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convent tests
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| const convnet = require('./build/convnet'); | |
| const v = new convnet.Vol(2,2,1); | |
| v.set(0, 0, 0, 1); | |
| v.set(0, 1, 0, 2); | |
| v.set(1, 0, 0, 3); | |
| v.set(1, 1, 0, 4); | |
| // const output = convnet.FullyConnLayer.prototype.forward.call({ | |
| // out_depth: 4, | |
| // num_inputs: 4, | |
| // biases: { w: [0.2, 0.2, 0.2, 0.2] }, | |
| // filters: [ | |
| // { w: [1,2,3,4] }, | |
| // { w: [5,6,7,8] }, | |
| // { w: [9,10,11,12] }, | |
| // { w: [13,14,15,16] }, | |
| // ] | |
| // }, v); | |
| // console.log(output); | |
| const filters = [ | |
| { w: [1,2,3,4], dw: [0,0,0,0] }, | |
| { w: [5,6,7,8], dw: [0,0,0,0] }, | |
| { w: [9,10,11,12], dw: [0,0,0,0] }, | |
| { w: [13,14,15,16], dw: [0,0,0,0] }, | |
| ]; | |
| const biases = { w: [0.2, 0.2, 0.2, 0.2], dw: [0,0,0,0] }; | |
| const output = convnet.FullyConnLayer.prototype.backward.call({ | |
| out_depth: 4, | |
| num_inputs: 4, | |
| in_act: v, | |
| biases: biases, | |
| filters: filters, | |
| out_act: { | |
| dw: [1,2,3,4] | |
| } | |
| }); | |
| // console.log(filters); | |
| // console.log(biases); | |
| console.log(v.dw); |
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