builds

build/dann.js

@@ -1,5 +1,5 @@
 const isBrowser = typeof process !== 'object';
-const VERSION = 'v2.3.12';
+const VERSION = 'v2.3.13';
 
 /**
  * Add a new custom function to Dannjs.
@@ -2254,73 +2254,6 @@ Dann.prototype.feed = function feed(inputs, options) {
   return this.feedForward(inputs, options);
 };
 
-/**
- * Applies a json object to a Dann model.
- * @method fromJSON
- * @for Dann
- * @param {Object} data model data json object, you can get this object from a yourmodel.toJSON(); See docs <a href="https:/dannjs.org">here</a>.
- * @return {Dann} A Dann model.
- * @example
- * <code>
- * const nn = new Dann(24,4);
- * nn.addHiddenLayer(18,'tanH');
- * nn.addHiddenLayer(12,'sigmoid');
- * nn.makeWeights();
- * const modelData = nn.toJSON();
- * const newNN = new Dann();
- * newNN.fromJSON(modelData);
- * newNN.log();
- * </code>
- */
-Dann.prototype.fromJSON = function fromJSON(data) {
-  this.i = data.arch[0];
-  this.inputs = new Matrix(this.i, 1);
-  this.o = data.arch[data.arch.length - 1];
-  this.outputs = new Matrix(this.o, 1);
-
-  let slayers = JSON.parse(data.lstr);
-  for (let i = 0; i < slayers.length; i++) {
-    let layerdata = JSON.parse(slayers[i]);
-    let layerObj = new Layer(layerdata.type, layerdata.size, layerdata.actname);
-    this.Layers[i] = layerObj;
-  }
-  this.makeWeights();
-  let sweights = JSON.parse(data.wstr);
-  for (let i = 0; i < sweights.length; i++) {
-    this.weights[i].set(JSON.parse(sweights[i]));
-  }
-  let sbiases = JSON.parse(data.bstr);
-  for (let i = 0; i < sbiases.length; i++) {
-    this.biases[i].set(JSON.parse(sbiases[i]));
-  }
-  let serrors = JSON.parse(data.estr);
-  for (let i = 0; i < serrors.length; i++) {
-    this.errors[i].set(JSON.parse(serrors[i]));
-  }
-  let sgradients = JSON.parse(data.gstr);
-  for (let i = 0; i < sgradients.length; i++) {
-    this.gradients[i].set(JSON.parse(sgradients[i]));
-  }
-
-  this.lossfunc_s = data.lf;
-  if (isBrowser) {
-    this.lossfunc = window[data.lf];
-  } else {
-    this.lossfunc = lossfuncs[data.lf];
-  }
-  this.outs = Matrix.toArray(this.Layers[this.Layers.length - 1].layer);
-  this.loss = data.loss;
-  this.losses = [];
-  this.lr = data.lrate;
-  this.arch = data.arch;
-  this.epoch = data.e;
-  this.percentile = data.per;
-  return this;
-};
-Dann.prototype.feed = function feed(inputs, options) {
-  return this.feedForward(inputs, options);
-};
-
 /**
  * Applies a json object to a Dann model.
  * @method fromJSON