tx · 5YEessYepbheYsZNiX56NeUXqYCKwLNXVy2zuHJdzinQ

3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY:  -0.01000000 Waves

2024.03.24 13:46 [3032034] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

{
    "type": 13,
    "id": "5YEessYepbheYsZNiX56NeUXqYCKwLNXVy2zuHJdzinQ",
    "fee": 1000000,
    "feeAssetId": null,
    "timestamp": 1711277208398,
    "version": 2,
    "chainId": 84,
    "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY",
    "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc",
    "proofs": [
        "2JTWNaRsz6nBGAjZXp5cwVqCzFMoDzx8fdqkVx2nnAaovoG6hxuPPXVgwG2pmerY9YdHyvsAR65vJfpHB5FWkHzL"
    ],
    "script": "base64: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    "height": 3032034,
    "applicationStatus": "succeeded",
    "spentComplexity": 0
}

View: original | compacted
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Diff: 
Old
New
Differences
30
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
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
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 $t020082064 = sigmoid(sum0, (debugPrefix + "L0N0"))
34
-
    let debug0 = $t020082064._1
35
-
    let sig0 = $t020082064._2
36
-
    let $t020692125 = sigmoid(sum1, (debugPrefix + "L1N0"))
37
-
    let debug1 = $t020692125._1
38
-
    let sig1 = $t020692125._2
39
-
    let $t021302186 = sigmoid(sum2, (debugPrefix + "L2N0"))
40
-
    let debug2 = $t021302186._1
41
-
    let sig2 = $t021302186._2
42
-
    let $t021912247 = sigmoid(sum3, (debugPrefix + "L3N0"))
43
-
    let debug3 = $t021912247._1
44
-
    let sig3 = $t021912247._2
33
+
    let $t019922048 = sigmoid(sum0, (debugPrefix + "L1N0"))
34
+
    let debug0 = $t019922048._1
35
+
    let sig0 = $t019922048._2
36
+
    let $t020532109 = sigmoid(sum1, (debugPrefix + "L1N1"))
37
+
    let debug1 = $t020532109._1
38
+
    let sig1 = $t020532109._2
39
+
    let $t021142170 = sigmoid(sum2, (debugPrefix + "L1N2"))
40
+
    let debug2 = $t021142170._1
41
+
    let sig2 = $t021142170._2
42
+
    let $t021752231 = sigmoid(sum3, (debugPrefix + "L1N3"))
43
+
    let debug3 = $t021752231._1
44
+
    let sig3 = $t021752231._2
45
45
 
    $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3))
46
46
 
    }
47
47
 
49
49
 
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
50
50
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
51
51
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
52
-
    let $t027072763 = sigmoid(sum0, (debugPrefix + "L0N0"))
53
-
    let debug0 = $t027072763._1
54
-
    let sig0 = $t027072763._2
55
-
    let $t027682824 = sigmoid(sum1, (debugPrefix + "L1N0"))
56
-
    let debug1 = $t027682824._1
57
-
    let sig1 = $t027682824._2
52
+
    let $t026692725 = sigmoid(sum0, (debugPrefix + "L2N0"))
53
+
    let debug0 = $t026692725._1
54
+
    let sig0 = $t026692725._2
55
+
    let $t027302786 = sigmoid(sum1, (debugPrefix + "L2N1"))
56
+
    let debug1 = $t027302786._1
57
+
    let sig1 = $t027302786._2
58
58
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
59
59
 
    }
60
60
 
61
61
 
62
-
func forwardPassLayer3 (input,weights,bias,debugPrefix) = {
63
-
    let dotProduct = (fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000))
64
-
    let sum = (dotProduct + bias)
65
-
    sigmoid(sum, debugPrefix)
62
+
func forwardPassLayer3 (input,weights,biases,debugPrefix) = {
63
+
    let sum = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000)) + biases)
64
+
    let $t030553099 = sigmoid(sum, debugPrefix)
65
+
    let debug = $t030553099._1
66
+
    let sig = $t030553099._2
67
+
    $Tuple2(sig, debug)
66
68
 
    }
67
69
 
68
70
 
75
77
 
        then 1000000
76
78
 
        else 0
77
79
 
    let inputs = [scaledInput1, scaledInput2]
78
-
    let $t034293527 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
79
-
    let layer1Output = $t034293527._1
80
-
    let debugLayer1 = $t034293527._2
81
-
    let $t035323636 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
82
-
    let layer2Output = $t035323636._1
83
-
    let debugLayer2 = $t035323636._2
84
-
    let $t036413743 = forwardPassLayer3(layer2Output, [-8939640, 9517362], -192349, "Layer3")
85
-
    let output = $t036413743._1
86
-
    let debugLayerLast = $t036413743._2
87
-
[IntegerEntry("result", output[0].value)]
80
+
    let $t033613459 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
81
+
    let layer1Output = $t033613459._1
82
+
    let debugLayer1 = $t033613459._2
83
+
    let $t034643568 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
84
+
    let layer2Output = $t034643568._1
85
+
    let debugLayer2 = $t034643568._2
86
+
    let $t035733675 = forwardPassLayer3(layer2Output, [-8939640, 9517362], -192349, "Layer3")
87
+
    let output = $t035733675._1
88
+
    let debugLayerLast = $t035733675._2
89
+
[IntegerEntry("result", output)]
88
90
 
    }
89
91
 
90
92
 

Full: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
4
 
let layer1Weights = [[-9275240, 6222139], [-9201827, -6516189], [-1528731, 11450396], [-7524843, -6044814]]
5
5
 
6
6
 
let layer1Biases = [-2569627, 2312524, -4752973, 1895166]
7
7
 
8
8
 
let layer2Weights = [[-7575203, 5523326, 6581110, 3773202], [6861028, -5706216, -6035509, -3323542]]
9
9
 
10
10
 
let layer2Biases = [-3161622, 2945010]
11
11
 
12
12
 
let layer3Weights = [[-8939640, 9517362]]
13
13
 
14
14
 
let layer3Biases = [-192349]
15
15
 
16
16
 
func sigmoid (z,debugPrefix) = {
17
17
 
    let e = 2718281
18
18
 
    let base = 1000000
19
19
 
    let positiveZ = if ((0 > z))
20
20
 
        then -(z)
21
21
 
        else z
22
22
 
    let expPart = fraction(e, base, positiveZ)
23
23
 
    let sigValue = fraction(base, base, (base + expPart))
24
24
 
    $Tuple2([IntegerEntry((debugPrefix + "positiveZ"), positiveZ), IntegerEntry((debugPrefix + "expPart"), expPart), IntegerEntry((debugPrefix + "sigValue"), sigValue)], sigValue)
25
25
 
    }
26
26
 
27
27
 
28
28
 
func forwardPassLayer1 (input,weights,biases,debugPrefix) = {
29
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
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
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
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 $t020082064 = sigmoid(sum0, (debugPrefix + "L0N0"))
34
-
    let debug0 = $t020082064._1
35
-
    let sig0 = $t020082064._2
36
-
    let $t020692125 = sigmoid(sum1, (debugPrefix + "L1N0"))
37
-
    let debug1 = $t020692125._1
38
-
    let sig1 = $t020692125._2
39
-
    let $t021302186 = sigmoid(sum2, (debugPrefix + "L2N0"))
40
-
    let debug2 = $t021302186._1
41
-
    let sig2 = $t021302186._2
42
-
    let $t021912247 = sigmoid(sum3, (debugPrefix + "L3N0"))
43
-
    let debug3 = $t021912247._1
44
-
    let sig3 = $t021912247._2
33
+
    let $t019922048 = sigmoid(sum0, (debugPrefix + "L1N0"))
34
+
    let debug0 = $t019922048._1
35
+
    let sig0 = $t019922048._2
36
+
    let $t020532109 = sigmoid(sum1, (debugPrefix + "L1N1"))
37
+
    let debug1 = $t020532109._1
38
+
    let sig1 = $t020532109._2
39
+
    let $t021142170 = sigmoid(sum2, (debugPrefix + "L1N2"))
40
+
    let debug2 = $t021142170._1
41
+
    let sig2 = $t021142170._2
42
+
    let $t021752231 = sigmoid(sum3, (debugPrefix + "L1N3"))
43
+
    let debug3 = $t021752231._1
44
+
    let sig3 = $t021752231._2
45
45
 
    $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3))
46
46
 
    }
47
47
 
48
48
 
49
49
 
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
50
50
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
51
51
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
52
-
    let $t027072763 = sigmoid(sum0, (debugPrefix + "L0N0"))
53
-
    let debug0 = $t027072763._1
54
-
    let sig0 = $t027072763._2
55
-
    let $t027682824 = sigmoid(sum1, (debugPrefix + "L1N0"))
56
-
    let debug1 = $t027682824._1
57
-
    let sig1 = $t027682824._2
52
+
    let $t026692725 = sigmoid(sum0, (debugPrefix + "L2N0"))
53
+
    let debug0 = $t026692725._1
54
+
    let sig0 = $t026692725._2
55
+
    let $t027302786 = sigmoid(sum1, (debugPrefix + "L2N1"))
56
+
    let debug1 = $t027302786._1
57
+
    let sig1 = $t027302786._2
58
58
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
59
59
 
    }
60
60
 
61
61
 
62
-
func forwardPassLayer3 (input,weights,bias,debugPrefix) = {
63
-
    let dotProduct = (fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000))
64
-
    let sum = (dotProduct + bias)
65
-
    sigmoid(sum, debugPrefix)
62
+
func forwardPassLayer3 (input,weights,biases,debugPrefix) = {
63
+
    let sum = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000)) + biases)
64
+
    let $t030553099 = sigmoid(sum, debugPrefix)
65
+
    let debug = $t030553099._1
66
+
    let sig = $t030553099._2
67
+
    $Tuple2(sig, debug)
66
68
 
    }
67
69
 
68
70
 
69
71
 
@Callable(i)
70
72
 
func predict (input1,input2) = {
71
73
 
    let scaledInput1 = if ((input1 == 1))
72
74
 
        then 1000000
73
75
 
        else 0
74
76
 
    let scaledInput2 = if ((input2 == 1))
75
77
 
        then 1000000
76
78
 
        else 0
77
79
 
    let inputs = [scaledInput1, scaledInput2]
78
-
    let $t034293527 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
79
-
    let layer1Output = $t034293527._1
80
-
    let debugLayer1 = $t034293527._2
81
-
    let $t035323636 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
82
-
    let layer2Output = $t035323636._1
83
-
    let debugLayer2 = $t035323636._2
84
-
    let $t036413743 = forwardPassLayer3(layer2Output, [-8939640, 9517362], -192349, "Layer3")
85
-
    let output = $t036413743._1
86
-
    let debugLayerLast = $t036413743._2
87
-
[IntegerEntry("result", output[0].value)]
80
+
    let $t033613459 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
81
+
    let layer1Output = $t033613459._1
82
+
    let debugLayer1 = $t033613459._2
83
+
    let $t034643568 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
84
+
    let layer2Output = $t034643568._1
85
+
    let debugLayer2 = $t034643568._2
86
+
    let $t035733675 = forwardPassLayer3(layer2Output, [-8939640, 9517362], -192349, "Layer3")
87
+
    let output = $t035733675._1
88
+
    let debugLayerLast = $t035733675._2
89
+
[IntegerEntry("result", output)]
88
90
 
    }
89
91
 
90
92
 

github/deemru/w8io/6500d08 
30.86 ms ◑