Modular model definitions

.gitignore

@@ -79,6 +79,10 @@ docs/dev
 
 # Eclipse Project settings
 *.*project
+.settings
 
 # CMake generated files
 *.gen.cmake
+
+# OSX files
+.DS_Store

Makefile

@@ -4,8 +4,8 @@ CONFIG_FILE := Makefile.config
 include $(CONFIG_FILE)
 
 BUILD_DIR_LINK := $(BUILD_DIR)
-RELEASE_BUILD_DIR := .$(BUILD_DIR)_release
-DEBUG_BUILD_DIR := .$(BUILD_DIR)_debug
+RELEASE_BUILD_DIR ?= .$(BUILD_DIR)_release
+DEBUG_BUILD_DIR ?= .$(BUILD_DIR)_debug
 
 DEBUG ?= 0
 ifeq ($(DEBUG), 1)
@@ -269,7 +269,7 @@ endif
 
 # Debugging
 ifeq ($(DEBUG), 1)
-	COMMON_FLAGS += -DDEBUG -g -O0
+	COMMON_FLAGS += -DDEBUG -g -O0 -DBOOST_NOINLINE='__attribute__ ((noinline))'
 	NVCCFLAGS += -G
 else
 	COMMON_FLAGS += -DNDEBUG -O2

examples/mnist/lenet_conv_pool.prototxt

@@ -0,0 +1,30 @@
+layers {
+  name: "conv"
+  type: CONVOLUTION
+  bottom: "${bottom}"
+  top: "conv"
+  blobs_lr: 1
+  blobs_lr: 2
+  convolution_param {
+    num_output: ${num_output}
+    kernel_size: 5
+    stride: 1
+    weight_filler {
+      type: "xavier"
+    }
+    bias_filler {
+      type: "constant"
+    }
+  }
+}
+layers {
+  name: "pool"
+  type: POOLING
+  bottom: "conv"
+  top: "pool"
+  pooling_param {
+    pool: MAX
+    kernel_size: 2
+    stride: 2
+  }
+}

examples/mnist/lenet_train_test.prototxt

@@ -29,71 +29,28 @@ layers {
   }
   include: { phase: TEST }
 }
-
 layers {
-  name: "conv1"
-  type: CONVOLUTION
-  bottom: "data"
-  top: "conv1"
-  blobs_lr: 1
-  blobs_lr: 2
-  convolution_param {
-    num_output: 20
-    kernel_size: 5
-    stride: 1
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
-  }
-}
-layers {
-  name: "pool1"
-  type: POOLING
-  bottom: "conv1"
-  top: "pool1"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
-  }
-}
-layers {
-  name: "conv2"
-  type: CONVOLUTION
-  bottom: "pool1"
-  top: "conv2"
-  blobs_lr: 1
-  blobs_lr: 2
-  convolution_param {
-    num_output: 50
-    kernel_size: 5
-    stride: 1
-    weight_filler {
-      type: "xavier"
-    }
-    bias_filler {
-      type: "constant"
-    }
+  name: "cp1"
+  type: IMPORT
+  import_param {
+    net: "examples/mnist/lenet_conv_pool.prototxt"
+    var { name: "bottom" value: "/data" }
+    var { name: "num_output" value: "20" }
   }
 }
 layers {
-  name: "pool2"
-  type: POOLING
-  bottom: "conv2"
-  top: "pool2"
-  pooling_param {
-    pool: MAX
-    kernel_size: 2
-    stride: 2
+  name: "cp2"
+  type: IMPORT
+  import_param {
+    net: "examples/mnist/lenet_conv_pool.prototxt"
+    var { name: "bottom" value: "../cp1/pool" }
+    var { name: "num_output" value: "50" }
   }
 }
 layers {
   name: "ip1"
   type: INNER_PRODUCT
-  bottom: "pool2"
+  bottom: "cp2/pool"
   top: "ip1"
   blobs_lr: 1
   blobs_lr: 2

include/caffe/net.hpp

@@ -192,6 +192,13 @@ class Net {
   /// @brief Get misc parameters, e.g. the LR multiplier and weight decay.
   void GetLearningRateAndWeightDecay();
 
+  // @brief Loads imports, for modular network definitions
+  static void LoadImports(const NetParameter& source, NetParameter* target);
+  static void LoadImports(const NetParameter& source, NetParameter* target,
+      const string& pwd);
+  // @brief Resolves a layer or blob name, e.g. "../data"
+  static string ResolveImportName(const string& path, const string& pwd);
+
   /// @brief Individual layers in the net
   vector<shared_ptr<Layer<Dtype> > > layers_;
   vector<string> layer_names_;

include/caffe/util/io.hpp

@@ -88,6 +88,8 @@ inline void WriteProtoToBinaryFile(
   WriteProtoToBinaryFile(proto, filename.c_str());
 }
 
+string ReadFile(const string& filename);
+
 bool ReadFileToDatum(const string& filename, const int label, Datum* datum);
 
 inline bool ReadFileToDatum(const string& filename, Datum* datum) {

src/caffe/net.cpp

@@ -1,3 +1,6 @@
+#include <boost/algorithm/string.hpp>
+#include <google/protobuf/text_format.h>
+
 #include <algorithm>
 #include <map>
 #include <set>
@@ -15,6 +18,7 @@
 #include "caffe/util/upgrade_proto.hpp"
 
 #include "caffe/test/test_caffe_main.hpp"
+using boost::replace_all;
 
 namespace caffe {
 
@@ -32,10 +36,13 @@ Net<Dtype>::Net(const string& param_file) {
 
 template <typename Dtype>
 void Net<Dtype>::Init(const NetParameter& in_param) {
+  // Load import layers
+  NetParameter expanded(in_param);
+  LoadImports(in_param, &expanded);
   // Filter layers based on their include/exclude rules and
   // the current NetState.
   NetParameter filtered_param;
-  FilterNet(in_param, &filtered_param);
+  FilterNet(expanded, &filtered_param);
   LOG(INFO) << "Initializing net from parameters: " << std::endl
             << filtered_param.DebugString();
   // Create a copy of filtered_param with splits added where necessary.
@@ -462,6 +469,64 @@ void Net<Dtype>::AppendParam(const NetParameter& param, const int layer_id,
   }
 }
 
+template <typename Dtype>
+void Net<Dtype>::LoadImports(const NetParameter& source, NetParameter* target) {
+  target->CopyFrom(source);
+  target->clear_layers();
+  LoadImports(source, target, "");
+}
+
+template <typename Dtype>
+void Net<Dtype>::LoadImports(const NetParameter& source, NetParameter* target,
+    const string& pwd) {
+  for (int i = 0; i < source.layers_size(); ++i) {
+    if (source.layers(i).type() == LayerParameter_LayerType_IMPORT) {
+      const LayerParameter& layer = source.layers(i);
+      CHECK(layer.has_import_param()) << "Missing import_param";
+      const ImportParameter& import = layer.import_param();
+      string proto = ReadFile(import.net());
+      // Replace variables and references
+      for (int j = 0; j < import.var_size(); ++j) {
+        const Pair& p = import.var(j);
+        replace_all(proto, "${" + p.name() + "}", p.value());
+      }
+      NetParameter net;
+      bool parse = google::protobuf::TextFormat::ParseFromString(proto, &net);
+      CHECK(parse) << "Failed to parse NetParameter file: " << import.net();
+      CHECK(layer.has_name() && layer.name().length() > 0)
+          << "Import layer must have a name";
+      LoadImports(net, target, ResolveImportName(layer.name(), pwd));
+    } else {
+      LayerParameter *t = target->add_layers();
+      t->CopyFrom(source.layers(i));
+      t->set_name(ResolveImportName(t->name(), pwd));
+      for (int j = 0; j < source.layers(i).top_size(); ++j)
+        t->set_top(j, ResolveImportName(source.layers(i).top(j), pwd));
+      for (int j = 0; j < source.layers(i).bottom_size(); ++j)
+        t->set_bottom(j, ResolveImportName(source.layers(i).bottom(j), pwd));
+    }
+  }
+}
+
+template <typename Dtype>
+string Net<Dtype>::ResolveImportName(const string& path, const string& pwd) {
+  CHECK(!boost::starts_with(pwd, "/") && !boost::ends_with(pwd, "/"));
+  if (boost::starts_with(path, "/"))
+    return path.substr(1, path.size() - 1);
+  string cpath = path;
+  string cpwd = pwd;
+  while (boost::starts_with(cpath, "../")) {
+    cpath = cpath.substr(3, cpath.size() - 3);
+    size_t i = cpwd.find_last_of('/');
+    cpwd = i == string::npos ? "" : cpwd.substr(0, i);
+  }
+  if (!cpwd.size())
+    return cpath;
+  if (!cpath.size() || cpath == ".")
+    return cpwd;
+  return cpwd + '/' + cpath;
+}
+
 template <typename Dtype>
 void Net<Dtype>::GetLearningRateAndWeightDecay() {
   LOG(INFO) << "Collecting Learning Rate and Weight Decay.";

src/caffe/proto/caffe.proto

@@ -206,7 +206,7 @@ message NetStateRule {
 // NOTE
 // Update the next available ID when you add a new LayerParameter field.
 //
-// LayerParameter next available ID: 42 (last added: exp_param)
+// LayerParameter next available ID: 43 (last added: import_param)
 message LayerParameter {
   repeated string bottom = 2; // the name of the bottom blobs
   repeated string top = 3; // the name of the top blobs
@@ -227,7 +227,7 @@ message LayerParameter {
   // line above the enum. Update the next available ID when you add a new
   // LayerType.
   //
-  // LayerType next available ID: 39 (last added: EXP)
+  // LayerType next available ID: 40 (last added: IMPORT)
   enum LayerType {
     // "NONE" layer type is 0th enum element so that we don't cause confusion
     // by defaulting to an existent LayerType (instead, should usually error if
@@ -252,6 +252,7 @@ message LayerParameter {
     HINGE_LOSS = 28;
     IM2COL = 11;
     IMAGE_DATA = 12;
+    IMPORT = 39;
     INFOGAIN_LOSS = 13;
     INNER_PRODUCT = 14;
     LRN = 15;
@@ -313,6 +314,7 @@ message LayerParameter {
   optional HDF5OutputParameter hdf5_output_param = 14;
   optional HingeLossParameter hinge_loss_param = 29;
   optional ImageDataParameter image_data_param = 15;
+  optional ImportParameter import_param = 42;
   optional InfogainLossParameter infogain_loss_param = 16;
   optional InnerProductParameter inner_product_param = 17;
   optional LRNParameter lrn_param = 18;
@@ -342,6 +344,20 @@ message LayerParameter {
   optional V0LayerParameter layer = 1;
 }
 
+message Pair {
+   required string name = 1;
+   required string value = 2;
+}
+
+// Message that stores parameters used by ImportLayer
+message ImportParameter {
+    // Proto file to import
+    required string net = 1;
+    // Variable names to replace before importing the file. Variables can
+    // be used in the file in this format: ${name}
+    repeated Pair var = 2;
+}
+
 // Message that stores parameters used to apply transformation
 // to the data layer's data
 message TransformationParameter {

src/caffe/test/test_data/module.prototxt

@@ -0,0 +1,21 @@
+layers: {
+  name: 'innerproduct'
+  type: INNER_PRODUCT
+  inner_product_param {
+    num_output: ${num_output}
+    weight_filler {
+      type: 'gaussian'
+      std: 0.01
+    }
+    bias_filler {
+      type: 'constant'
+      value: 0
+    }
+  }
+  blobs_lr: 1.
+  blobs_lr: 2.
+  weight_decay: 1.
+  weight_decay: 0.
+  bottom: '../data'
+  top: 'innerproduct'
+}