From c95d549025f1c1ddc7e1aebda026431ac51ded5d Mon Sep 17 00:00:00 2001 From: Travis CI Date: Sun, 9 Oct 2016 05:57:41 +0000 Subject: [PATCH] Deploy to GitHub Pages: 191fafe355717c506663b5ddd13d8a18ae944924 --- doc/genindex.html | 48 ++++++------- doc/objects.inv | Bin 155876 -> 155873 bytes doc/searchindex.js | 2 +- doc/source/cuda/rnn/rnn.html | 68 ++++++++++++------ doc/source/gserver/layers/layer.html | 17 ++--- doc/source/math/matrix/matrix.html | 48 ++++++------- doc/ui/api/trainer_config_helpers/layers.html | 13 ++-- .../api/trainer_config_helpers/networks.html | 10 +-- 8 files changed, 113 insertions(+), 93 deletions(-) diff --git a/doc/genindex.html b/doc/genindex.html index 50f5737bb09..5eb89b5c237 100644 --- a/doc/genindex.html +++ b/doc/genindex.html @@ -993,11 +993,11 @@ var _hmt = _hmt || []; -
hl_avgpool_backward (C++ function) +
hl_avgpool_backward (C++ function)
-
hl_avgpool_forward (C++ function) +
hl_avgpool_forward (C++ function)
@@ -1691,11 +1691,11 @@ var _hmt = _hmt || []; -
hl_maxpool_backward (C++ function) +
hl_maxpool_backward (C++ function)
-
hl_maxpool_forward (C++ function) +
hl_maxpool_forward (C++ function)
@@ -5187,11 +5187,11 @@ var _hmt = _hmt || []; -
paddle::CpuMatrix::avgPoolBackward (C++ function) +
paddle::CpuMatrix::avgPoolBackward (C++ function)
-
paddle::CpuMatrix::avgPoolForward (C++ function) +
paddle::CpuMatrix::avgPoolForward (C++ function)
@@ -5311,11 +5311,11 @@ var _hmt = _hmt || []; -
paddle::CpuMatrix::maxPoolBackward (C++ function) +
paddle::CpuMatrix::maxPoolBackward (C++ function)
-
paddle::CpuMatrix::maxPoolForward (C++ function) +
paddle::CpuMatrix::maxPoolForward (C++ function)
@@ -6215,10 +6215,6 @@ var _hmt = _hmt || []; -
paddle::CudnnPoolLayer::outputSize (C++ function) -
- -
paddle::CudnnPoolLayer::outputW_ (C++ member)
@@ -7311,11 +7307,11 @@ var _hmt = _hmt || []; -
paddle::GpuMatrix::avgPoolBackward (C++ function) +
paddle::GpuMatrix::avgPoolBackward (C++ function)
-
paddle::GpuMatrix::avgPoolForward (C++ function) +
paddle::GpuMatrix::avgPoolForward (C++ function)
@@ -7419,11 +7415,11 @@ var _hmt = _hmt || []; -
paddle::GpuMatrix::maxPoolBackward (C++ function) +
paddle::GpuMatrix::maxPoolBackward (C++ function)
-
paddle::GpuMatrix::maxPoolForward (C++ function) +
paddle::GpuMatrix::maxPoolForward (C++ function)
@@ -9271,11 +9267,11 @@ var _hmt = _hmt || []; -
paddle::Matrix::avgPoolBackward (C++ function) +
paddle::Matrix::avgPoolBackward (C++ function)
-
paddle::Matrix::avgPoolForward (C++ function) +
paddle::Matrix::avgPoolForward (C++ function)
@@ -9451,11 +9447,11 @@ var _hmt = _hmt || []; -
paddle::Matrix::maxPoolBackward (C++ function) +
paddle::Matrix::maxPoolBackward (C++ function)
-
paddle::Matrix::maxPoolForward (C++ function) +
paddle::Matrix::maxPoolForward (C++ function)
@@ -9682,12 +9678,12 @@ var _hmt = _hmt || [];
paddle::MatrixOffset::bCol_ (C++ member)
- -
paddle::MatrixOffset::bRow_ (C++ member)
+
+
paddle::MatrixOffset::cCol_ (C++ member)
@@ -12725,6 +12721,10 @@ var _hmt = _hmt || []; +
paddle::PoolLayer::outputSize (C++ function) +
+ +
paddle::PoolLayer::outputX_ (C++ member)
@@ -12749,10 +12749,6 @@ var _hmt = _hmt || []; -
paddle::PoolLayer::start_ (C++ member) -
- -
paddle::PoolLayer::stride_ (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 7674518f273..862178244ec 100644 --- a/doc/source/cuda/rnn/rnn.html +++ b/doc/source/cuda/rnn/rnn.html @@ -159,8 +159,8 @@ var _hmt = _hmt || [];

-
-void hl_maxpool_forward(int frameCnt, const real *inputData, int channels, int height, int width, int pooledH, int pooledW, int sizeX, int stride, int start, real *tgtData)
+
+void hl_maxpool_forward(const int frameCnt, const real *inputData, const int channels, const int height, const int width, const int pooledH, const int pooledW, const int sizeX, const int sizeY, const int strideH, const int strideW, const int paddingH, const int paddingW, real *tgtData)

Maximum pool forward.

Parameters
@@ -179,11 +179,17 @@ var _hmt = _hmt || [];
  • pooledW -

    output image width.

    • -
  • sizeX -

    size of pooling window.

    +
  • sizeX -

    width of pooling window.

    • -
  • stride -

    pooling stride.

    +
  • sizeY -

    height of pooling window.

    • -
  • start -

    pooling start.

    +
  • strideH -

    pooling stride height.

    +
    • +
  • strideW -

    pooling stride width.

    +
    • +
  • paddingH -

    padding height.

    +
    • +
  • paddingW -

    padding width.

  • tgtData -

    output data.

    • @@ -194,8 +200,8 @@ var _hmt = _hmt || [];
    -
    -void hl_maxpool_backward(int frameCnt, const real *inputData, const real *outData, const real *outGrad, int channels, int height, int width, int pooledH, int pooledW, int sizeX, int stride, int start, real *targetGrad, real scaleA, real scaleB)
    +
    +void hl_maxpool_backward(const int frameCnt, const real *inputData, const real *outData, const real *outGrad, const int channels, const int height, const int width, const int pooledH, const int pooledW, const int sizeX, const int sizeY, const int strideH, const int strideW, const int paddingH, const int paddingW, real scaleA, real scaleB, real *targetGrad)

    Maximum pool backward.

    Parameters
    @@ -218,18 +224,24 @@ var _hmt = _hmt || [];
  • pooledW -

    output image width.

    • -
  • sizeX -

    size of pooling window.

    +
  • sizeX -

    width of pooling window.

    • -
  • stride -

    pooling stride.

    +
  • sizeY -

    height of pooling window.

    • -
  • start -

    pooling start.

    +
  • strideH -

    pooling stride height.

    • -
  • targetGrad -

    output grad.

    +
  • strideW -

    pooling stride width.

  • scaleA -

    scale.

  • scaleB -

    scale.

    • +
  • paddingH -

    padding height.

    +
    • +
  • paddingW -

    padding width.

    +
    • +
  • targetGrad -

    output grad.

    +
    • @@ -237,8 +249,8 @@ var _hmt = _hmt || [];
    -
    -void hl_avgpool_forward(int frameCnt, const real *inputData, int channels, int height, int width, int pooledH, int pooledW, int sizeX, int stride, int start, real *tgtData)
    +
    +void hl_avgpool_forward(const int frameCnt, const real *inputData, const int channels, const int height, const int width, const int pooledH, const int pooledW, const int sizeX, const int sizeY, const int strideH, const int strideW, const int paddingH, const int paddingW, real *tgtData)

    Averge pool forward.

    Parameters
    @@ -257,11 +269,17 @@ var _hmt = _hmt || [];
  • pooledW -

    output image width.

    • -
  • sizeX -

    size of pooling window.

    +
  • sizeX -

    width of pooling window.

    • -
  • stride -

    pooling stride.

    +
  • sizeY -

    height of pooling window.

    • -
  • start -

    pooling start.

    +
  • strideH -

    pooling stride height.

    +
    • +
  • strideW -

    pooling stride width.

    +
    • +
  • paddingH -

    padding height.

    +
    • +
  • paddingW -

    padding width.

  • tgtData -

    output data.

    • @@ -272,8 +290,8 @@ var _hmt = _hmt || [];
    -
    -void hl_avgpool_backward(int frameCnt, const real *outGrad, int channels, int height, int width, int pooledH, int pooledW, int sizeX, int stride, int start, real *backGrad, real scaleA, real scaleB)
    +
    +void hl_avgpool_backward(const int frameCnt, const real *outGrad, const int channels, const int height, const int width, const int pooledH, const int pooledW, const int sizeX, const int sizeY, const int strideH, const int strideW, int paddingH, int paddingW, real scaleA, real scaleB, real *backGrad)

    Maximum pool backward.

    Parameters
    @@ -292,18 +310,24 @@ var _hmt = _hmt || [];
  • pooledW -

    output image width.

    • -
  • sizeX -

    size of pooling window.

    +
  • sizeX -

    width of pooling window.

    • -
  • stride -

    pooling stride.

    +
  • sizeY -

    height of pooling window.

    • -
  • start -

    pooling start.

    +
  • strideH -

    pooling stride height.

    • -
  • backGrad -

    output grad.

    +
  • strideW -

    pooling stride width.

    +
    • +
  • paddingH -

    padding height.

    +
    • +
  • paddingW -

    padding width.

  • scaleA -

    scale.

  • scaleB -

    scale.

    • +
  • backGrad -

    output grad.

    +
    • diff --git a/doc/source/gserver/layers/layer.html b/doc/source/gserver/layers/layer.html index 986968adf0d..453a44b4e69 100644 --- a/doc/source/gserver/layers/layer.html +++ b/doc/source/gserver/layers/layer.html @@ -1794,6 +1794,12 @@ virtual +
    +int outputSize(int imageSize, int windowSize, int padding, int stride)
    +

    Calculate output size according window size and padding size.

    +
    +

    Public Static Functions

    @@ -1831,11 +1837,6 @@ virtual size_t imgSize_
    -
    -
    -int start_
    -
    -
    int confPadding_
    @@ -1966,12 +1967,6 @@ virtual Layer::forward() function.

    -
    -
    -int outputSize(int imageSize, int windowSize, int padding, int stride)
    -

    Calculate output size according window size of pooling.

    -
    -

    Public Static Functions

    diff --git a/doc/source/math/matrix/matrix.html b/doc/source/math/matrix/matrix.html index 600590e5fd4..374a333e7d1 100644 --- a/doc/source/math/matrix/matrix.html +++ b/doc/source/math/matrix/matrix.html @@ -2205,26 +2205,26 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
    -
    -virtual void maxPoolForward(Matrix &inputMat, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, int start_, size_t stride, size_t outputH, size_t outputW)
    +
    +virtual void maxPoolForward(Matrix &inputMat, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, size_t paddingH, size_t paddingW)

    Pooling forward operation, pick out the largest element in the sizeX of value

    -
    -virtual void maxPoolBackward(Matrix &image, size_t imgSizeH, size_t imgSizeW, Matrix &outGrad, Matrix &outV, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput)
    +
    +virtual void maxPoolBackward(Matrix &image, size_t imgSizeH, size_t imgSizeW, Matrix &outGrad, Matrix &outV, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput, size_t paddingH, size_t paddingW)

    Pooling backward operation.

    -
    -virtual void avgPoolForward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW)
    +
    +virtual void avgPoolForward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, size_t paddingH, size_t paddingW)

    Pooling forward operation, caculate the average of sizeX elements.

    -
    -virtual void avgPoolBackward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput)
    +
    +virtual void avgPoolBackward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput, size_t paddingH, size_t paddingW)
    @@ -2909,26 +2909,26 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
    -
    -virtual void maxPoolForward(Matrix &inputMat, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, int start_, size_t stride, size_t outputH, size_t outputW)
    +
    +virtual void maxPoolForward(Matrix &inputMat, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, size_t paddingH, size_t paddingW)

    Pooling forward operation, pick out the largest element in the sizeX of value

    -
    -virtual void maxPoolBackward(Matrix &image, size_t imgSizeH, size_t imgSizeW, Matrix &outGrad, Matrix &outV, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput)
    +
    +virtual void maxPoolBackward(Matrix &image, size_t imgSizeH, size_t imgSizeW, Matrix &outGrad, Matrix &outV, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput, size_t paddingH, size_t paddingW)

    Pooling backward operation.

    -
    -virtual void avgPoolForward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW)
    +
    +virtual void avgPoolForward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, size_t paddingH, size_t paddingW)

    Pooling forward operation, caculate the average of sizeX elements.

    -
    -virtual void avgPoolBackward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput)
    +
    +virtual void avgPoolBackward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput, size_t paddingH, size_t paddingW)
    @@ -3137,26 +3137,26 @@ where bit(i, j) = ((codes(i) + numClasses) & 2^j) ? 1 : 0
    -
    -virtual void maxPoolForward(Matrix &inputMat, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, int start_, size_t stride, size_t outputH, size_t outputW)
    +
    +virtual void maxPoolForward(Matrix &inputMat, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, size_t paddingH, size_t paddingW)

    Pooling forward operation, pick out the largest element in the sizeX of value

    -
    -virtual void maxPoolBackward(Matrix &image, size_t imgSizeH, size_t imgSizeW, Matrix &outGrad, Matrix &outV, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput)
    +
    +virtual void maxPoolBackward(Matrix &image, size_t imgSizeH, size_t imgSizeW, Matrix &outGrad, Matrix &outV, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput, size_t paddingH, size_t paddingW)

    Pooling backward operation.

    -
    -virtual void avgPoolForward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW)
    +
    +virtual void avgPoolForward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t channels, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, size_t paddingH, size_t paddingW)

    Pooling forward operation, caculate the average of sizeX elements.

    -
    -virtual void avgPoolBackward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t sizeX, int start, size_t stride, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput)
    +
    +virtual void avgPoolBackward(Matrix &input, size_t imgSizeH, size_t imgSizeW, size_t sizeX, size_t sizeY, size_t strideH, size_t strideW, size_t outputH, size_t outputW, real scaleTargets, real scaleOutput, size_t paddingH, size_t paddingW)
    diff --git a/doc/ui/api/trainer_config_helpers/layers.html b/doc/ui/api/trainer_config_helpers/layers.html index c85e7dfd72f..99e2734b672 100644 --- a/doc/ui/api/trainer_config_helpers/layers.html +++ b/doc/ui/api/trainer_config_helpers/layers.html @@ -483,16 +483,21 @@ parameter attribute is set by this parameter. Parameters:
      -
    • padding (int) – pooling padding
      • +
    • padding (int) – pooling padding width.
      • +
    • padding_y (int|None) – pooling padding height. It’s equal to padding by default.
    • name (basestring.) – name of pooling layer
    • input (LayerOutput) – layer’s input
      • -
    • pool_size (int) – pooling size
      • +
    • pool_size (int) – pooling window width
      • +
    • pool_size_y (int|None) – pooling window height. It’s eaqual to pool_size by default.
    • num_channels (int) – number of input channel.
    • pool_type (BasePoolingType) – pooling type. MaxPooling or AveragePooling. Default is MaxPooling.
      • -
    • stride (int) – stride of pooling.
      • -
    • start (int) – start position of pooling operation.
      • +
    • stride (int) – stride width of pooling.
      • +
    • stride_y (int|None) – stride height of pooling. It is equal to stride by default.
      • +
    • start (int|None) – start position of pooling operation. Note it is deprecated now.
    • layer_attr (ExtraLayerAttribute) – Extra Layer attribute.
      • +
    • img_width (int|None) – the width of input feature map. If it is None, the input feature +map should be square.
    diff --git a/doc/ui/api/trainer_config_helpers/networks.html b/doc/ui/api/trainer_config_helpers/networks.html index 93e67d83293..fe88e04ffec 100644 --- a/doc/ui/api/trainer_config_helpers/networks.html +++ b/doc/ui/api/trainer_config_helpers/networks.html @@ -202,7 +202,7 @@ False if no bias.
  • bn_bias_attr – see batch_norm_layer’s document.
  • bn_layer_attr – ParameterAttribute.
  • pool_stride (int) – see img_pool_layer’s document.
    • -
  • pool_start (int) – see img_pool_layer’s document.
    • +
  • pool_start (int) – see img_pool_layer’s document. It is deprecated now.
  • pool_padding (int) – see img_pool_layer’s document.
  • pool_layer_attr (ExtraLayerAttribute) – see img_pool_layer’s document.
    • @@ -280,10 +280,10 @@ False if no bias.
  • param_attr (ParameterAttribute) – see img_conv_layer for details
  • shared_bias (bool) – see img_conv_layer for details
  • conv_layer_attr (ExtraLayerAttribute) – see img_conv_layer for details
    • -
  • pool_stride (int) – see img_conv_layer for details
    • -
  • pool_start (int) – see img_conv_layer for details
    • -
  • pool_padding (int) – see img_conv_layer for details
    • -
  • pool_layer_attr (ExtraLayerAttribute) – see img_conv_layer for details
    • +
  • pool_stride (int) – see img_pool_layer for details
    • +
  • pool_start (int) – see img_pool_layer for details. It is deprecated now.
    • +
  • pool_padding (int) – see img_pool_layer for details
    • +
  • pool_layer_attr (ExtraLayerAttribute) – see img_pool_layer for details
    • -- GitLab