[mlpack-git] master: Add convolution batch mode. (c122d05)

[gitdub at big.cc.gt.atl.ga.us]

Repository : https://github.com/mlpack/mlpack

On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/fbd6b1f878ec3b2fa365254a22daf3add743ee51...2eb28bcc2ada2fe09a7ad7073c0bbcbb96aac0c5

>---------------------------------------------------------------

commit c122d05a46301d17ed4721f5e76829c86ba23a15
Author: Marcus Edel <marcus.edel at fu-berlin.de>
Date:   Sat Apr 25 16:34:36 2015 +0200

    Add convolution batch mode.


>---------------------------------------------------------------

c122d05a46301d17ed4721f5e76829c86ba23a15
 .../ann/convolution_rules/fft_convolution.hpp      | 34 +++++++++++++++++++++-
 .../ann/convolution_rules/naive_convolution.hpp    | 28 ++++++++++++++++++
 .../ann/convolution_rules/svd_convolution.hpp      | 29 ++++++++++++++++++
 3 files changed, 90 insertions(+), 1 deletion(-)

diff --git a/src/mlpack/methods/ann/convolution_rules/fft_convolution.hpp b/src/mlpack/methods/ann/convolution_rules/fft_convolution.hpp
index a7cd366..d247e33 100644
--- a/src/mlpack/methods/ann/convolution_rules/fft_convolution.hpp
+++ b/src/mlpack/methods/ann/convolution_rules/fft_convolution.hpp
@@ -116,7 +116,7 @@ class FFTConvolution
   }
 
   /*
-   * Perform a convolution through using fft 3rd order tensors. This method only
+   * Perform a convolution through fft using 3rd order tensors. This method only
    * supports input which is even on the last dimension. In case of an odd input
    * width, a user can manually pad the imput or specify the padLastDim
    * parameter which takes care of the padding. The filter instead can have any
@@ -146,6 +146,38 @@ class FFTConvolution
       output.slice(i) = convOutput;
     }
   }
+
+  /*
+   * Perform a convolution through fft using dense matrix as input and a 3rd
+   * order tensors as filter and output. This method only supports input which
+   * is even on the last dimension. In case of an odd input width, a user can
+   * manually pad the imput or specify the padLastDim parameter which takes care
+   * of the padding. The filter instead can have any size.
+   *
+   * @param input Input used to perform the convolution.
+   * @param filter Filter used to perform the conolution.
+   * @param output Output data that contains the results of the convolution.
+   */
+  template<typename eT>
+  static void Convolution(const arma::Mat<eT>& input,
+                          const arma::Cube<eT>& filter,
+                          arma::Cube<eT>& output)
+  {
+    arma::Mat<eT> convOutput;
+    FFTConvolution<BorderMode>::Convolution(input, filter.slice(0),
+        convOutput);
+
+    output = arma::Cube<eT>(convOutput.n_rows, convOutput.n_cols,
+        filter.n_slices);
+    output.slice(0) = convOutput;
+
+    for (size_t i = 1; i < filter.n_slices; i++)
+    {
+      FFTConvolution<BorderMode>::Convolution(input, filter.slice(i),
+          convOutput);
+      output.slice(i) = convOutput;
+    }
+  }
 };  // class FFTConvolution
 
 }; // namespace ann
diff --git a/src/mlpack/methods/ann/convolution_rules/naive_convolution.hpp b/src/mlpack/methods/ann/convolution_rules/naive_convolution.hpp
index 5934131..45c75fd 100644
--- a/src/mlpack/methods/ann/convolution_rules/naive_convolution.hpp
+++ b/src/mlpack/methods/ann/convolution_rules/naive_convolution.hpp
@@ -120,6 +120,34 @@ class NaiveConvolution
           output.slice(i));
     }
   }
+
+  /*
+   * Perform a convolution using dense matrix as input and a 3rd order tensors
+   * as filter and output.
+   *
+   * @param input Input used to perform the convolution.
+   * @param filter Filter used to perform the conolution.
+   * @param output Output data that contains the results of the convolution.
+   */
+  template<typename eT>
+  static void Convolution(const arma::Mat<eT>& input,
+                          const arma::Cube<eT>& filter,
+                          arma::Cube<eT>& output)
+  {
+    arma::Mat<eT> convOutput;
+    NaiveConvolution<BorderMode>::Convolution(input, filter.slice(0),
+        convOutput);
+
+    output = arma::Cube<eT>(convOutput.n_rows, convOutput.n_cols,
+        filter.n_slices);
+    output.slice(0) = convOutput;
+
+    for (size_t i = 1; i < filter.n_slices; i++)
+    {
+      NaiveConvolution<BorderMode>::Convolution(input, filter.slice(i),
+          output.slice(i));
+    }
+  }
 };  // class NaiveConvolution
 
 }; // namespace ann
diff --git a/src/mlpack/methods/ann/convolution_rules/svd_convolution.hpp b/src/mlpack/methods/ann/convolution_rules/svd_convolution.hpp
index 3a49684..95d7997 100644
--- a/src/mlpack/methods/ann/convolution_rules/svd_convolution.hpp
+++ b/src/mlpack/methods/ann/convolution_rules/svd_convolution.hpp
@@ -129,6 +129,35 @@ class SVDConvolution
       output.slice(i) = convOutput;
     }
   }
+
+  /*
+   * Perform a convolution using dense matrix as input and a 3rd order tensors
+   * as filter and output.
+   *
+   * @param input Input used to perform the convolution.
+   * @param filter Filter used to perform the conolution.
+   * @param output Output data that contains the results of the convolution.
+   */
+  template<typename eT>
+  static void Convolution(const arma::Mat<eT>& input,
+                          const arma::Cube<eT>& filter,
+                          arma::Cube<eT>& output)
+  {
+    arma::Mat<eT> convOutput;
+    SVDConvolution<BorderMode>::Convolution(input, filter.slice(0),
+        convOutput);
+
+    output = arma::Cube<eT>(convOutput.n_rows, convOutput.n_cols,
+        filter.n_slices);
+    output.slice(0) = convOutput;
+
+    for (size_t i = 1; i < filter.n_slices; i++)
+    {
+      SVDConvolution<BorderMode>::Convolution(input, filter.slice(i),
+          convOutput);
+      output.slice(i) = convOutput;
+    }
+  }
 };  // class SVDConvolution
 
 }; // namespace ann