1.5.2

Additions

Tensorflow Integration

• Tensorflow (beta) support now live, thanks to the tensorflow_scala project! Try it out in:
  • CIFAR-10 example script
  • MNIST example script

Package dynaml.tensorflow

• The dtf package object houses utility functions related to tensorflow primitives. Currently supports creation of tensors from arrays.

  import io.github.mandar2812.dynaml.tensorflow._
  import org.platanios.tensorflow.api._
  //Create a FLOAT32 Tensor of shape (2, 2), i.e. a square matrix
  val mat = dtf.tensor_f32(2, 2)(1d, 2d, 3d, 4d)
           
  //Create a random 2 * 3 matrix with independent standard normal entries
  val rand_mat = dtf.random(FLOAT32, 2, 3)(
    GaussianRV(0d, 1d) > DataPipe((x: Double) => x.toFloat)
  )
           
  //Multiply matrices
  val prod = mat.matmul(rand_mat)
  println(prod.summarize())
  
  val another_rand_mat = dtf.random(FLOAT32, 2, 3)(
    GaussianRV(0d, 1d) > DataPipe((x: Double) => x.toFloat)
  )
  
  //Stack tensors vertically, i.e. row wise
  val vert_tensor = dtf.stack(Seq(rand_mat, another_rand_mat), axis = 0)
  //Stack vectors horizontally, i.e. column wise
  val horz_tensor = dtf.stack(Seq(rand_mat, another_rand_mat), axis = 1)

• The dtflearn package object deals with basic neural network building blocks which are often needed while constructing prediction architectures.

  //Create a simple neural architecture with one convolutional layer 
  //followed by a max pool and feedforward layer  
  val net = tf.learn.Cast("Input/Cast", FLOAT32) >>
    dtflearn.conv2d_pyramid(2, 3)(4, 2)(0.1f, true, 0.6F) >>
    tf.learn.MaxPool("Layer_3/MaxPool", Seq(1, 2, 2, 1), 1, 1, SamePadding) >>
    tf.learn.Flatten("Layer_3/Flatten") >>
    dtflearn.feedforward(256)(id = 4) >>
    tf.learn.ReLU("Layer_4/ReLU", 0.1f) >>
    dtflearn.feedforward(10)(id = 5)

Library Organisation

• Added dynaml-repl and dynaml-notebook modules to repository.

DynaML Server

• DynaML ssh server now available (only in Local mode)

  $ ./target/universal/stage/bin/dynaml --server

  To login to the server open a separate shell and type, (when prompted for password, just press ENTER)

  $ ssh repl@localhost -p22222

Basis Generators

• Legrendre polynomial basis generators

Bugfixes

• Acceptance rule of HyperParameterMCMC and related classes.

Changes

• Increased pretty printing to screen instead of logging.

Cleanup

Package dynaml.models.svm

• Removal of deprecated model classes from svm package