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No commits in common. "eeadfbdd384bd0d3a446ad65ca3f483e056498e2" and "43cd89faa5e7274875cb0100fff7af208dd84c46" have entirely different histories.
eeadfbdd38
...
43cd89faa5
75
tf.js
75
tf.js
@ -7,15 +7,16 @@ const inputShape = parseInt(args[0]);
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const outputShape = parseInt(args[1]);
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const hiddenSize = parseInt(args[2]);
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// Define a model for linear regression.
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var model = tf.sequential();
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model.add(tf.layers.dense({units: hiddenSize, inputShape: [inputShape], activation: 'relu'}));
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model.add(tf.layers.dense({units: hiddenSize, inputShape: [inputShape]}));
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model.add(tf.layers.dense({units: outputShape}));
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model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
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// Generate some synthetic data for training.
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var xsArr = [];
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@ -23,7 +24,6 @@ var ysArr = [];
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maxApi.addHandler("train", (epochs) => {
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model.compile({loss: 'meanSquaredError', optimizer: 'sgd'});
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// aggregate data
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const xs = tf.tensor2d(xsArr, [xsArr.length, inputShape]);
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@ -31,28 +31,14 @@ maxApi.addHandler("train", (epochs) => {
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// Train the model using the data.
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model.fit(xs, ys, {epochs});
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maxApi.outlet("training_done");
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});
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maxApi.addHandler("data_point", (...data) => {
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maxApi.addHandler("dataPoint", (...data) => {
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data.map((item) => parseFloat(item));
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xsArr.push(data.slice(0, inputShape));
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ysArr.push(data.slice(inputShape));
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});
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maxApi.addHandler("clear_data", () => {
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xsArr = [];
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ysArr = [];
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});
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maxApi.addHandler("dump_data", () => {
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for (let i=0; i<xsArr.length; i++) {
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maxApi.outlet(xsArr[i].concat(ysArr[i]));
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}
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});
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maxApi.addHandler("predict", (...data) => {
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data.map((item) => parseFloat(item));
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model.predict(tf.tensor2d([data], [1, inputShape])).array().then((value) => {
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@ -74,43 +60,28 @@ async function getWeights() {
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maxApi.addHandler("save", (dictId, key) => {
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maxApi.getDict(dictId).then((dict) => {
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getJson().then((json) => {
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dict[key] = json
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getWeights().then((weights) => {
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console.log(weights);
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dict[key] = weights;
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maxApi.setDict(dictId, dict);
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});
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});
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});
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async function getJson() {
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let json = {}
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json.weights = await getWeights();
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json.model = model.toJSON(null, false);
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return json;
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}
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maxApi.addHandler("load", (dictId, key) => {
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maxApi.getDict(dictId).then((dict) => {
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let data = dict[key];
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let tensors = [];
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data.forEach(item => {
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let shape = item.shape;
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let vals = [];
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for (const [key, value] of Object.entries(item.data)) {
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vals.push(value);
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function loadWeights(dict){
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tf.models.modelFromJSON(dict.model).then((m) => {
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model = m
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let data = dict.weights;
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let tensors = [];
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data.forEach(item => {
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let shape = item.shape;
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let vals = [];
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for (const [key, value] of Object.entries(item.data)) {
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vals.push(value);
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}
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tensors.push(tf.tensor(vals, shape));
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});
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model.setWeights(tensors);
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});
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}
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maxApi.addHandler("set_weights", loadWeights);
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maxApi.addHandler("dump_weights", () => {
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getJson().then((json) => {maxApi.outlet("weights", json);});
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})
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}
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tensors.push(tf.tensor(vals, shape));
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});
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model.setWeights(tensors);
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});
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});
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411
tf.maxpat
411
tf.maxpat
@ -10,7 +10,7 @@
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||||
}
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||||
,
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||||
"classnamespace" : "box",
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"rect" : [ 44.0, 125.0, 1036.0, 622.0 ],
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"rect" : [ 164.0, 165.0, 948.0, 575.0 ],
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"bglocked" : 0,
|
||||
"openinpresentation" : 0,
|
||||
"default_fontsize" : 12.0,
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||||
@ -40,36 +40,26 @@
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||||
"assistshowspatchername" : 0,
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||||
"boxes" : [ {
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||||
"box" : {
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"id" : "obj-44",
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"maxclass" : "comment",
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"numinlets" : 1,
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||||
"numoutlets" : 0,
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"patching_rect" : [ 858.0, 270.0, 150.0, 20.0 ],
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"text" : "dump all training points"
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||||
}
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||||
}
|
||||
, {
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||||
"box" : {
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"id" : "obj-42",
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"id" : "obj-40",
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"linecount" : 2,
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"maxclass" : "message",
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"numinlets" : 2,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 858.0, 296.0, 69.0, 22.0 ],
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"text" : "dump_data"
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"patching_rect" : [ 237.0, 453.0, 50.0, 36.0 ],
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"text" : "9. 10. 11."
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}
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}
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, {
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"box" : {
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"id" : "obj-39",
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"linecount" : 3,
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"maxclass" : "comment",
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"numinlets" : 1,
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"numoutlets" : 0,
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"patching_rect" : [ 854.0, 175.0, 150.0, 48.0 ],
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"text" : "clear all cached training data points (does not clear the weights)"
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"id" : "obj-36",
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"maxclass" : "message",
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"numinlets" : 2,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 768.0, 156.0, 111.0, 22.0 ],
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"text" : "load weights kieran"
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}
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}
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||||
@ -80,287 +70,66 @@
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"numinlets" : 2,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 858.0, 232.0, 65.0, 22.0 ],
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"text" : "clear_data"
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}
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}
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, {
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"box" : {
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"id" : "obj-40",
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"linecount" : 2,
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"maxclass" : "message",
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"numinlets" : 2,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 199.0, 355.0, 50.0, 36.0 ],
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"text" : "1 1 1 2 3"
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}
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}
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, {
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"box" : {
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"id" : "obj-38",
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"maxclass" : "newobj",
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"numinlets" : 3,
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"numoutlets" : 3,
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"outlettype" : [ "", "", "" ],
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"patching_rect" : [ 230.0, 325.0, 98.0, 22.0 ],
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"text" : "route list weights"
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}
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}
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, {
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"box" : {
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"id" : "obj-37",
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"linecount" : 4,
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"maxclass" : "comment",
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"numinlets" : 1,
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"numoutlets" : 0,
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"patching_rect" : [ 510.0, 97.0, 150.0, 62.0 ],
|
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"text" : "Send a dictionary with weights and architecture prepended by \"set_weights\" to load"
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}
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|
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}
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, {
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"box" : {
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"id" : "obj-2",
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"maxclass" : "newobj",
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"numinlets" : 1,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 482.0, 192.0, 119.0, 22.0 ],
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"text" : "prepend set_weights"
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}
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}
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, {
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"box" : {
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"id" : "obj-31",
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"maxclass" : "button",
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"numinlets" : 1,
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"numoutlets" : 1,
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"outlettype" : [ "bang" ],
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"parameter_enable" : 0,
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"patching_rect" : [ 482.0, 130.0, 24.0, 24.0 ]
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}
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}
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, {
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"box" : {
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"id" : "obj-27",
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"linecount" : 3,
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"maxclass" : "comment",
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"numinlets" : 1,
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"numoutlets" : 0,
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"patching_rect" : [ 676.0, 172.0, 150.0, 48.0 ],
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"text" : "output a dictionary containing model architecture and weights"
|
||||
}
|
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|
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}
|
||||
, {
|
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"box" : {
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"id" : "obj-7",
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"maxclass" : "dict.view",
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"numinlets" : 1,
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"numoutlets" : 0,
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"patching_rect" : [ 305.0, 382.0, 220.0, 214.0 ]
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}
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}
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, {
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"box" : {
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"id" : "obj-21",
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"maxclass" : "message",
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"numinlets" : 2,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 676.0, 225.0, 86.0, 22.0 ],
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"text" : "dump_weights"
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}
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}
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, {
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"box" : {
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"id" : "obj-12",
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"maxclass" : "newobj",
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"numinlets" : 2,
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"numoutlets" : 5,
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"outlettype" : [ "dictionary", "", "", "", "" ],
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"patching_rect" : [ 305.0, 355.0, 61.0, 22.0 ],
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"saved_object_attributes" : {
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"embed" : 0,
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"legacy" : 0,
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"parameter_enable" : 0,
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"parameter_mappable" : 0
|
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}
|
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,
|
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"text" : "dict"
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}
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}
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, {
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"box" : {
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"id" : "obj-11",
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"maxclass" : "message",
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"numinlets" : 2,
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"numoutlets" : 1,
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"outlettype" : [ "" ],
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"patching_rect" : [ 9.0, 185.0, 94.0, 22.0 ],
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"text" : "script start 2 3 4"
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}
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}
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, {
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"box" : {
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"id" : "obj-8",
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"linecount" : 2,
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"patching_rect" : [ 7.0, 134.0, 150.0, 34.0 ],
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"text" : "0.5. Restart the main script"
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"patching_rect" : [ 626.0, 156.0, 114.0, 22.0 ],
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"text" : "save weights kieran"
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}
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}
|
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, {
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"box" : {
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"data" : {
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"weights" : [ {
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,
|
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"shape" : [ 3 ]
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}
|
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],
|
||||
"model" : {
|
||||
"class_name" : "Sequential",
|
||||
"config" : {
|
||||
"name" : "sequential_1",
|
||||
"layers" : [ {
|
||||
"class_name" : "Dense",
|
||||
"config" : {
|
||||
"units" : 4,
|
||||
"activation" : "relu",
|
||||
"use_bias" : 1,
|
||||
"kernel_initializer" : {
|
||||
"class_name" : "VarianceScaling",
|
||||
"config" : {
|
||||
"scale" : 1,
|
||||
"mode" : "fan_avg",
|
||||
"distribution" : "normal",
|
||||
"seed" : null
|
||||
}
|
||||
|
||||
}
|
||||
,
|
||||
"bias_initializer" : {
|
||||
"class_name" : "Zeros",
|
||||
"config" : {
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
,
|
||||
"kernel_regularizer" : null,
|
||||
"bias_regularizer" : null,
|
||||
"activity_regularizer" : null,
|
||||
"kernel_constraint" : null,
|
||||
"bias_constraint" : null,
|
||||
"name" : "dense_Dense1",
|
||||
"trainable" : 1,
|
||||
"batch_input_shape" : [ null, 2 ],
|
||||
"dtype" : "float32"
|
||||
}
|
||||
|
||||
}
|
||||
, {
|
||||
"class_name" : "Dense",
|
||||
"config" : {
|
||||
"units" : 3,
|
||||
"activation" : "linear",
|
||||
"use_bias" : 1,
|
||||
"kernel_initializer" : {
|
||||
"class_name" : "VarianceScaling",
|
||||
"config" : {
|
||||
"scale" : 1,
|
||||
"mode" : "fan_avg",
|
||||
"distribution" : "normal",
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"seed" : null
|
||||
}
|
||||
|
||||
}
|
||||
,
|
||||
"bias_initializer" : {
|
||||
"class_name" : "Zeros",
|
||||
"config" : {
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
,
|
||||
"kernel_regularizer" : null,
|
||||
"bias_regularizer" : null,
|
||||
"activity_regularizer" : null,
|
||||
"kernel_constraint" : null,
|
||||
"bias_constraint" : null,
|
||||
"name" : "dense_Dense2",
|
||||
"trainable" : 1
|
||||
}
|
||||
|
||||
}
|
||||
]
|
||||
}
|
||||
,
|
||||
"keras_version" : "tfjs-layers 4.20.0",
|
||||
"backend" : "tensor_flow.js"
|
||||
}
|
||||
|
||||
}
|
||||
,
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@ -376,7 +145,7 @@
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"text" : "args are input shape, output shape, and size of the single hidden layer"
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@ -601,8 +370,6 @@
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}
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, {
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"patchline" : {
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Loading…
Reference in New Issue
Block a user