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---
title: Softmax with Loss Layer
---
# Softmax with Loss Layer
* Layer type: `SoftmaxWithLoss`
* [Doxygen Documentation](http://caffe.berkeleyvision.org/doxygen/classcaffe_1_1SoftmaxWithLossLayer.html)
* Header: [`./include/caffe/layers/softmax_loss_layer.hpp`](https://github.com/BVLC/caffe/blob/master/include/caffe/layers/softmax_loss_layer.hpp)
* CPU implementation: [`./src/caffe/layers/softmax_loss_layer.cpp`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/softmax_loss_layer.cpp)
* CUDA GPU implementation: [`./src/caffe/layers/softmax_loss_layer.cu`](https://github.com/BVLC/caffe/blob/master/src/caffe/layers/softmax_loss_layer.cu)
The softmax loss layer computes the multinomial logistic loss of the softmax of its inputs. It's conceptually identical to a softmax layer followed by a multinomial logistic loss layer, but provides a more numerically stable gradient.
## Parameters
* Parameters (`SoftmaxParameter softmax_param`)
* From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto):
{% highlight Protobuf %}
{% include proto/SoftmaxParameter.txt %}
{% endhighlight %}
* Parameters (`LossParameter loss_param`)
* From [`./src/caffe/proto/caffe.proto`](https://github.com/BVLC/caffe/blob/master/src/caffe/proto/caffe.proto):
{% highlight Protobuf %}
{% include proto/LossParameter.txt %}
{% endhighlight %}
## See also
* [Softmax layer](softmax.html)
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