tx · Beo3A1x3YgpPfTYBjQjGUY9Ek7vP9ChQnZaMxR8pStbe

3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY:  -0.01000000 Waves

2024.05.28 01:02 [3124976] smart account 3N3n75UqB8G1GKmXFr4zPhKCjGcqJPRSuJY > SELF 0.00000000 Waves

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OldNewDifferences
2929 else (5000 + (input / 2))
3030
3131
32-func sigmoid_activation_1 (inputs) = [sigmoid(inputs[0]), sigmoid(inputs[1])]
33-
34-
35-func sigmoid_activation_2 (inputs) = [sigmoid(inputs[0])]
32+func sigmoid_activation (inputs,num_outputs) = [sigmoid(inputs[0]), sigmoid(inputs[1])]
3633
3734
3835 @Callable(i)
4138 let x2_scaled = (x2 * 10000)
4239 let inputs = [x1_scaled, x2_scaled]
4340 let z1 = linear_forward_1(inputs, weights_layer_1, biases_layer_1)
44- let a1 = sigmoid_activation_1(z1)
41+ let a1 = sigmoid_activation(z1, 2)
4542 let z2 = linear_forward_2(a1, weights_layer_2, biases_layer_2)
46- let a2 = sigmoid_activation_2(z2)
43+ let a2 = sigmoid_activation(z2, 1)
4744 let results = [a2[0]]
48- let result_entries = [IntegerEntry("result", results[0])]
4945 let debug_outputs = nil
50- $Tuple2(debug_outputs, result_entries)
46+ $Tuple2(debug_outputs, results)
5147 }
5248
5349
Full:
OldNewDifferences
11 {-# STDLIB_VERSION 7 #-}
22 {-# SCRIPT_TYPE ACCOUNT #-}
33 {-# CONTENT_TYPE DAPP #-}
44 let weights_layer_1 = [[60049, 60073], [41419, 41425]]
55
66 let biases_layer_1 = [-25905, -63563]
77
88 let weights_layer_2 = [[83296, -89714]]
99
1010 let biases_layer_2 = [-38117]
1111
1212 func linear_forward_1 (input,weights,biases) = {
1313 let weighted_sum1 = ((((input[0] * weights[0][0]) + (input[1] * weights[0][1])) / 10000) + biases[0])
1414 let weighted_sum2 = ((((input[0] * weights[1][0]) + (input[1] * weights[1][1])) / 10000) + biases[1])
1515 [weighted_sum1, weighted_sum2]
1616 }
1717
1818
1919 func linear_forward_2 (input,weights,biases) = {
2020 let weighted_sum1 = ((((input[0] * weights[0][0]) + (input[1] * weights[0][1])) / 10000) + biases[0])
2121 [weighted_sum1]
2222 }
2323
2424
2525 func sigmoid (input) = if ((-10000 > input))
2626 then 0
2727 else if ((input > 10000))
2828 then 10000
2929 else (5000 + (input / 2))
3030
3131
32-func sigmoid_activation_1 (inputs) = [sigmoid(inputs[0]), sigmoid(inputs[1])]
33-
34-
35-func sigmoid_activation_2 (inputs) = [sigmoid(inputs[0])]
32+func sigmoid_activation (inputs,num_outputs) = [sigmoid(inputs[0]), sigmoid(inputs[1])]
3633
3734
3835 @Callable(i)
3936 func predict (x1,x2) = {
4037 let x1_scaled = (x1 * 10000)
4138 let x2_scaled = (x2 * 10000)
4239 let inputs = [x1_scaled, x2_scaled]
4340 let z1 = linear_forward_1(inputs, weights_layer_1, biases_layer_1)
44- let a1 = sigmoid_activation_1(z1)
41+ let a1 = sigmoid_activation(z1, 2)
4542 let z2 = linear_forward_2(a1, weights_layer_2, biases_layer_2)
46- let a2 = sigmoid_activation_2(z2)
43+ let a2 = sigmoid_activation(z2, 1)
4744 let results = [a2[0]]
48- let result_entries = [IntegerEntry("result", results[0])]
4945 let debug_outputs = nil
50- $Tuple2(debug_outputs, result_entries)
46+ $Tuple2(debug_outputs, results)
5147 }
5248
5349

github/deemru/w8io/169f3d6 
24.48 ms