kris-singh

#include <mlpack/core.hpp>
#include <mlpack/core/util/cli.hpp>

#include <mlpack/methods/ann/init_rules/gaussian_init.hpp>
#include <mlpack/methods/ann/layer/layer_types.hpp>
#include <mlpack/methods/ann/layer/layer.hpp>
#include <mlpack/methods/ann/gan.hpp>
#include <mlpack/methods/softmax_regression/softmax_regression.hpp>
#include <mlpack/core/optimizers/minibatch_sgd/minibatch_sgd.hpp>

kris-singh

Title: Deep Learning Modules

Summary Date: 2017-08-26 22:05:00

Tags: gsoc, rbm, ssRBM, deep learning

Author: Kris Singh

Goals for the summer

---

kris-singh

#include <mlpack/core.hpp>
#include <mlpack/core/util/cli.hpp>

#include <mlpack/methods/ann/init_rules/gaussian_init.hpp>
#include <mlpack/methods/ann/gan.hpp>
#include <mlpack/methods/softmax_regression/softmax_regression.hpp>
#include <mlpack/core/optimizers/minibatch_sgd/minibatch_sgd.hpp>

using namespace mlpack;
using namespace mlpack::ann;

kris-singh

#include <mlpack/core.hpp>
#include <mlpack/core/util/cli.hpp>

#include <mlpack/methods/ann/init_rules/gaussian_init.hpp>
#include <mlpack/methods/ann/gan.hpp>
#include <mlpack/methods/softmax_regression/softmax_regression.hpp>
#include <mlpack/core/optimizers/minibatch_sgd/minibatch_sgd.hpp>

using namespace mlpack;
using namespace mlpack::ann;

kris-singh

#include <mlpack/core.hpp>
#include <mlpack/core/util/cli.hpp>

#include <mlpack/methods/ann/init_rules/gaussian_init.hpp>
#include <mlpack/methods/ann/layer/layer_types.hpp>
#include <mlpack/methods/ann/layer/layer.hpp>
#include <mlpack/methods/ann/gan.hpp>
#include <mlpack/methods/softmax_regression/softmax_regression.hpp>
#include <mlpack/core/optimizers/minibatch_sgd/minibatch_sgd.hpp>

kris-singh

BOOST_AUTO_TEST_CASE(SimpleResizeLayerTest)
{
 arma::mat input, output, unzoomedOutput, expectedOutput;
  input.set_size(100, 1);
  for (size_t i = 0; i < 10; i++)
    for (size_t j = 0; j < 10; j++)
    input[i * 10 + j] = 1 * i / 10.0 + 1 * j / 10.0;

  expectedOutput.set_size(400, 1);
  for (size_t i = 0; i < 20; i++)

kris-singh

 /**
 * @file gan_network_test.cpp
 * @author Kris Singh
 *
 * Tests the gan Network example from keras adverserial
 *
 * mlpack is free software; you may redistribute it and/or modify it under the
 * terms of the 3-clause BSD license.  You should have received a copy of the
 * 3-clause BSD license along with mlpack.  If not, see
 * http://www.opensource.org/licenses/BSD-3-Clause for more information.

kris-singh

/**
 * @file bilinear_function.hpp
 * @author Kris Singh
 *
 * Definition and implementation of the bilinear interpolation function.
 *
 * mlpack is free software; you may redistribute it and/or modify it under the
 * terms of the 3-clause BSD license.  You should have received a copy of the
 * 3-clause BSD license along with mlpack.  If not, see
 * http://www.opensource.org/licenses/BSD-3-Clause for more information.

kris-singh

#include <mlpack/core.hpp>
#include <mlpack/methods/ann/init_rules/gaussian_init.hpp>
#include <mlpack/methods/ann/gan.hpp>
#include <mlpack/methods/softmax_regression/softmax_regression.hpp>
#include <mlpack/core/optimizers/minibatch_sgd/minibatch_sgd.hpp>

int main()
{
  size_t gInputDim = 100;
    // Intialisation function

kris-singh

/**
 * @file binary_rbm_policy.hpp
 * @author Kris Singh
 *
 * mlpack is free software; you may redistribute it and/or modify it under the
 * terms of the 3-clause BSD license.  You should have received a copy of the
 * 3-clause BSD license along with mlpack.  If not, see
 * http://www.opensource.org/licenses/BSD-3-Clause for more information.
 */
#ifndef MLPACK_METHODS_ANN_RBM_BINARY_RBM_POLICY_HPP