From 952a0bf831e83eaf05082edb76006c970a2a6f61 Mon Sep 17 00:00:00 2001 From: Travis CI Date: Mon, 24 Oct 2016 13:04:32 +0000 Subject: [PATCH] Deploy to GitHub Pages: 3dd8c9bea4761652a8e4a4730b52563954ebc42b --- .../ui/api/trainer_config_helpers/layers.txt | 6 ++ doc/genindex.html | 46 +++++++++++-- doc/objects.inv | Bin 155403 -> 155784 bytes doc/searchindex.js | 2 +- doc/source/cuda/rnn/rnn.html | 56 +++++++++++++++- doc/source/gserver/layers/layer.html | 2 +- doc/source/math/matrix/matrix.html | 62 ++++++++++++++++-- doc/ui/api/trainer_config_helpers/layers.html | 59 +++++++++++++++++ .../trainer_config_helpers/layers_index.html | 1 + 9 files changed, 220 insertions(+), 14 deletions(-) diff --git a/doc/_sources/ui/api/trainer_config_helpers/layers.txt b/doc/_sources/ui/api/trainer_config_helpers/layers.txt index 55f5623b0fa..5bb88b0615c 100644 --- a/doc/_sources/ui/api/trainer_config_helpers/layers.txt +++ b/doc/_sources/ui/api/trainer_config_helpers/layers.txt @@ -73,6 +73,12 @@ img_pool_layer :members: img_pool_layer :noindex: +maxout_layer +------------ +.. automodule:: paddle.trainer_config_helpers.layers + :members: maxout_layer + :noindex: + Norm Layer ========== diff --git a/doc/genindex.html b/doc/genindex.html index 4109c73d0c3..76516e6c514 100644 --- a/doc/genindex.html +++ b/doc/genindex.html @@ -1552,12 +1552,12 @@ var _hmt = _hmt || [];
HL_MATRIX_BASE_CUH_ (C macro)
- -
hl_matrix_classification_error (C++ function)
+
+
hl_matrix_column_max (C++ function)
@@ -1691,6 +1691,14 @@ var _hmt = _hmt || []; +
hl_maxout_backward (C++ function) +
+ + +
hl_maxout_forward (C++ function) +
+ +
hl_maxpool_backward (C++ function)
@@ -5203,7 +5211,7 @@ var _hmt = _hmt || []; -
paddle::CpuMatrix::colMax (C++ function) +
paddle::CpuMatrix::colMax (C++ function), [1]
@@ -5291,6 +5299,14 @@ var _hmt = _hmt || []; +
paddle::CpuMatrix::maxoutBackward (C++ function) +
+ + +
paddle::CpuMatrix::maxoutForward (C++ function) +
+ +
paddle::CpuMatrix::maxPoolBackward (C++ function)
@@ -7307,7 +7323,7 @@ var _hmt = _hmt || []; -
paddle::GpuMatrix::colMax (C++ function) +
paddle::GpuMatrix::colMax (C++ function), [1]
@@ -7391,6 +7407,14 @@ var _hmt = _hmt || []; +
paddle::GpuMatrix::maxoutBackward (C++ function) +
+ + +
paddle::GpuMatrix::maxoutForward (C++ function) +
+ +
paddle::GpuMatrix::maxPoolBackward (C++ function)
@@ -9283,7 +9307,7 @@ var _hmt = _hmt || []; -
paddle::Matrix::colMax (C++ function) +
paddle::Matrix::colMax (C++ function), [1]
@@ -9423,6 +9447,14 @@ var _hmt = _hmt || []; +
paddle::Matrix::maxoutBackward (C++ function) +
+ + +
paddle::Matrix::maxoutForward (C++ function) +
+ +
paddle::Matrix::maxPoolBackward (C++ function)
@@ -9638,6 +9670,8 @@ var _hmt = _hmt || [];
paddle::Matrix::~Matrix (C++ function)
+
+
paddle::MatrixOffset (C++ class)
@@ -9650,8 +9684,6 @@ var _hmt = _hmt || [];
paddle::MatrixOffset::aRow_ (C++ member)
-
-
paddle::MatrixOffset::bCol_ (C++ member)
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\ No newline at end of file diff --git a/doc/source/cuda/rnn/rnn.html b/doc/source/cuda/rnn/rnn.html index 2006d46de82..51fb53c71d7 100644 --- a/doc/source/cuda/rnn/rnn.html +++ b/doc/source/cuda/rnn/rnn.html @@ -298,7 +298,7 @@ var _hmt = _hmt || [];

+
+
+void hl_maxout_forward(const real *inData, real *outData, int *idData, size_t batchSize, size_t size, size_t featLen, size_t groups)
+

MaxOut forward.

+

+
Parameters
+
    +
  • inData -

    input data.

    +
    • +
  • outData -

    output data.

    +
    • +
  • idData -

    output maxId.

    +
    • +
  • batchSize -

    batchSize.

    +
    • +
  • size -

    number of channels * image height * image width.

    +
    • +
  • featLen -

    feature length = image height * image width.

    +
    • +
  • groups -

    number of groups.

    +
    • +
+
+
+

+
+ +
+
+void hl_maxout_backward(real *inGrad, const real *outGrad, const int *idData, size_t batchSize, size_t size, size_t featLen, size_t groups)
+

MaxOut backward.

+

+
Parameters
+
    +
  • inGrad -

    input grad data.

    +
    • +
  • outGrad -

    output grad data.

    +
    • +
  • idData -

    output maxId.

    +
    • +
  • batchSize -

    batchSize.

    +
    • +
  • size -

    number of channels * image height * image width.

    +
    • +
  • featLen -

    feature length = image height * image width.

    +
    • +
  • groups -

    number of groups.

    +
    • +
+
+
+

+
+

Defines

diff --git a/doc/source/gserver/layers/layer.html b/doc/source/gserver/layers/layer.html index 3f742ef1533..ef0947489be 100644 --- a/doc/source/gserver/layers/layer.html +++ b/doc/source/gserver/layers/layer.html @@ -78,7 +78,7 @@ var _hmt = _hmt || [];
class paddle::Layer

Base class for layer. Define necessary variables and functions for every layer.

-

Subclassed by paddle::AddtoLayer, paddle::AgentLayer, paddle::BatchNormBaseLayer, paddle::BlockExpandLayer, paddle::BootBiasLayer, paddle::ConcatenateLayer, paddle::ConcatenateLayer2, paddle::ConvBaseLayer, paddle::ConvexCombinationLayer, paddle::ConvShiftLayer, paddle::CosSimLayer, paddle::CosSimVecMatLayer, paddle::CostLayer, paddle::CRFLayer, paddle::CTCLayer, paddle::DataLayer, paddle::DataNormLayer, paddle::EosIdCheckLayer, paddle::ExpandLayer, paddle::FeatureMapExpandLayer, paddle::FullyConnectedLayer, paddle::GatedRecurrentLayer, paddle::GatherAgentLayer, paddle::GetOutputLayer, paddle::GruStepLayer, paddle::HierarchicalSigmoidLayer, paddle::InterpolationLayer, paddle::LambdaCost, paddle::LstmLayer, paddle::LstmStepLayer, paddle::MaxIdLayer, paddle::MixedLayer, paddle::MultiplexLayer, paddle::NCELayer, paddle::NormLayer, paddle::OuterProdLayer, paddle::ParameterReluLayer, paddle::PoolLayer, paddle::PowerLayer, paddle::PrintLayer, paddle::RankingCost, paddle::RecurrentLayer, paddle::RecurrentLayerGroup, paddle::ResizeLayer, paddle::SamplingIdLayer, paddle::ScalingLayer, paddle::ScatterAgentLayer, paddle::SelectiveFullyConnectedLayer, paddle::SequenceConcatLayer, paddle::SequencePoolLayer, paddle::SequenceReshapeLayer, paddle::SlopeInterceptLayer, paddle::SubSequenceLayer, paddle::SumToOneNormLayer, paddle::TensorLayer, paddle::TransLayer, paddle::ValidationLayer

+

Subclassed by paddle::AddtoLayer, paddle::AgentLayer, paddle::BatchNormBaseLayer, paddle::BlockExpandLayer, paddle::BootBiasLayer, paddle::ConcatenateLayer, paddle::ConcatenateLayer2, paddle::ConvBaseLayer, paddle::ConvexCombinationLayer, paddle::ConvShiftLayer, paddle::CosSimLayer, paddle::CosSimVecMatLayer, paddle::CostLayer, paddle::CRFLayer, paddle::CTCLayer, paddle::DataLayer, paddle::DataNormLayer, paddle::EosIdCheckLayer, paddle::ExpandLayer, paddle::FeatureMapExpandLayer, paddle::FullyConnectedLayer, paddle::GatedRecurrentLayer, paddle::GatherAgentLayer, paddle::GetOutputLayer, paddle::GruStepLayer, paddle::HierarchicalSigmoidLayer, paddle::InterpolationLayer, paddle::LambdaCost, paddle::LstmLayer, paddle::LstmStepLayer, paddle::MaxIdLayer, paddle::MaxOutLayer, paddle::MixedLayer, paddle::MultiplexLayer, paddle::NCELayer, paddle::NormLayer, paddle::OuterProdLayer, paddle::ParameterReluLayer, paddle::PoolLayer, paddle::PowerLayer, paddle::PrintLayer, paddle::RankingCost, paddle::RecurrentLayer, paddle::RecurrentLayerGroup, paddle::ResizeLayer, paddle::SamplingIdLayer, paddle::ScalingLayer, paddle::ScatterAgentLayer, paddle::SelectiveFullyConnectedLayer, paddle::SequenceConcatLayer, paddle::SequencePoolLayer, paddle::SequenceReshapeLayer, paddle::SlopeInterceptLayer, paddle::SubSequenceLayer, paddle::SumToOneNormLayer, paddle::TensorLayer, paddle::TransLayer, paddle::ValidationLayer

Public Functions

diff --git a/doc/source/math/matrix/matrix.html b/doc/source/math/matrix/matrix.html index 148e6e1c822..861025ad48b 100644 --- a/doc/source/math/matrix/matrix.html +++ b/doc/source/math/matrix/matrix.html @@ -1966,6 +1966,24 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
virtual void colMax(Matrix &max)
+

set the max of each column of this to mat

+
+ +
+
+virtual void colMax(IVector &maxIds, Matrix &maxVal)
+

Get the top k elements of each column of this matrix.

+

The row ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

+
+ +
+
+virtual void maxoutForward(Matrix &a, IVector &id, size_t channels, size_t groups)
+
+ +
+
+virtual void maxoutBackward(Matrix &a, IVector &id, size_t channels, size_t groups)
@@ -1977,7 +1995,7 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
virtual void rowMax(IVector &maxIds, Matrix &max)

Get the top k elements of each row of this matrix.

-

The column ids and values of these elements are stored in maxIds and max respectively. Note that the top k elements are not sorted.

+

The column ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

@@ -2748,12 +2766,30 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
virtual void rowMax(IVector &maxIds, Matrix &max)

Get the top k elements of each row of this matrix.

-

The column ids and values of these elements are stored in maxIds and max respectively. Note that the top k elements are not sorted.

+

The column ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

virtual void colMax(Matrix &max)
+

set the max of each column of this to mat

+
+ +
+
+virtual void colMax(IVector &maxIds, Matrix &maxVal)
+

Get the top k elements of each column of this matrix.

+

The row ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

+
+ +
+
+virtual void maxoutForward(Matrix &a, IVector &id, size_t channels, size_t groups)
+
+ +
+
+virtual void maxoutBackward(Matrix &a, IVector &id, size_t channels, size_t groups)
@@ -3372,12 +3408,30 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
virtual void rowMax(IVector &maxIds, Matrix &max)

Get the top k elements of each row of this matrix.

-

The column ids and values of these elements are stored in maxIds and max respectively. Note that the top k elements are not sorted.

+

The column ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

virtual void colMax(Matrix &max)
+

set the max of each column of this to mat

+
+ +
+
+virtual void colMax(IVector &maxIds, Matrix &maxVal)
+

Get the top k elements of each column of this matrix.

+

The row ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

+
+ +
+
+virtual void maxoutForward(Matrix &a, IVector &id, size_t channels, size_t groups)
+
+ +
+
+virtual void maxoutBackward(Matrix &a, IVector &id, size_t channels, size_t groups)
@@ -5954,7 +6008,7 @@ virtual virtual void rowMax(IVector &maxIds, Matrix &max)

Get the top k elements of each row of this matrix.

-

The column ids and values of these elements are stored in maxIds and max respectively. Note that the top k elements are not sorted.

+

The column ids and values of these elements are stored in maxIds and max respectively. where k is the size of maxIds. And note that the top k elements are not sorted.

diff --git a/doc/ui/api/trainer_config_helpers/layers.html b/doc/ui/api/trainer_config_helpers/layers.html index f6d045c9b88..e3db75512d7 100644 --- a/doc/ui/api/trainer_config_helpers/layers.html +++ b/doc/ui/api/trainer_config_helpers/layers.html @@ -512,6 +512,64 @@ map should be square.
+
+
+

maxout_layer

+
+
+paddle.trainer_config_helpers.layers.maxout_layer(*args, **kwargs)
+
+
A layer to do max out on conv layer output.
+
    +
  • Input: output of a conv layer.
    • +
  • Output: feature map size same as input. Channel is (input channel) / groups.
    • +
+
+
+

So groups should be larger than 1, and the num of channels should be able +to devided by groups.

+
+
Please refer to Paper:
+
+
+
+

The simple usage is:

+
maxout = maxout_layer(input,
+                      num_channels=128,
+                      groups=4)
+
+
+ +++ + + + + + + + +
Parameters:
    +
  • input (LayerOutput) – The input layer.
    • +
  • num_channels (int|None) – The channel number of input layer. If None will be set +automatically from previous output.
    • +
  • groups (int) – The group number of input layer.
    • +
  • size_x (int|None) – conv output width. If None will be set +automatically from previous output.
    • +
  • size_y (int|None) – conv output height. If None will be set +automatically from previous output.
    • +
  • name (None|basestring.) – The name of this layer, which can not specify.
    • +
  • layer_attr (ExtraLayerAttribute) – Extra Layer attribute.
    • +
+
Returns:

LayerOutput object.

+
Return type:

LayerOutput

+
+
+
@@ -2687,6 +2745,7 @@ It is used by recurrent layer group.

  • Image Pooling Layer
  • Norm Layer
      diff --git a/doc/ui/api/trainer_config_helpers/layers_index.html b/doc/ui/api/trainer_config_helpers/layers_index.html index 4b825430a0a..6448cb3adeb 100644 --- a/doc/ui/api/trainer_config_helpers/layers_index.html +++ b/doc/ui/api/trainer_config_helpers/layers_index.html @@ -97,6 +97,7 @@ var _hmt = _hmt || [];
    • Image Pooling Layer
    • Norm Layer
        -- GitLab