From 00598ca84e2611cf3bbd363d4920796ce1517ff2 Mon Sep 17 00:00:00 2001
From: Evan Shelhamer <shelhamer@imaginarynumber.net>
Date: Fri, 16 Oct 2015 16:44:23 -0700
Subject: [PATCH] add InputLayer for Net input

Create an input layer to replace oddball Net `input` fields.
---
 include/caffe/layers/input_layer.hpp | 44 ++++++++++++++++++++++++++++++++++++
 src/caffe/layers/input_layer.cpp     | 27 ++++++++++++++++++++++
 src/caffe/proto/caffe.proto          | 13 +++++++++--
 3 files changed, 82 insertions(+), 2 deletions(-)
 create mode 100644 include/caffe/layers/input_layer.hpp
 create mode 100644 src/caffe/layers/input_layer.cpp

diff --git a/include/caffe/layers/input_layer.hpp b/include/caffe/layers/input_layer.hpp
new file mode 100644
index 0000000..f447267
--- /dev/null
+++ b/include/caffe/layers/input_layer.hpp
@@ -0,0 +1,44 @@
+#ifndef CAFFE_INPUT_LAYER_HPP_
+#define CAFFE_INPUT_LAYER_HPP_
+
+#include <vector>
+
+#include "caffe/blob.hpp"
+#include "caffe/layer.hpp"
+#include "caffe/proto/caffe.pb.h"
+
+namespace caffe {
+
+/**
+ * @brief Provides data to the Net by assigning tops directly.
+ *
+ * This data layer is a container that merely holds the data assigned to it;
+ * forward, backward, and reshape are all no-ops.
+ */
+template <typename Dtype>
+class InputLayer : public Layer<Dtype> {
+ public:
+  explicit InputLayer(const LayerParameter& param)
+      : Layer<Dtype>(param) {}
+  virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
+      const vector<Blob<Dtype>*>& top);
+  // Data layers should be shared by multiple solvers in parallel
+  virtual inline bool ShareInParallel() const { return true; }
+  // Data layers have no bottoms, so reshaping is trivial.
+  virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
+      const vector<Blob<Dtype>*>& top) {}
+
+  virtual inline const char* type() const { return "Input"; }
+  virtual inline int ExactNumBottomBlobs() const { return 0; }
+  virtual inline int MinTopBlobs() const { return 1; }
+
+ protected:
+  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
+      const vector<Blob<Dtype>*>& top) {}
+  virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
+      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {}
+};
+
+}  // namespace caffe
+
+#endif  // CAFFE_INPUT_LAYER_HPP_
diff --git a/src/caffe/layers/input_layer.cpp b/src/caffe/layers/input_layer.cpp
new file mode 100644
index 0000000..667d8ad
--- /dev/null
+++ b/src/caffe/layers/input_layer.cpp
@@ -0,0 +1,27 @@
+#include <vector>
+
+#include "caffe/layers/input_layer.hpp"
+
+namespace caffe {
+
+template <typename Dtype>
+void InputLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
+      const vector<Blob<Dtype>*>& top) {
+  const int num_top = top.size();
+  const InputParameter& param = this->layer_param_.input_param();
+  const int num_shape = param.shape_size();
+  CHECK(num_shape == 0 || num_shape == 1 || num_shape == num_top)
+      << "Must specify 'shape' once, once per top blob, or not at all: "
+      << num_top << " tops vs. " << num_shape << " shapes.";
+  if (num_shape > 0) {
+    for (int i = 0; i < num_top; ++i) {
+      const int shape_index = (param.shape_size() == 1) ? 0 : i;
+      top[i]->Reshape(param.shape(shape_index));
+    }
+  }
+}
+
+INSTANTIATE_CLASS(InputLayer);
+REGISTER_LAYER_CLASS(Input);
+
+}  // namespace caffe
diff --git a/src/caffe/proto/caffe.proto b/src/caffe/proto/caffe.proto
index 7edb6ae..702ce6b 100644
--- a/src/caffe/proto/caffe.proto
+++ b/src/caffe/proto/caffe.proto
@@ -306,7 +306,7 @@ message ParamSpec {
 // NOTE
 // Update the next available ID when you add a new LayerParameter field.
 //
-// LayerParameter next available layer-specific ID: 143 (last added: scale_param)
+// LayerParameter next available layer-specific ID: 144 (last added: input_param)
 message LayerParameter {
   optional string name = 1; // the layer name
   optional string type = 2; // the layer type
@@ -374,6 +374,7 @@ message LayerParameter {
   optional ImageDataParameter image_data_param = 115;
   optional InfogainLossParameter infogain_loss_param = 116;
   optional InnerProductParameter inner_product_param = 117;
+  optional InputParameter input_param = 143;
   optional LogParameter log_param = 134;
   optional LRNParameter lrn_param = 118;
   optional MemoryDataParameter memory_data_param = 119;
@@ -431,7 +432,7 @@ message LossParameter {
     // Outputs that receive the ignore label will NOT be ignored in computing
     // the normalization factor.
     FULL = 0;
-    // Divide by the total number of output locations that do not take the 
+    // Divide by the total number of output locations that do not take the
     // ignore_label.  If ignore_label is not set, this behaves like FULL.
     VALID = 1;
     // Divide by the batch size.
@@ -793,6 +794,14 @@ message InnerProductParameter {
   optional bool transpose = 6 [default = false];
 }
 
+message InputParameter {
+  // This layer produces N >= 1 top blob(s) to be assigned manually.
+  // Define N shapes to set a shape for each top.
+  // Define 1 shape to set the same shape for every top.
+  // Define no shape to defer to reshaping manually.
+  repeated BlobShape shape = 1;
+}
+
 // Message that stores parameters used by LogLayer
 message LogParameter {
   // LogLayer computes outputs y = log_base(shift + scale * x), for base > 0.
-- 
2.7.4