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DynaML v1.5.2 Release Notes

Release Date: 2018-03-05 // about 6 years ago

  • ➕ Additions

    Tensorflow Integration

    📦 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 matrixval mat = dtf.tensor\_f32(2, 2)(1d, 2d, 3d, 4d) //Create a random 2 \* 3 matrix with independent standard normal entriesval rand\_mat = dtf.random(FLOAT32, 2, 3)( GaussianRV(0d, 1d) \> DataPipe((x: Double) =\> x.toFloat) ) //Multiply matricesval 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 wiseval vert\_tensor = dtf.stack(Seq(rand\_mat, another\_rand\_mat), axis = 0)//Stack vectors horizontally, i.e. column wiseval 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