tx · GrYgFiPFtYBHK5z9HdzqdS27NYqqNRNR7QHf3AxwJu1z

3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY:  -0.01000000 Waves

2024.04.16 23:30 [3065796] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

{
    "type": 13,
    "id": "GrYgFiPFtYBHK5z9HdzqdS27NYqqNRNR7QHf3AxwJu1z",
    "fee": 1000000,
    "feeAssetId": null,
    "timestamp": 1713299337067,
    "version": 2,
    "chainId": 84,
    "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY",
    "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc",
    "proofs": [
        "4xgM47Ng9cNwazp4NCtZTZthXRuUDF6s7eVwR11imeCnbo3QDCMR89CrbGbWNiC18yhZUYB8SgnCA4kFxjsF7x4H"
    ],
    "script": "base64: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",
    "height": 3065796,
    "applicationStatus": "succeeded",
    "spentComplexity": 0
}

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Diff: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
-
let layer1Weights = [[600496, 600732], [414196, 414252]]
4
+
let layer1Weights = [[600496, 600732], [414197, 414252]]
5
5
 
6
6
 
let layer1Biases = [-259050, -635637]
7
7
 
8
-
let layer2Weights = [[832965, -897141]]
8
+
let layer2Weights = [[832966, -897142]]
9
9
 
10
10
 
let layer2Biases = [-381178]
11
11
 
16
16
 
        then -(z)
17
17
 
        else z
18
18
 
    let expPart = fraction(e, base, positiveZ)
19
-
    let sigValue = fraction(base, base, (base + expPart))
19
+
    let sigValue = fraction(base, (base + expPart), base)
20
20
 
    $Tuple2([IntegerEntry((debugPrefix + "positiveZ"), positiveZ), IntegerEntry((debugPrefix + "expPart"), expPart), IntegerEntry((debugPrefix + "sigValue"), sigValue)], sigValue)
21
21
 
    }
22
22
 
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 $t011721218 = sigmoid(sum0, "Layer1N0")
28
-
    let debug0 = $t011721218._1
29
-
    let sig0 = $t011721218._2
30
-
    let $t012231269 = sigmoid(sum1, "Layer1N1")
31
-
    let debug1 = $t012231269._1
32
-
    let sig1 = $t012231269._2
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
33
33
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
34
34
 
    }
35
35
 
36
36
 
37
37
 
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
38
38
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
39
-
    let $t015381584 = sigmoid(sum0, "Layer2N0")
40
-
    let debug0 = $t015381584._1
41
-
    let sig0 = $t015381584._2
42
-
    $Tuple2([sig0], debug0)
39
+
    let $t014331479 = sigmoid(sum0, "Layer2N0")
40
+
    let debug0 = $t014331479._1
41
+
    let sig0 = $t014331479._2
42
+
    $Tuple2(sig0, debug0)
43
43
 
    }
44
44
 
45
45
 
52
52
 
        then 1000000
53
53
 
        else 0
54
54
 
    let inputs = [scaledInput1, scaledInput2]
55
-
    let $t018371935 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
56
-
    let layer1Output = $t018371935._1
57
-
    let debugLayer1 = $t018371935._2
58
-
    let $t019402044 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
59
-
    let layer2Output = $t019402044._1
60
-
    let debugLayer2 = $t019402044._2
61
-
    (([IntegerEntry("result", layer2Output[0])] ++ debugLayer1) ++ debugLayer2)
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)
62
62
 
    }
63
63
 
64
64
 

Full: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
-
let layer1Weights = [[600496, 600732], [414196, 414252]]
4
+
let layer1Weights = [[600496, 600732], [414197, 414252]]
5
5
 
6
6
 
let layer1Biases = [-259050, -635637]
7
7
 
8
-
let layer2Weights = [[832965, -897141]]
8
+
let layer2Weights = [[832966, -897142]]
9
9
 
10
10
 
let layer2Biases = [-381178]
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
-
    let sigValue = fraction(base, base, (base + expPart))
19
+
    let sigValue = fraction(base, (base + expPart), base)
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 $t011721218 = sigmoid(sum0, "Layer1N0")
28
-
    let debug0 = $t011721218._1
29
-
    let sig0 = $t011721218._2
30
-
    let $t012231269 = sigmoid(sum1, "Layer1N1")
31
-
    let debug1 = $t012231269._1
32
-
    let sig1 = $t012231269._2
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
33
33
 
    $Tuple2([sig0, sig1], (debug0 ++ debug1))
34
34
 
    }
35
35
 
36
36
 
37
37
 
func forwardPassLayer2 (input,weights,biases,debugPrefix) = {
38
38
 
    let sum0 = ((fraction(input[0], weights[0][0], 1000000) + fraction(input[1], weights[0][1], 1000000)) + biases[0])
39
-
    let $t015381584 = sigmoid(sum0, "Layer2N0")
40
-
    let debug0 = $t015381584._1
41
-
    let sig0 = $t015381584._2
42
-
    $Tuple2([sig0], debug0)
39
+
    let $t014331479 = sigmoid(sum0, "Layer2N0")
40
+
    let debug0 = $t014331479._1
41
+
    let sig0 = $t014331479._2
42
+
    $Tuple2(sig0, debug0)
43
43
 
    }
44
44
 
45
45
 
46
46
 
@Callable(i)
47
47
 
func predict (input1,input2) = {
48
48
 
    let scaledInput1 = if ((input1 == 1))
49
49
 
        then 1000000
50
50
 
        else 0
51
51
 
    let scaledInput2 = if ((input2 == 1))
52
52
 
        then 1000000
53
53
 
        else 0
54
54
 
    let inputs = [scaledInput1, scaledInput2]
55
-
    let $t018371935 = forwardPassLayer1(inputs, layer1Weights, layer1Biases, "Layer1")
56
-
    let layer1Output = $t018371935._1
57
-
    let debugLayer1 = $t018371935._2
58
-
    let $t019402044 = forwardPassLayer2(layer1Output, layer2Weights, layer2Biases, "Layer2")
59
-
    let layer2Output = $t019402044._1
60
-
    let debugLayer2 = $t019402044._2
61
-
    (([IntegerEntry("result", layer2Output[0])] ++ debugLayer1) ++ debugLayer2)
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)
62
62
 
    }
63
63
 
64
64
 

github/deemru/w8io/169f3d6 
31.03 ms ◑