158._1
85
+
    let debugLayer2 = $t030543158._2
86
+
    let $t031633267 = forwardPassLayer3(layer2Output, layer3Weights, layer3Biases, "Layer3")
87
+
    let layer3Output = $t031633267._1
88
+
    let debugLayer3 = $t031633267._2
89
+
    ((([IntegerEntry("result", layer3Output)] ++ debugLayer1) ++ debugLayer2) ++ debugLayer3)
62
90
 
    }
63
91
 
64
92
 

Full: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
-
let layer1Weights = [[600496, 600732], [414197, 414252]]
4
+
let layer1Weights = [[-927524, 622214], [-920182, -651619], [-152874, 1145040], [-752484, -604481]]
5
5
 
6
-
let layer1Biases = [-259050, -635637]
6
+
let layer1Biases = [-256962, 231253, -475298, 189517]
7
7
 
8
-
let layer2Weights = [[832966, -897142]]
8
+
let layer2Weights = [[-757521, 552333, 658111, 377320], [686102, -570621, -603550, -332354]]
9
9
 
10
-
let layer2Biases = [-381178]
10
+
let layer2Biases = [-316162, 294501]
11
+
12
+
let layer3Weights = [[-893964, 951736]]
13
+
14
+
let layer3Biases = [-19235]
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 + expPart), base)
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) = {
25
29
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
26
30
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
27
-
    let $t010671113 = sigmoid(sum0, "Layer1N0")
28
-
    let debug0 = $t010671113._1
29
-
    let sig0 = $t010671113._2
30
-
    let $t011181164 = sigmoid(sum1, "Layer1N1")
31
-
    let debug1 = $t011181164._1
32
-
    let sig1 = $t011181164._2
31
+
    let sum2 = ((fraction(input[0], weights[2][0], 1000000) + fraction(input[1], weights[2][1], 1000000)) + biases[2])
32
+
    let sum3 = ((fraction(input[0], weights[3][0], 1000000) + fraction(input[1], weights[3][1], 1000000)) + biases[3])
33
+
    let $t014931539 = sigmoid(sum0, "Layer1N0")
34
+
    let debug0 = $t014931539._1
35
+
    let sig0 = $t014931539._2
36
+
    let $t015441590 = sigmoid(sum1, "Layer1N1")
37
+
    let debug1 = $t015441590._1
38
+
    let sig1 = $t015441590._2
39
+
    let $t015951641 = sigmoid(sum2, "Layer1N2")
40
+
    let debug2 = $t015951641._1
41
+
    let sig2 = $t015951641._2
42
+
    let $t016461692 = sigmoid(sum3, "Layer1N3")
43
+
    let debug3 = $t016461692._1
44
+
    let sig3 = $t016461692._2
45
+
    $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3))
46
+
    }
47
+
48
+
49
+
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
50
+
    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])
51
+
    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])
52
+
    let $t022882334 = sigmoid(sum0, "Layer2N0")
53
+
    let debug0 = $t022882334._1
54
+
    let sig0 = $t022882334._2
55
+
    let $t023392385 = sigmoid(sum1, "Layer2N1")
56
+
    let debug1 = $t023392385._1
57
+
    let sig1 = $t023392385._2
33
58
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
34
59
 
    }
35
60
 
36
61
 
37
-
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
62
+
func forwardPassLayer3 (input,weights,biases,debugPrefix) = {
38
63
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
39
-
    let $t014331479 = sigmoid(sum0, "Layer2N0")
40
-
    let debug0 = $t014331479._1
41
-
    let sig0 = $t014331479._2
64
+
    let $t026542700 = sigmoid(sum0, "Layer3N0")
65
+
    let debug0 = $t026542700._1
66
+
    let sig0 = $t026542700._2
42
67
 
    $Tuple2(sig0, debug0)
43
68
 
    }
44
69
 
45
70
 
46
71
 
@Callable(i)
47
72
 
func predict (input1,input2) = {
48
73
 
    let scaledInput1 = if ((input1 == 1))
49
74
 
        then 1000000
50
75
 
        else 0
51
76
 
    let scaledInput2 = if ((input2 == 1))
52
77
 
        then 1000000
53
78
 
        else 0
54
79
 
    let inputs = [scaledInput1, scaledInput2]
55
-
    let $t017301828 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
56
-
    let layer1Output = $t017301828._1
57
-
    let debugLayer1 = $t017301828._2
58
-
    let $t018331937 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
59
-
    let layer2Output = $t018331937._1
60
-
    let debugLayer2 = $t018331937._2
61
-
    (([IntegerEntry("result", layer2Output)] ++ debugLayer1) ++ debugLayer2)
80
+
    let $t029513049 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
81
+
    let layer1Output = $t029513049._1
82
+
    let debugLayer1 = $t029513049._2
83
+
    let $t030543158 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
84
+
    let layer2Output = $t030543158._1
85
+
    let debugLayer2 = $t030543158._2
86
+
    let $t031633267 = forwardPassLayer3(layer2Output, layer3Weights, layer3Biases, "Layer3")
87
+
    let layer3Output = $t031633267._1
88
+
    let debugLayer3 = $t031633267._2
89
+
    ((([IntegerEntry("result", layer3Output)] ++ debugLayer1) ++ debugLayer2) ++ debugLayer3)
62
90
 
    }
63
91
 
64
92
 

github/deemru/w8io/786bc32 
36.23 ms ◑