tx · AzkepTgdsr4fYGk5ZLwJnFd387drQyDzUAC8hQq6gM1g

3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY:  -0.01000000 Waves

2024.03.23 17:18 [3030813] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

{
    "type": 13,
    "id": "AzkepTgdsr4fYGk5ZLwJnFd387drQyDzUAC8hQq6gM1g",
    "fee": 1000000,
    "feeAssetId": null,
    "timestamp": 1711203534191,
    "version": 2,
    "chainId": 84,
    "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY",
    "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc",
    "proofs": [
        "TVsaYF9XZs3hLmjrjkHLTu1awArP5WZhJ7vf4c5npvFYegmiFnUxXfCiBNvCQ4GW7eAMTYBC9RerHrpqnCZMX1H"
    ],
    "script": "base64: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    "height": 3030813,
    "applicationStatus": "succeeded",
    "spentComplexity": 0
}

View: original | compacted
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Diff: 
Old
New
Differences
13
13
 
14
14
 
let layer3Biases = [-192349]
15
15
 
16
-
func sigmoid (z) = {
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
-
    fraction(base, base, (base + expPart))
23
+
    let sigValue = fraction(base, base, (base + expPart))
24
+
    $Tuple2([IntegerEntry((debugPrefix + "positiveZ"), positiveZ), IntegerEntry((debugPrefix + "expPart"), expPart), IntegerEntry((debugPrefix + "sigValue"), sigValue)], sigValue)
24
25
 
    }
25
26
 
26
27
 
27
-
func forwardPassLayer1 (input,weights,biases) = {
28
+
func forwardPassLayer1 (input,weights,biases,debugPrefix) = {
28
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])
29
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])
30
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])
31
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])
32
-
    let sig0 = sigmoid(sum0)
33
-
    let sig1 = sigmoid(sum1)
34
-
    let sig2 = sigmoid(sum2)
35
-
    let sig3 = sigmoid(sum3)
36
-
[sig0, sig1, sig2, sig3]
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
45
+
    $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3))
37
46
 
    }
38
47
 
39
48
 
40
-
func forwardPassLayer2 (input,weights,biases) = {
49
+
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
41
50
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
42
51
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
43
-
    let sig0 = sigmoid(sum0)
44
-
    let sig1 = sigmoid(sum1)
45
-
[sig0, sig1]
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
58
+
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
46
59
 
    }
47
60
 
48
61
 
49
-
func forwardPassLayer3 (input,weights,bias) = {
62
+
func forwardPassLayer3 (input,weights,bias,debugPrefix) = {
50
63
 
    let dotProduct = (fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000))
51
64
 
    let sum = (dotProduct + bias)
52
-
    sigmoid(sum)
65
+
    sigmoid(sum, debugPrefix)
53
66
 
    }
54
67
 
55
68
 
56
69
 
@Callable(i)
57
-
func predict_three (input1,input2) = {
70
+
func predict (input1,input2) = {
58
71
 
    let scaledInput1 = if ((input1 == 1))
59
72
 
        then 1000000
60
73
 
        else 0
62
75
 
        then 1000000
63
76
 
        else 0
64
77
 
    let inputs = [scaledInput1, scaledInput2]
65
-
    let layer1Output = forwardPassLayer1(inputs, layer1Weights, layer1Biases)
66
-
    let layer2Output = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases)
67
-
    let output = forwardPassLayer3(layer2Output, [-8939640, 9517362], -192349)
68
-
[IntegerEntry("result", output)]
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)]
69
88
 
    }
70
89
 
71
90
 

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
-
func sigmoid (z) = {
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
-
    fraction(base, base, (base + expPart))
23
+
    let sigValue = fraction(base, base, (base + expPart))
24
+
    $Tuple2([IntegerEntry((debugPrefix + "positiveZ"), positiveZ), IntegerEntry((debugPrefix + "expPart"), expPart), IntegerEntry((debugPrefix + "sigValue"), sigValue)], sigValue)
24
25
 
    }
25
26
 
26
27
 
27
-
func forwardPassLayer1 (input,weights,biases) = {
28
+
func forwardPassLayer1 (input,weights,biases,debugPrefix) = {
28
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])
29
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])
30
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])
31
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])
32
-
    let sig0 = sigmoid(sum0)
33
-
    let sig1 = sigmoid(sum1)
34
-
    let sig2 = sigmoid(sum2)
35
-
    let sig3 = sigmoid(sum3)
36
-
[sig0, sig1, sig2, sig3]
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
45
+
    $Tuple2([sig0, sig1, sig2, sig3], (((debug0 ++ debug1) ++ debug2) ++ debug3))
37
46
 
    }
38
47
 
39
48
 
40
-
func forwardPassLayer2 (input,weights,biases) = {
49
+
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
41
50
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
42
51
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
43
-
    let sig0 = sigmoid(sum0)
44
-
    let sig1 = sigmoid(sum1)
45
-
[sig0, sig1]
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
58
+
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
46
59
 
    }
47
60
 
48
61
 
49
-
func forwardPassLayer3 (input,weights,bias) = {
62
+
func forwardPassLayer3 (input,weights,bias,debugPrefix) = {
50
63
 
    let dotProduct = (fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000))
51
64
 
    let sum = (dotProduct + bias)
52
-
    sigmoid(sum)
65
+
    sigmoid(sum, debugPrefix)
53
66
 
    }
54
67
 
55
68
 
56
69
 
@Callable(i)
57
-
func predict_three (input1,input2) = {
70
+
func predict (input1,input2) = {
58
71
 
    let scaledInput1 = if ((input1 == 1))
59
72
 
        then 1000000
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73
 
        else 0
61
74
 
    let scaledInput2 = if ((input2 == 1))
62
75
 
        then 1000000
63
76
 
        else 0
64
77
 
    let inputs = [scaledInput1, scaledInput2]
65
-
    let layer1Output = forwardPassLayer1(inputs, layer1Weights, layer1Biases)
66
-
    let layer2Output = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases)
67
-
    let output = forwardPassLayer3(layer2Output, [-8939640, 9517362], -192349)
68
-
[IntegerEntry("result", output)]
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)]
69
88
 
    }
70
89
 
71
90
 

github/deemru/w8io/6500d08 
25.16 ms ◑