update model

app.py

@@ -22,13 +22,62 @@ app.add_middleware(
 class ItemRequest(BaseModel):
     items: list[str]
 
+class CustomDense(layers.Layer):
+
+    def __init__(self, units, activation=None, dropout_rate=0.0, **kwargs):
+        super(CustomDense, self).__init__(**kwargs)
+
+        self.units = units
+        self.activation = tf.keras.activations.get(activation)
+        self.dropout_rate = dropout_rate
+        self.dropout = layers.Dropout(dropout_rate)
+
+    def build(self, input_shape):
+
+        self.w = self.add_weight(
+            shape=(input_shape[-1], self.units),
+            initializer='he_normal',
+            trainable=True,
+            name='kernel'
+        )
+
+        self.b = self.add_weight(
+            shape=(self.units,),
+            initializer='zeros',
+            trainable=True,
+            name='bias'
+        )
+
+    def call(self, inputs, training=False):
+
+        x = tf.matmul(inputs, self.w) + self.b
+
+        if self.activation is not None:
+            x = self.activation(x)
+
+        x = self.dropout(x, training=training)
+
+        return x
+
+    def get_config(self):
+
+        config = super().get_config()
+
+        config.update({
+            "units": self.units,
+            "activation": tf.keras.activations.serialize(self.activation),
+            "dropout_rate": self.dropout_rate
+        })
+
+        return config
+
 model = None
 encoder = None
 
 def get_model():
     global model, encoder
     if model is None:
-        model = tf.keras.models.load_model('model_strukly.keras')
+        model = tf.keras.models.load_model('model_strukly.keras', custom_objects={'CustomDense': CustomDense})
         with open('penerjemah_kategori.pkl', 'rb') as file:
             encoder = pickle.load(file)
     return model, encoder
@@ -94,7 +143,7 @@ def classify_items(request: ItemRequest):
             "success": True, 
             "class_id": best_cat_id,
             "category_name": best_cat_name,
-            "confidence": round(best_confidence * 100, 2)
+            "confidence": round(best_confidence, 2)
         }
         
     except Exception as err:

penerjemah_kategori.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3853757276ca5dc3cd90da9a2cdbb56339be10ddbb38b492831a9ff7773fe8ee
-size 389
+oid sha256:3db024b74a86b6da104ce0044712d118b7b0bce5fefa68617a0827f4b4e01876
+size 363