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Fix broken links in layer documentation, minor fixes. · anhuipl2010/Caffe-HRT@6bf10af · GitHub

  1. anhuipl2010
  2. Caffe-HRT

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Commit 6bf10af

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williford
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Fix broken links in layer documentation, minor fixes.
1 parent b8fa34d commit 6bf10af

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‎docs/tutorial/layers/accuracy.md‎

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* [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1AccuracyLayer.html)
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* Header: [`./include/caffe/layers/accuracy_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/accuracy_layer.hpp)
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* CPU implementation: [`./src/caffe/layers/accuracy_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/accuracy_layer.cpp)
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* CUDA GPU implementation: [`./src/caffe/layers/accuracy_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/accuracy_layer.cu)
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## Parameters
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* Parameters (`AccuracyParameter accuracy_param`)
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* From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)):
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{% highlight Protobuf %}
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{% include proto/AccuracyParameter.txt %}
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{% endhighlight %}
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{% endhighlight %}

‎docs/tutorial/layers/argmax.md‎

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* [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1ArgMaxLayer.html)
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* Header: [`./include/caffe/layers/argmax_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/argmax_layer.hpp)
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* CPU implementation: [`./src/caffe/layers/argmax_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/argmax_layer.cpp)
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* CUDA GPU implementation: [`./src/caffe/layers/argmax_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/argmax_layer.cu)
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## Parameters
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* Parameters (`ArgMaxParameter argmax_param`)
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* From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto)):
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{% highlight Protobuf %}
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{% include proto/ArgMaxParameter.txt %}
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{% endhighlight %}
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{% endhighlight %}

‎docs/tutorial/layers/infogainloss.md‎

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* [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1InfogainLossLayer.html)
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* Header: [`./include/caffe/layers/infogain_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/infogain_loss_layer.hpp)
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* CPU implementation: [`./src/caffe/layers/infogain_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/infogain_loss_layer.cpp)
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* CUDA GPU implementation: [`./src/caffe/layers/infogain_loss_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/infogain_loss_layer.cu)
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A generalization of [MultinomialLogisticLossLayer](layers/multinomiallogisticloss.md) that takes an "information gain" (infogain) matrix specifying the "value" of all label pairs.
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A generalization of [MultinomialLogisticLossLayer](multinomiallogisticloss.html) that takes an "information gain" (infogain) matrix specifying the "value" of all label pairs.
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Equivalent to the [MultinomialLogisticLossLayer](layers/multinomiallogisticloss.md) if the infogain matrix is the identity.
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Equivalent to the [MultinomialLogisticLossLayer](multinomiallogisticloss.html) if the infogain matrix is the identity.
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## Parameters
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‎docs/tutorial/layers/lrn.md‎

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## Parameters
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* Parameters (`Parameter lrn_param`)
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* Parameters (`LRNParameter lrn_param`)
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* From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto):
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{% highlight Protobuf %}
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{% include proto/BatchNormParameter.txt %}
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{% include proto/LRNParameter.txt %}
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{% endhighlight %}

‎docs/tutorial/layers/memorydata.md‎

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* Layer type: `MemoryData`
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* [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1MemoryDataLayer.html)
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* Header: [`./include/caffe/layers/memory_data_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/memory_data_layer.hpp)
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* CPU implementation: [`./src/caffe/layers/memory_data_layer.cpu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/memory_data_layer.cpu)
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* CPU implementation: [`./src/caffe/layers/memory_data_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/memory_data_layer.cpp)
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The memory data layer reads data directly from memory, without copying it. In order to use it, one must call `MemoryDataLayer::Reset` (from C++) or `Net.set_input_arrays` (from Python) in order to specify a source of contiguous data (as 4D row major array), which is read one batch-sized chunk at a time.
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‎docs/tutorial/layers/multinomiallogisticloss.md‎

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* Layer type: `MultinomialLogisticLoss`
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* [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1MultinomialLogisticLossLayer.html)
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* Header: [`./include/caffe/layers/multinomial_logistic_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/multinomial_logistic_loss_layer.hpp)
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* CPU implementation: [`./src/caffe/layers/multinomial_logistic_loss_layer.cpu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/multinomial_logistic_loss_layer.cpu)
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* CPU implementation: [`./src/caffe/layers/multinomial_logistic_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/multinomial_logistic_loss_layer.cpp)
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## Parameters
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‎docs/tutorial/layers/silence.md‎

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## Parameters
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* Parameters (`SilenceParameter silence_param`)
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* From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto):
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{% highlight Protobuf %}
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{% include proto/BatchNormParameter.txt %}
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{% endhighlight %}
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No parameters.

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