tx · 9553vJ12edZJ27jBKnYz9WXzRqroNuR2RTpiimASfPrE 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY: -0.01000000 Waves 2024.05.04 11:59 [3091172] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves
{ "type": 13, "id": "9553vJ12edZJ27jBKnYz9WXzRqroNuR2RTpiimASfPrE", "fee": 1000000, "feeAssetId": null, "timestamp": 1714813180191, "version": 2, "chainId": 84, "sender": "3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY", "senderPublicKey": "2AWdnJuBMzufXSjTvzVcawBQQhnhF1iXR6QNVgwn33oc", "proofs": [ "4JHaZa9YoccNjw8ZAGKAQJHWYiihb8CwXdM7dwCpU7ggdAp8mZY9bhm9dmaQgrReUGYFgxcwpGbbemyaV9tZLudw" ], "script": "base64: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", "height": 3091172, "applicationStatus": "succeeded", "spentComplexity": 0 } View: original | compacted Prev: 8W4DpmGZprxE3grV984a9nnSJ6PF59WrUbFKJyDihWDj Next: FZharDfu9u3yURdpNVPoqVoSWuAJo4VBm5dPLS1sNtbM Diff:
Old | New | Differences | |
---|---|---|---|
14 | 14 | else 0 | |
15 | 15 | ||
16 | 16 | ||
17 | - | func sigmoid_approx (x) = if ((- | |
18 | - | then | |
19 | - | else if ((- | |
17 | + | func sigmoid_approx (x) = if ((-4000 > x)) | |
18 | + | then 0 | |
19 | + | else if ((-2000 > x)) | |
20 | 20 | then 1000 | |
21 | - | else if ((- | |
21 | + | else if ((-1000 > x)) | |
22 | 22 | then 2000 | |
23 | 23 | else if ((0 > x)) | |
24 | 24 | then 3000 | |
25 | - | else if ((2000 > x)) | |
26 | - | then 5000 | |
27 | - | else if ((4000 > x)) | |
28 | - | then 7000 | |
29 | - | else if ((6000 > x)) | |
30 | - | then 8000 | |
31 | - | else if ((8000 > x)) | |
32 | - | then 9000 | |
33 | - | else 9500 | |
25 | + | else if ((1000 > x)) | |
26 | + | then 7000 | |
27 | + | else if ((2000 > x)) | |
28 | + | then 8000 | |
29 | + | else if ((4000 > x)) | |
30 | + | then 9000 | |
31 | + | else 10000 | |
34 | 32 | ||
35 | 33 | ||
36 | 34 | func dotProduct (v1,v2) = { | |
55 | 53 | @Callable(i) | |
56 | 54 | func predict (input1,input2) = { | |
57 | 55 | let inputs = [input1, input2] | |
58 | - | let $ | |
59 | - | let prediction = $ | |
60 | - | let dp1 = $ | |
61 | - | let dp2 = $ | |
62 | - | let layer1Result1 = $ | |
63 | - | let layer1Result2 = $ | |
64 | - | let dp3 = $ | |
56 | + | let $t015381621 = feedforward(inputs) | |
57 | + | let prediction = $t015381621._1 | |
58 | + | let dp1 = $t015381621._2 | |
59 | + | let dp2 = $t015381621._3 | |
60 | + | let layer1Result1 = $t015381621._4 | |
61 | + | let layer1Result2 = $t015381621._5 | |
62 | + | let dp3 = $t015381621._6 | |
65 | 63 | [IntegerEntry("prediction", prediction), IntegerEntry("dotProduct1", dp1), IntegerEntry("dotProduct2", dp2), IntegerEntry("layer1Result1", layer1Result1), IntegerEntry("layer1Result2", layer1Result2), IntegerEntry("dotProduct3", dp3)] | |
66 | 64 | } | |
67 | 65 |
Old | New | Differences | |
---|---|---|---|
1 | 1 | {-# STDLIB_VERSION 5 #-} | |
2 | 2 | {-# SCRIPT_TYPE ACCOUNT #-} | |
3 | 3 | {-# CONTENT_TYPE DAPP #-} | |
4 | 4 | let layer1Weights = [[600496, 600733], [414197, 414253]] | |
5 | 5 | ||
6 | 6 | let layer1Biases = [-259050, -635637] | |
7 | 7 | ||
8 | 8 | let layer2Weights = [[832966, -897141]] | |
9 | 9 | ||
10 | 10 | let layer2Biases = [-381179] | |
11 | 11 | ||
12 | 12 | func relu (x) = if ((x > 0)) | |
13 | 13 | then x | |
14 | 14 | else 0 | |
15 | 15 | ||
16 | 16 | ||
17 | - | func sigmoid_approx (x) = if ((- | |
18 | - | then | |
19 | - | else if ((- | |
17 | + | func sigmoid_approx (x) = if ((-4000 > x)) | |
18 | + | then 0 | |
19 | + | else if ((-2000 > x)) | |
20 | 20 | then 1000 | |
21 | - | else if ((- | |
21 | + | else if ((-1000 > x)) | |
22 | 22 | then 2000 | |
23 | 23 | else if ((0 > x)) | |
24 | 24 | then 3000 | |
25 | - | else if ((2000 > x)) | |
26 | - | then 5000 | |
27 | - | else if ((4000 > x)) | |
28 | - | then 7000 | |
29 | - | else if ((6000 > x)) | |
30 | - | then 8000 | |
31 | - | else if ((8000 > x)) | |
32 | - | then 9000 | |
33 | - | else 9500 | |
25 | + | else if ((1000 > x)) | |
26 | + | then 7000 | |
27 | + | else if ((2000 > x)) | |
28 | + | then 8000 | |
29 | + | else if ((4000 > x)) | |
30 | + | then 9000 | |
31 | + | else 10000 | |
34 | 32 | ||
35 | 33 | ||
36 | 34 | func dotProduct (v1,v2) = { | |
37 | 35 | let sum1 = ((v1[0] * v2[0]) / 10000) | |
38 | 36 | let sum2 = ((v1[1] * v2[1]) / 10000) | |
39 | 37 | (sum1 + sum2) | |
40 | 38 | } | |
41 | 39 | ||
42 | 40 | ||
43 | 41 | func feedforward (inputs) = { | |
44 | 42 | let dp1 = dotProduct(inputs, layer1Weights[0]) | |
45 | 43 | let dp2 = dotProduct(inputs, layer1Weights[1]) | |
46 | 44 | let layer1Result1 = sigmoid_approx((dp1 + layer1Biases[0])) | |
47 | 45 | let layer1Result2 = sigmoid_approx((dp2 + layer1Biases[1])) | |
48 | 46 | let layer2Inputs = [layer1Result1, layer1Result2] | |
49 | 47 | let dp3 = dotProduct(layer2Inputs, layer2Weights[0]) | |
50 | 48 | let output = sigmoid_approx((dp3 + layer2Biases[0])) | |
51 | 49 | $Tuple6(output, dp1, dp2, layer1Result1, layer1Result2, dp3) | |
52 | 50 | } | |
53 | 51 | ||
54 | 52 | ||
55 | 53 | @Callable(i) | |
56 | 54 | func predict (input1,input2) = { | |
57 | 55 | let inputs = [input1, input2] | |
58 | - | let $ | |
59 | - | let prediction = $ | |
60 | - | let dp1 = $ | |
61 | - | let dp2 = $ | |
62 | - | let layer1Result1 = $ | |
63 | - | let layer1Result2 = $ | |
64 | - | let dp3 = $ | |
56 | + | let $t015381621 = feedforward(inputs) | |
57 | + | let prediction = $t015381621._1 | |
58 | + | let dp1 = $t015381621._2 | |
59 | + | let dp2 = $t015381621._3 | |
60 | + | let layer1Result1 = $t015381621._4 | |
61 | + | let layer1Result2 = $t015381621._5 | |
62 | + | let dp3 = $t015381621._6 | |
65 | 63 | [IntegerEntry("prediction", prediction), IntegerEntry("dotProduct1", dp1), IntegerEntry("dotProduct2", dp2), IntegerEntry("layer1Result1", layer1Result1), IntegerEntry("layer1Result2", layer1Result2), IntegerEntry("dotProduct3", dp3)] | |
66 | 64 | } | |
67 | 65 | ||
68 | 66 |
github/deemru/w8io/6500d08 29.41 ms ◑