tehZevo

from keras.layers import Dense, Flatten, InputLayer, Reshape
from keras.models import Sequential
from keras.datasets import mnist
import numpy as np
import matplotlib.pyplot as plt

(x_train, y_train), (x_test, y_test) = mnist.load_data()

x = np.concatenate([x_train, x_test]) / 255.

tehZevo

//mod function that handles negatives "properly"
function mod(a, b)
{
  return ((a%b)+b)%b
}

//shifts a tensor n times on the given axis
function shift(x, axis, n)
{
  n = mod(n, x.shape[axis]);

tehZevo

//this example was tested in electron; if anyone knows how to get around
//this silliness when using nodejs/electron (without including the .js file in
//html, please let me know)
var tfCore = require("@tensorflow/tfjs-core");
var tfLayers = require("@tensorflow/tfjs-layers");
var tf = Object.assign({}, tfCore, tfLayers);

var xs = tf.tensor([[0, 0], [0, 1], [1, 0], [1, 1]]);
var ys = tf.tensor([[0], [1], [1], [0]]);

tehZevo

var tf = require("@tensorflow/tfjs");

//code modified from:
//https://medium.com/tensorflow/a-gentle-introduction-to-tensorflow-js-dba2e5257702

//define our inputs (combinations of 2 bits, represented as 0s and 1s)
//https://js.tensorflow.org/api/0.12.0/#tensor
var xs = tf.tensor([[0, 0], [0, 1], [1, 0], [1, 1]]);

//define our outputs (xor operation, a simple non-linear problem)

tehZevo

/**
  original: the tensor to modify
  axis: the axis to splice in
  start: the position in the given axis to begin splicing from
  deleteCount: how many frames to remove from the tensor
  toInsert: the tensor to insert at "start" (all axes must match except for "axis")
*/
function spliceTensor(original, axis, start, deleteCount, toInsert)
{
  var preStart = original.shape.map((e) => 0);