[mlpack-git] master: Remove the input parameter since we can't provide an input for batch learning and it wasn't used anyway. (4eb41ca)
gitdub at big.cc.gt.atl.ga.us
gitdub at big.cc.gt.atl.ga.us
Fri Jan 9 09:55:38 EST 2015
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/2c9cb2c2a51d74b42465aae892f29e1e4b842156...059a9b6e7da15e25151daae43e4a41d235f8c84c
>---------------------------------------------------------------
commit 4eb41caabad6b682a1b2a64b539d7e50228b0860
Author: Marcus Edel <marcus.edel at fu-berlin.de>
Date: Fri Jan 9 14:20:20 2015 +0100
Remove the input parameter since we can't provide an input for batch learning and it wasn't used anyway.
>---------------------------------------------------------------
4eb41caabad6b682a1b2a64b539d7e50228b0860
src/mlpack/methods/ann/ffnn.hpp | 7 ++-----
src/mlpack/methods/ann/rnn.hpp | 25 ++++++++++++-------------
2 files changed, 14 insertions(+), 18 deletions(-)
diff --git a/src/mlpack/methods/ann/ffnn.hpp b/src/mlpack/methods/ann/ffnn.hpp
index 907782e..9611c85 100644
--- a/src/mlpack/methods/ann/ffnn.hpp
+++ b/src/mlpack/methods/ann/ffnn.hpp
@@ -91,13 +91,10 @@ class FFNN
}
/**
- * Updating the weights using the specified optimizer and the given input.
+ * Updating the weights using the specified optimizer.
*
- * @param input Input data used to evaluate the network.
- * @tparam VecType Type of data (arma::colvec, arma::mat or arma::sp_mat).
*/
- template <typename VecType>
- void ApplyGradients(const VecType& /* unused */)
+ void ApplyGradients()
{
gradientNum = 0;
ApplyGradients(network);
diff --git a/src/mlpack/methods/ann/rnn.hpp b/src/mlpack/methods/ann/rnn.hpp
index d5862ad..c616aeb 100644
--- a/src/mlpack/methods/ann/rnn.hpp
+++ b/src/mlpack/methods/ann/rnn.hpp
@@ -130,18 +130,18 @@ class RNN
}
/**
- * Updating the weights using the specified optimizer and the given input.
+ * Updating the weights using the specified optimizer.
*
- * @param input Input data used for evaluating the network.
- * @tparam VecType Type of data (arma::colvec, arma::mat or arma::sp_mat).
*/
- template <typename VecType>
- void ApplyGradients(const VecType& input)
+ void ApplyGradients()
{
gradientNum = 0;
- ApplyGradients(network, input);
+ ApplyGradients(network);
}
+ //! Get the error of the network.
+ double Error() const { return err; }
+
private:
/**
* Helper function to reset the network by zeroing the layer activations.
@@ -335,7 +335,7 @@ class RNN
}
/**
- * Sum up all gradients and store the results in the gradients storage.
+ * Sum up all gradients and store the results in the gradients storage.
*
* enable_if (SFINAE) is used to iterate through the network connections.
* The general case peels off the first type and recurses, as usual with
@@ -364,17 +364,16 @@ class RNN
* connections, and one for the general case which peels off the first type
* and recurses, as usual with variadic function templates.
*/
- template<size_t I = 0, typename VecType, typename... Tp>
+ template<size_t I = 0, typename... Tp>
typename std::enable_if<I == sizeof...(Tp) - 1, void>::type
- ApplyGradients(std::tuple<Tp...>& /* unused */,
- const VecType& /* unused */) { }
+ ApplyGradients(std::tuple<Tp...>& /* unused */) { }
- template<size_t I = 0, typename VecType, typename... Tp>
+ template<size_t I = 0, typename... Tp>
typename std::enable_if<I < sizeof...(Tp) - 1, void>::type
- ApplyGradients(std::tuple<Tp...>& t, const VecType& input)
+ ApplyGradients(std::tuple<Tp...>& t)
{
Gradients(std::get<I>(t));
- ApplyGradients<I + 1, VecType, Tp...>(t, input);
+ ApplyGradients<I + 1, Tp...>(t);
}
/**
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