[mlpack-git] master: remove move constructor and assignement, let the compiler generated it.Remember to define ARMA_USE_CXX11 (32d4bad)
gitdub at mlpack.org
gitdub at mlpack.org
Sat Feb 27 03:36:57 EST 2016
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/c25a2b65e14e86e8c5d1a0c672893c33e337bc0f...a2e57d617e952f1ea2fda8a23e1c6bd2f78beb6d
>---------------------------------------------------------------
commit 32d4badb3adc3b3174ee12618e4db28d7f1bcddd
Author: stereomatchingkiss <stereomatchingkiss at gmail.com>
Date: Sat Feb 27 16:36:57 2016 +0800
remove move constructor and assignement, let the compiler generated it.Remember to define ARMA_USE_CXX11
>---------------------------------------------------------------
32d4badb3adc3b3174ee12618e4db28d7f1bcddd
src/mlpack/methods/ann/layer/conv_layer.hpp | 20 ------------------
src/mlpack/methods/ann/layer/dropout_layer.hpp | 16 ---------------
src/mlpack/methods/ann/layer/linear_layer.hpp | 14 -------------
src/mlpack/methods/ann/layer/lstm_layer.hpp | 15 --------------
.../ann/layer/multiclass_classification_layer.hpp | 8 ++++++++
src/mlpack/methods/ann/layer/one_hot_layer.hpp | 8 ++++++++
src/mlpack/methods/ann/layer/pooling_layer.hpp | 24 ++++++++--------------
src/mlpack/methods/ann/layer/recurrent_layer.hpp | 14 -------------
src/mlpack/methods/ann/layer/softmax_layer.hpp | 14 -------------
9 files changed, 24 insertions(+), 109 deletions(-)
diff --git a/src/mlpack/methods/ann/layer/conv_layer.hpp b/src/mlpack/methods/ann/layer/conv_layer.hpp
index 06f38a8..91c0903 100644
--- a/src/mlpack/methods/ann/layer/conv_layer.hpp
+++ b/src/mlpack/methods/ann/layer/conv_layer.hpp
@@ -70,26 +70,6 @@ class ConvLayer
weights.set_size(wfilter, hfilter, inMaps * outMaps);
}
- ConvLayer(ConvLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- ConvLayer& operator=(ConvLayer &&layer) noexcept
- {
- wfilter = layer.wfilter;
- hfilter = layer.hfilter;
- inMaps = layer.inMaps;
- outMaps = layer.outMaps;
- xStride = layer.xStride;
- yStride = layer.yStride;
- wPad = layer.wPad;
- hPad = layer.hPad;
- weights.swap(layer.weights);
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
diff --git a/src/mlpack/methods/ann/layer/dropout_layer.hpp b/src/mlpack/methods/ann/layer/dropout_layer.hpp
index 4fa46af..c9da721 100644
--- a/src/mlpack/methods/ann/layer/dropout_layer.hpp
+++ b/src/mlpack/methods/ann/layer/dropout_layer.hpp
@@ -66,22 +66,6 @@ class DropoutLayer
// Nothing to do here.
}
- DropoutLayer(DropoutLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- DropoutLayer& operator=(DropoutLayer &&layer) noexcept
- {
- mask.swap(layer.mask);
- ratio = layer.ratio;
- scale = layer.scale;
- deterministic = layer.deterministic;
- rescale = layer.rescale;
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of the dropout layer.
*
diff --git a/src/mlpack/methods/ann/layer/linear_layer.hpp b/src/mlpack/methods/ann/layer/linear_layer.hpp
index f059bb3..1c3a1fa 100644
--- a/src/mlpack/methods/ann/layer/linear_layer.hpp
+++ b/src/mlpack/methods/ann/layer/linear_layer.hpp
@@ -43,20 +43,6 @@ class LinearLayer
weights.set_size(outSize, inSize);
}
- LinearLayer(LinearLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- LinearLayer& operator=(LinearLayer &&layer) noexcept
- {
- inSize = layer.inSize;
- outSize = layer.outSize;
- weights.swap(layer.weights);
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
diff --git a/src/mlpack/methods/ann/layer/lstm_layer.hpp b/src/mlpack/methods/ann/layer/lstm_layer.hpp
index 0ac04e7..ee57456 100644
--- a/src/mlpack/methods/ann/layer/lstm_layer.hpp
+++ b/src/mlpack/methods/ann/layer/lstm_layer.hpp
@@ -61,21 +61,6 @@ class LSTMLayer
}
}
- LSTMLayer(LSTMLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- LSTMLayer& operator=(LSTMLayer &&layer) noexcept
- {
- outSize = layer.outSize;
- seqLen = layer.seqLen;
-
- peepholeWeights.swap(layer.peepholeWeights);
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
diff --git a/src/mlpack/methods/ann/layer/multiclass_classification_layer.hpp b/src/mlpack/methods/ann/layer/multiclass_classification_layer.hpp
index f74ac28..43f8754 100644
--- a/src/mlpack/methods/ann/layer/multiclass_classification_layer.hpp
+++ b/src/mlpack/methods/ann/layer/multiclass_classification_layer.hpp
@@ -61,6 +61,14 @@ class MulticlassClassificationLayer
{
output = inputActivations;
}
+
+ /**
+ * Serialize the layer
+ */
+ template<typename Archive>
+ void Serialize(Archive& ar, const unsigned int /* version */)
+ {
+ }
}; // class MulticlassClassificationLayer
//! Layer traits for the multiclass classification layer.
diff --git a/src/mlpack/methods/ann/layer/one_hot_layer.hpp b/src/mlpack/methods/ann/layer/one_hot_layer.hpp
index e820632..a4dc6f4 100644
--- a/src/mlpack/methods/ann/layer/one_hot_layer.hpp
+++ b/src/mlpack/methods/ann/layer/one_hot_layer.hpp
@@ -62,6 +62,14 @@ class OneHotLayer
inputActivations.max(maxIndex);
output(maxIndex) = 1;
}
+
+ /**
+ * Serialize the layer
+ */
+ template<typename Archive>
+ void Serialize(Archive& ar, const unsigned int /* version */)
+ {
+ }
}; // class OneHotLayer
//! Layer traits for the one-hot class classification layer.
diff --git a/src/mlpack/methods/ann/layer/pooling_layer.hpp b/src/mlpack/methods/ann/layer/pooling_layer.hpp
index fdaefad..64add9b 100644
--- a/src/mlpack/methods/ann/layer/pooling_layer.hpp
+++ b/src/mlpack/methods/ann/layer/pooling_layer.hpp
@@ -45,22 +45,6 @@ class PoolingLayer
// Nothing to do here.
}
- PoolingLayer(PoolingLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- PoolingLayer& operator=(PoolingLayer &&layer) noexcept
- {
- kSize = layer.kSize;
- delta.swap(layer.delta);
- inputParameter.swap(layer.inputParameter);
- outputParameter.swap(layer.outputParameter);
- pooling = std::move(layer.pooling);
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
@@ -163,6 +147,14 @@ class PoolingLayer
//! Modify the delta.
OutputDataType& Delta() { return delta; }
+ /**
+ * Serialize the layer
+ */
+ template<typename Archive>
+ void Serialize(Archive& ar, const unsigned int /* version */)
+ {
+ }
+
private:
/**
* Apply pooling to the input and store the results.
diff --git a/src/mlpack/methods/ann/layer/recurrent_layer.hpp b/src/mlpack/methods/ann/layer/recurrent_layer.hpp
index 332a659..729179f 100644
--- a/src/mlpack/methods/ann/layer/recurrent_layer.hpp
+++ b/src/mlpack/methods/ann/layer/recurrent_layer.hpp
@@ -57,20 +57,6 @@ class RecurrentLayer
weights.set_size(outSize, inSize);
}
- RecurrentLayer(RecurrentLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- RecurrentLayer& operator=(RecurrentLayer &&layer) noexcept
- {
- inSize = layer.inSize;
- outSize = layer.outSize;
- weights.swap(layer.weights);
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
diff --git a/src/mlpack/methods/ann/layer/softmax_layer.hpp b/src/mlpack/methods/ann/layer/softmax_layer.hpp
index 12e0146..4bfd27d 100644
--- a/src/mlpack/methods/ann/layer/softmax_layer.hpp
+++ b/src/mlpack/methods/ann/layer/softmax_layer.hpp
@@ -36,20 +36,6 @@ class SoftmaxLayer
// Nothing to do here.
}
- SoftmaxLayer(SoftmaxLayer &&layer) noexcept
- {
- *this = std::move(layer);
- }
-
- SoftmaxLayer& operator=(SoftmaxLayer &&layer) noexcept
- {
- delta.swap(layer.delta);
- inputParameter.swap(layer.inputParameter);
- outputParameter.swap(layer.outputParameter);
-
- return *this;
- }
-
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
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