tx · 9o2vqzbv5JjJKboqkHfGhnn2XCjoXwLe8EaH4ffdKaSu

3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY:  -0.01000000 Waves

2024.05.04 12:30 [3091206] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

{
    "type": 13,
    "id": "9o2vqzbv5JjJKboqkHfGhnn2XCjoXwLe8EaH4ffdKaSu",
    "fee": 1000000,
    "feeAssetId": null,
    "timestamp": 1714815027916,
    "version": 2,
    "chainId": 84,
    "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY",
    "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc",
    "proofs": [
        "3nS4NZC6JrJkuNqxqyT8bTpuUVhJ7SmvvsZS6qcEvrVfaKJi5obowRFFekkrktVX9iSznPo69Tt2G13rg9QdQhhU"
    ],
    "script": "base64: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",
    "height": 3091206,
    "applicationStatus": "succeeded",
    "spentComplexity": 0
}

View: original | compacted
Prev: 6sK5SDfsLBqsGfy4qjtYGMKo72xqzbCSDcxVnRpEtrLn
Next: none

Diff: 
Old
New
Differences
43
43
 
    let dp4 = (dotProduct(inputs, layer1Weights[3]) + layer1Biases[3])
44
44
 
    let layer1Results = [relu(dp1), relu(dp2), relu(dp3), relu(dp4)]
45
45
 
    let dpLayer2 = (dotProduct(layer1Results, layer2Weights[0]) + layer2Biases[0])
46
-
    sigmoid_approx(dpLayer2)
46
+
    let output = sigmoid_approx(dpLayer2)
47
+
    $Tuple6(output, dp1, dp2, dp3, dp4, dpLayer2)
47
48
 
    }
48
49
 
49
50
 
50
51
 
@Callable(i)
51
52
 
func predict (input1,input2) = {
52
53
 
    let inputs = [input1, input2]
53
-
    let prediction = feedforward(inputs)
54
-
[IntegerEntry("prediction", prediction)]
54
+
    let $t015731641 = feedforward(inputs)
55
+
    let prediction = $t015731641._1
56
+
    let dp1 = $t015731641._2
57
+
    let dp2 = $t015731641._3
58
+
    let dp3 = $t015731641._4
59
+
    let dp4 = $t015731641._5
60
+
    let dpLayer2 = $t015731641._6
61
+
[IntegerEntry("prediction", prediction), IntegerEntry("dotProduct1", dp1), IntegerEntry("dotProduct2", dp2), IntegerEntry("dotProduct3", dp3), IntegerEntry("dotProduct4", dp4), IntegerEntry("dotProductLayer2", dpLayer2)]
55
62
 
    }
56
63
 
57
64
 

Full: 
Old
New
Differences
1
1
 
{-# STDLIB_VERSION 5 #-}
2
2
 
{-# SCRIPT_TYPE ACCOUNT #-}
3
3
 
{-# CONTENT_TYPE DAPP #-}
4
4
 
let layer1Weights = [[4496, -6718], [36738, -36738], [3517, -3496], [-39880, 39880]]
5
5
 
6
6
 
let layer1Biases = [18719, -1, 29077, 0]
7
7
 
8
8
 
let layer2Weights = [[-11902, 64358, -26901, 48391]]
9
9
 
10
10
 
let layer2Biases = [-6873]
11
11
 
12
12
 
func relu (x) = if ((x > 0))
13
13
 
    then x
14
14
 
    else 0
15
15
 
16
16
 
17
17
 
func sigmoid_approx (x) = if ((-4000 > x))
18
18
 
    then 0
19
19
 
    else if ((-2000 > x))
20
20
 
        then 1000
21
21
 
        else if ((-1000 > x))
22
22
 
            then 2000
23
23
 
            else if ((0 > x))
24
24
 
                then 3000
25
25
 
                else if ((1000 > x))
26
26
 
                    then 5000
27
27
 
                    else if ((2000 > x))
28
28
 
                        then 7000
29
29
 
                        else if ((3000 > x))
30
30
 
                            then 8000
31
31
 
                            else if ((4000 > x))
32
32
 
                                then 9000
33
33
 
                                else 10000
34
34
 
35
35
 
36
36
 
func dotProduct (v1,v2) = (((v1[0] * v2[0]) + (v1[1] * v2[1])) / 10000)
37
37
 
38
38
 
39
39
 
func feedforward (inputs) = {
40
40
 
    let dp1 = (dotProduct(inputs, layer1Weights[0]) + layer1Biases[0])
41
41
 
    let dp2 = (dotProduct(inputs, layer1Weights[1]) + layer1Biases[1])
42
42
 
    let dp3 = (dotProduct(inputs, layer1Weights[2]) + layer1Biases[2])
43
43
 
    let dp4 = (dotProduct(inputs, layer1Weights[3]) + layer1Biases[3])
44
44
 
    let layer1Results = [relu(dp1), relu(dp2), relu(dp3), relu(dp4)]
45
45
 
    let dpLayer2 = (dotProduct(layer1Results, layer2Weights[0]) + layer2Biases[0])
46
-
    sigmoid_approx(dpLayer2)
46
+
    let output = sigmoid_approx(dpLayer2)
47
+
    $Tuple6(output, dp1, dp2, dp3, dp4, dpLayer2)
47
48
 
    }
48
49
 
49
50
 
50
51
 
@Callable(i)
51
52
 
func predict (input1,input2) = {
52
53
 
    let inputs = [input1, input2]
53
-
    let prediction = feedforward(inputs)
54
-
[IntegerEntry("prediction", prediction)]
54
+
    let $t015731641 = feedforward(inputs)
55
+
    let prediction = $t015731641._1
56
+
    let dp1 = $t015731641._2
57
+
    let dp2 = $t015731641._3
58
+
    let dp3 = $t015731641._4
59
+
    let dp4 = $t015731641._5
60
+
    let dpLayer2 = $t015731641._6
61
+
[IntegerEntry("prediction", prediction), IntegerEntry("dotProduct1", dp1), IntegerEntry("dotProduct2", dp2), IntegerEntry("dotProduct3", dp3), IntegerEntry("dotProduct4", dp4), IntegerEntry("dotProductLayer2", dpLayer2)]
55
62
 
    }
56
63
 
57
64
 

github/deemru/w8io/6500d08 
25.76 ms ◑