tx · 8hzRtKV4pz9FhxiF6znTWecbvi8wMaitg8Z4WWFgBEMK

3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY:  -0.01000000 Waves

2024.03.24 15:16 [3032122] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

{
    "type": 13,
    "id": "8hzRtKV4pz9FhxiF6znTWecbvi8wMaitg8Z4WWFgBEMK",
    "fee": 1000000,
    "feeAssetId": null,
    "timestamp": 1711282619468,
    "version": 2,
    "chainId": 84,
    "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY",
    "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc",
    "proofs": [
        "5eYkci6FmwSmVFnQELUmXwEz1RWZszDPkufAMN23LEdcLUVTyjthEbLg2h5bAQE1CWih8gYpW8WFnb8QqhRH99rD"
    ],
    "script": "base64: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",
    "height": 3032122,
    "applicationStatus": "succeeded",
    "spentComplexity": 0
}

View: original | compacted
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Diff: 
Old
New
Differences
24
24
 
func forwardPassLayer1 (input,weights,biases,debugPrefix) = {
25
25
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
26
26
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
27
-
    let $t011901246 = sigmoid(sum0, (debugPrefix + "L1N0"))
28
-
    let debug0 = $t011901246._1
29
-
    let sig0 = $t011901246._2
30
-
    let $t012511307 = sigmoid(sum1, (debugPrefix + "L1N1"))
31
-
    let debug1 = $t012511307._1
32
-
    let sig1 = $t012511307._2
27
+
    let $t011811237 = sigmoid(sum0, (debugPrefix + "L1N0"))
28
+
    let debug0 = $t011811237._1
29
+
    let sig0 = $t011811237._2
30
+
    let $t012421298 = sigmoid(sum1, (debugPrefix + "L1N1"))
31
+
    let debug1 = $t012421298._1
32
+
    let sig1 = $t012421298._2
33
33
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
34
34
 
    }
35
35
 
36
36
 
37
37
 
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
38
-
    let sum = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000)) + biases)
39
-
    let $t015761620 = sigmoid(sum, debugPrefix)
40
-
    let debug = $t015761620._1
41
-
    let sig = $t015761620._2
42
-
    $Tuple2(sig, debug)
38
+
    let sum0 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases)
39
+
    let sum1 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases)
40
+
    let $t016521708 = sigmoid(sum0, (debugPrefix + "L2N0"))
41
+
    let debug0 = $t016521708._1
42
+
    let sig0 = $t016521708._2
43
+
    let $t017131769 = sigmoid(sum1, (debugPrefix + "L2N1"))
44
+
    let debug1 = $t017131769._1
45
+
    let sig1 = $t017131769._2
46
+
    $Tuple2(sig0, (debug0 ++ debug1))
43
47
 
    }
44
48
 
45
49
 
52
56
 
        then 1000000
53
57
 
        else 0
54
58
 
    let inputs = [scaledInput1, scaledInput2]
55
-
    let $t018821980 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
56
-
    let layer1Output = $t018821980._1
57
-
    let debugLayer1 = $t018821980._2
58
-
    let $t019852088 = forwardPassLayer2(layer1Output, [8329656, -8971418], -3811788, "Layer2")
59
-
    let output = $t019852088._1
60
-
    let debugLayerLast = $t019852088._2
61
-
[IntegerEntry("result", output)]
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)
62
66
 
    }
63
67
 
64
68
 

Full: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
4
 
let layer1Weights = [[6004965, 6007324], [4141966, 4142525]]
5
5
 
6
6
 
let layer1Biases = [-2590503, -6356371]
7
7
 
8
8
 
let layer2Weights = [[8329656, -8971418]]
9
9
 
10
10
 
let layer2Biases = [-3811788]
11
11
 
12
12
 
func sigmoid (z,debugPrefix) = {
13
13
 
    let e = 2718281
14
14
 
    let base = 1000000
15
15
 
    let positiveZ = if ((0 > z))
16
16
 
        then -(z)
17
17
 
        else z
18
18
 
    let expPart = fraction(e, base, positiveZ)
19
19
 
    let sigValue = fraction(base, base, (base + expPart))
20
20
 
    $Tuple2([IntegerEntry((debugPrefix + "positiveZ"), positiveZ), IntegerEntry((debugPrefix + "expPart"), expPart), IntegerEntry((debugPrefix + "sigValue"), sigValue)], sigValue)
21
21
 
    }
22
22
 
23
23
 
24
24
 
func forwardPassLayer1 (input,weights,biases,debugPrefix) = {
25
25
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
26
26
 
    let sum1 = ((fraction(input[0], weights[1][0], 1000000) + fraction(input[1], weights[1][1], 1000000)) + biases[1])
27
-
    let $t011901246 = sigmoid(sum0, (debugPrefix + "L1N0"))
28
-
    let debug0 = $t011901246._1
29
-
    let sig0 = $t011901246._2
30
-
    let $t012511307 = sigmoid(sum1, (debugPrefix + "L1N1"))
31
-
    let debug1 = $t012511307._1
32
-
    let sig1 = $t012511307._2
27
+
    let $t011811237 = sigmoid(sum0, (debugPrefix + "L1N0"))
28
+
    let debug0 = $t011811237._1
29
+
    let sig0 = $t011811237._2
30
+
    let $t012421298 = sigmoid(sum1, (debugPrefix + "L1N1"))
31
+
    let debug1 = $t012421298._1
32
+
    let sig1 = $t012421298._2
33
33
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
34
34
 
    }
35
35
 
36
36
 
37
37
 
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
38
-
    let sum = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[0], 1000000)) + biases)
39
-
    let $t015761620 = sigmoid(sum, debugPrefix)
40
-
    let debug = $t015761620._1
41
-
    let sig = $t015761620._2
42
-
    $Tuple2(sig, debug)
38
+
    let sum0 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases)
39
+
    let sum1 = ((fraction(input[0], weights[0], 1000000) + fraction(input[1], weights[1], 1000000)) + biases)
40
+
    let $t016521708 = sigmoid(sum0, (debugPrefix + "L2N0"))
41
+
    let debug0 = $t016521708._1
42
+
    let sig0 = $t016521708._2
43
+
    let $t017131769 = sigmoid(sum1, (debugPrefix + "L2N1"))
44
+
    let debug1 = $t017131769._1
45
+
    let sig1 = $t017131769._2
46
+
    $Tuple2(sig0, (debug0 ++ debug1))
43
47
 
    }
44
48
 
45
49
 
46
50
 
@Callable(i)
47
51
 
func predict (input1,input2) = {
48
52
 
    let scaledInput1 = if ((input1 == 1))
49
53
 
        then 1000000
50
54
 
        else 0
51
55
 
    let scaledInput2 = if ((input2 == 1))
52
56
 
        then 1000000
53
57
 
        else 0
54
58
 
    let inputs = [scaledInput1, scaledInput2]
55
-
    let $t018821980 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
56
-
    let layer1Output = $t018821980._1
57
-
    let debugLayer1 = $t018821980._2
58
-
    let $t019852088 = forwardPassLayer2(layer1Output, [8329656, -8971418], -3811788, "Layer2")
59
-
    let output = $t019852088._1
60
-
    let debugLayerLast = $t019852088._2
61
-
[IntegerEntry("result", output)]
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)
62
66
 
    }
63
67
 
64
68
 

github/deemru/w8io/6500d08 
29.69 ms ◑