@webwriter/neural-network
Version:
Deep learning visualization for feed-forward networks with custom datasets, training and prediction.
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text/typescript
import { LitElementWw } from '@webwriter/lit'
import { CSSResult, TemplateResult, html } from 'lit'
import { customElement, property } from 'lit/decorators.js'
import { globalStyles } from '@/global_styles'
import type { CNeuron } from '@/components/network/neuron'
import { CCard } from '../reusables/c-card'
import { msg } from '@lit/localize'
export class NeuronActivationCard extends LitElementWw {
static scopedElements = {
'c-card': CCard,
}
({ attribute: false })
accessor neuron: CNeuron
// STYLES - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
static styles: CSSResult = globalStyles
// RENDER - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
render(): TemplateResult<1> {
return html`
<c-card>
<div slot="title">${msg('Activation function')}</div>
<div slot="content">
<p>Activation: ${this.neuron.layer.conf.activation.name}</p>
${Object.hasOwn(this.neuron.layer.conf.activation, 'img')
? html`<img src=${this.neuron.layer.conf.activation.img} />`
: html``}
<p>
${msg(
"After calculating a neuron's value by adding up its weighted input values and its bias:",
)}
${this.neuron.layer.conf.activation.description}
</p>
<p>
${msg('Range of possible output values:')}
${this.neuron.layer.conf.activation.range}
</p>
</div>
</c-card>
`
}
}