Multilayer neuron network

2026-09-08 16:29:02 +02:00
parent 2f4db07918
commit 08aa04fe56
17 changed files with 630 additions and 50 deletions
@@ -30,6 +30,8 @@ const props = defineProps<{
    datasets: Dataset[];
    selectedDataset: string;
    initializationMethod: InitializationMethod;
+    hiddenLayers: number;
+    hiddenLayersNeurons: number;
    minError: number;
    defaultLearningRate: number;
    sessionId: string;
@@ -38,6 +40,8 @@ const props = defineProps<{

 const selectedDatasetCopy = ref(props.selectedDataset);
 const selectedMethod = ref(props.initializationMethod);
+const hiddenLayers = ref(props.hiddenLayers);
+const hiddenLayersNeurons = ref(props.hiddenLayersNeurons);
 const minError = ref(props.minError);
 const learningRate = ref(props.defaultLearningRate);
 const maxIterations = ref(props.defaultMaxIterations);
@@ -59,6 +63,9 @@ watch(selectedDatasetCopy, (newvalue) => {
    }
    // MaxIterations
    maxIterations.value = props.defaultMaxIterations;
+    if (selectedDatasetCopy && selectedDatasetCopy.defaultMaxIterations !== undefined) {
+        maxIterations.value = selectedDatasetCopy.defaultMaxIterations;
+    }
 })

 const trainingId  = ref<string>('');
@@ -82,6 +89,8 @@ function startTraining() {
            type: props.type,
            dataset: selectedDatasetCopy.value,
            weight_init_method: selectedMethod.value,
+            hidden_layers: hiddenLayers.value,
+            hidden_layers_neurons: hiddenLayersNeurons.value,
            min_error: minError.value,
            learning_rate: learningRate.value,
            session_id: props.sessionId,
@@ -158,7 +167,7 @@ watch(selectedDatasetCopy, (newValue) => {
                                class="cursor-pointer"
                            >
                                <NativeSelectOption
-                                    v-for="method in ['zeros', 'random']"
+                                    v-for="method in (props.type == 'multilayer' ? ['random'] : ['zeros', 'random'])"
                                    v-bind:key="method"
                                    :value="method"
                                >
@@ -169,6 +178,42 @@ watch(selectedDatasetCopy, (newValue) => {
                    </FormItem>
                </FormField>

+                <!-- HIDDEN LAYERS -->
+                <FormField name="hidden_layers" v-if="props.type === 'multilayer'">
+                    <FormItem>
+                        <FormLabel>Nombre de couches cachées</FormLabel>
+                        <FormControl>
+                            <!-- TODO : MAX input -->
+                            <Input
+                                type="number"
+                                v-model="hiddenLayers"
+                                min="1"
+                                max="5"
+                                step="1"
+                                class="w-min"
+                            />
+                        </FormControl>
+                    </FormItem>
+                </FormField>
+
+                <!-- HIDDEN LAYERS NEURONS -->
+                <FormField name="hidden_layers_neurons" v-if="props.type === 'multilayer'">
+                    <FormItem>
+                        <FormLabel>Nombre de neurones par couche cachée</FormLabel>
+                        <FormControl>
+                            <!-- TODO : MAX input -->
+                            <Input
+                                type="number"
+                                v-model="hiddenLayersNeurons"
+                                min="1"
+                                max="5"
+                                step="1"
+                                class="w-min"
+                            />
+                        </FormControl>
+                    </FormItem>
+                </FormField>
+
                <!-- MIN ERROR -->
                <FormField name="min_error" v-if="props.type !== 'simple'">
                    <FormItem>
@@ -210,6 +255,7 @@ watch(selectedDatasetCopy, (newValue) => {
                                type="number"
                                v-model="maxIterations"
                                min="0"
+                                max="5000"
                                step="1"
                                class="w-min"
                            />