From 758e18f8fde286e72f9febe62ca93dcce83d90d9 Mon Sep 17 00:00:00 2001
From: akhandait <akhandait45@gmail.com>
Date: Wed, 18 Jul 2018 02:46:41 +0530
Subject: [PATCH] Overload Forward() function.

---
 src/mlpack/methods/ann/ffn.hpp      | 16 ++++++++++++++++
 src/mlpack/methods/ann/ffn_impl.hpp | 20 ++++++++++++++++++++
 2 files changed, 36 insertions(+)

diff --git a/src/mlpack/methods/ann/ffn.hpp b/src/mlpack/methods/ann/ffn.hpp
index 26dd862aff..7c826ae65f 100644
--- a/src/mlpack/methods/ann/ffn.hpp
+++ b/src/mlpack/methods/ann/ffn.hpp
@@ -284,6 +284,22 @@ class FFN
    */
   void Forward(arma::mat inputs, arma::mat& results);
 
+  /**
+   * Perform a partial forward pass of the data.
+   *
+   * This function is meant for the cases when users require a forward pass only
+   * through certain layers and not the entire network.
+   *
+   * @param inputs The input data for the specified first layer.
+   * @param results The predicted results from the specified last layer.
+   * @param begin The index of the first layer.
+   * @param end The index of the last layer.
+   */
+  void Forward(arma::mat inputs,
+               arma::mat& results,
+               const size_t begin,
+               const size_t end);
+
   /**
    * Perform the backward pass of the data in real batch mode.
    *
diff --git a/src/mlpack/methods/ann/ffn_impl.hpp b/src/mlpack/methods/ann/ffn_impl.hpp
index 8a3c2c57f0..b180b9b0ec 100644
--- a/src/mlpack/methods/ann/ffn_impl.hpp
+++ b/src/mlpack/methods/ann/ffn_impl.hpp
@@ -124,6 +124,26 @@ void FFN<OutputLayerType, InitializationRuleType, CustomLayers...>::Forward(
   results = boost::apply_visitor(outputParameterVisitor, network.back());
 }
 
+template<typename OutputLayerType, typename InitializationRuleType,
+         typename... CustomLayers>
+void FFN<OutputLayerType, InitializationRuleType, CustomLayers...>::Forward(
+    arma::mat inputs, arma::mat& results, const size_t begin, const size_t end)
+{
+  boost::apply_visitor(ForwardVisitor(std::move(inputs), std::move(
+      boost::apply_visitor(outputParameterVisitor, network[begin]))),
+      network[begin]);
+
+  for (size_t i = 1; i < end - begin + 1; ++i)
+  {
+    boost::apply_visitor(ForwardVisitor(std::move(boost::apply_visitor(
+        outputParameterVisitor, network[begin + i - 1])), std::move(
+        boost::apply_visitor(outputParameterVisitor, network[begin + i]))),
+        network[begin + i]);
+  }
+
+  results = boost::apply_visitor(outputParameterVisitor, network[end]);
+}
+
 template<typename OutputLayerType, typename InitializationRuleType,
          typename... CustomLayers>
 double FFN<OutputLayerType, InitializationRuleType, CustomLayers...>::Backward(