Fixing up assess(...) function #558
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s314cy
added
bug
s314cy
suggested changes
Dec 29, 2022
| const model = await this.getModel() | ||
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| let features: Array<number | number[] | number[][] | number[][][] | number[][][][] | number[][][][][]> = [] |
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the xs vector is always a batch of samples, hence we usually directly cast it as number[][] to avoid carrying TF.js's bad typing
| const ys = this.getLabel(e.ys as tf.Tensor) | ||
| const pred = this.getLabel(model.predict(xs, { batchSize: batchSize }) as tf.Tensor) | ||
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| const currentFeatures = xs.arraySync() |
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you might have to cast the result of arraySync to number[][] for the reason mentioned above :)
| const currentFeatures = xs.arraySync() | ||
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| if (Array.isArray(currentFeatures)) { | ||
| features = [...features, ...currentFeatures] |
| throw new TypeError('features array is not correct') | ||
| } | ||
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| groundTruth.push(...Array.from(ys)) |
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maybe getLabel could call arraySync instead of dataSync (and cast) to avoid manually constructing an array
s314cy
approved these changes
Jan 4, 2023
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