include/caffe/common_layers.hpp

@@ -180,69 +180,6 @@ class EltwiseLayer : public Layer<Dtype> {
   bool stable_prod_grad_;
 };
 
-/**
- * @brief Takes two+ Blobs, interprets last Blob as a selector and
- *  filter remaining Blobs accordingly with selector data (0 means that
- * the corresponding item has to be filtered, non-zero means that corresponding
- * item needs to stay).
- */
-template <typename Dtype>
-class FilterLayer : public Layer<Dtype> {
- public:
-  explicit FilterLayer(const LayerParameter& param)
-      : Layer<Dtype>(param) {}
-  virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
-      const vector<Blob<Dtype>*>& top);
-  virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
-      const vector<Blob<Dtype>*>& top);
-
-  virtual inline const char* type() const { return "Filter"; }
-  virtual inline int MinBottomBlobs() const { return 2; }
-  virtual inline int MinTopBlobs() const { return 1; }
-
- protected:
-  /**
-   * @param bottom input Blob vector (length 2+)
-   *   -# @f$ (N \times C \times H \times W) @f$
-   *      the inputs to be filtered @f$ x_1 @f$
-   *   -# ...
-   *   -# @f$ (N \times C \times H \times W) @f$
-   *      the inputs to be filtered @f$ x_K @f$
-   *   -# @f$ (N \times 1 \times 1 \times 1) @f$
-   *      the selector blob
-   * @param top output Blob vector (length 1+)
-   *   -# @f$ (S \times C \times H \times W) @f$ () 
-   *        the filtered output @f$ x_1 @f$ 
-   *        where S is the number of items
-   *        that haven't been filtered
-   *      @f$ (S \times C \times H \times W) @f$
-   *        the filtered output @f$ x_K @f$ 
-   *        where S is the number of items
-   *        that haven't been filtered
-   */
-  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
-      const vector<Blob<Dtype>*>& top);
-  virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
-    const vector<Blob<Dtype>*>& top);
-
-  /**
-   * @brief Computes the error gradient w.r.t. the forwarded inputs.
-   *
-   * @param top output Blob vector (length 1+), providing the error gradient with
-   *        respect to the outputs
-   * @param propagate_down see Layer::Backward.
-   * @param bottom input Blob vector (length 2+), into which the top error
-   *        gradient is copied
-   */
-  virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
-      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
-  virtual void Backward_gpu(const vector<Blob<Dtype>*>& top,
-    const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
-
-  bool first_reshape_;
-  vector<int> indices_to_forward_;
-};
-
 /**
  * @brief Reshapes the input Blob into flat vectors.
  *