Merge pull request #3863 from lukeyeager/bvlc/expose-all-netstate-opt…

…ions

Expose all netstate options (for all-in-one nets)

include/caffe/net.hpp

@@ -25,6 +25,7 @@ class Net {
  public:
   explicit Net(const NetParameter& param, const Net* root_net = NULL);
   explicit Net(const string& param_file, Phase phase,
+      const int level = 0, const vector<string>* stages = NULL,
       const Net* root_net = NULL);
   virtual ~Net() {}
 

python/caffe/_caffe.cpp

@@ -86,19 +86,42 @@ void CheckContiguousArray(PyArrayObject* arr, string name,
   }
 }
 
-// Net constructor for passing phase as int
-shared_ptr<Net<Dtype> > Net_Init(
-    string param_file, int phase) {
-  CheckFile(param_file);
+// Net constructor
+shared_ptr<Net<Dtype> > Net_Init(string network_file, int phase,
+    const int level, const bp::object& stages,
+    const bp::object& weights) {
+  CheckFile(network_file);
+
+  // Convert stages from list to vector
+  vector<string> stages_vector;
+  if (!stages.is_none()) {
+    for (int i = 0; i < len(stages); i++) {
+      stages_vector.push_back(bp::extract<string>(stages[i]));
+    }
+  }
+
+  // Initialize net
+  shared_ptr<Net<Dtype> > net(new Net<Dtype>(network_file,
+        static_cast<Phase>(phase), level, &stages_vector));
+
+  // Load weights
+  if (!weights.is_none()) {
+    std::string weights_file_str = bp::extract<std::string>(weights);
+    CheckFile(weights_file_str);
+    net->CopyTrainedLayersFrom(weights_file_str);
+  }
 
-  shared_ptr<Net<Dtype> > net(new Net<Dtype>(param_file,
-      static_cast<Phase>(phase)));
   return net;
 }
 
-// Net construct-and-load convenience constructor
+// Legacy Net construct-and-load convenience constructor
 shared_ptr<Net<Dtype> > Net_Init_Load(
     string param_file, string pretrained_param_file, int phase) {
+  LOG(WARNING) << "DEPRECATION WARNING - deprecated use of Python interface";
+  LOG(WARNING) << "Use this instead (with the named \"weights\""
+    << " parameter):";
+  LOG(WARNING) << "Net('" << param_file << "', " << phase
+    << ", weights='" << pretrained_param_file << "')";
   CheckFile(param_file);
   CheckFile(pretrained_param_file);
 
@@ -266,7 +289,12 @@ BOOST_PYTHON_MODULE(_caffe) {
 
   bp::class_<Net<Dtype>, shared_ptr<Net<Dtype> >, boost::noncopyable >("Net",
     bp::no_init)
-    .def("__init__", bp::make_constructor(&Net_Init))
+    // Constructor
+    .def("__init__", bp::make_constructor(&Net_Init,
+          bp::default_call_policies(), (bp::arg("network_file"), "phase",
+            bp::arg("level")=0, bp::arg("stages")=bp::object(),
+            bp::arg("weights")=bp::object())))
+    // Legacy constructor
     .def("__init__", bp::make_constructor(&Net_Init_Load))
     .def("_forward", &Net<Dtype>::ForwardFromTo)
     .def("_backward", &Net<Dtype>::BackwardFromTo)

python/caffe/test/test_net.py

@@ -72,7 +72,11 @@ def test_save_and_read(self):
         f.close()
         self.net.save(f.name)
         net_file = simple_net_file(self.num_output)
-        net2 = caffe.Net(net_file, f.name, caffe.TRAIN)
+        # Test legacy constructor
+        #   should print deprecation warning
+        caffe.Net(net_file, f.name, caffe.TRAIN)
+        # Test named constructor
+        net2 = caffe.Net(net_file, caffe.TRAIN, weights=f.name)
         os.remove(net_file)
         os.remove(f.name)
         for name in self.net.params:
@@ -93,3 +97,225 @@ def test_save_hdf5(self):
             for i in range(len(self.net.params[name])):
                 self.assertEqual(abs(self.net.params[name][i].data
                     - net2.params[name][i].data).sum(), 0)
+
+class TestLevels(unittest.TestCase):
+
+    TEST_NET = """
+layer {
+  name: "data"
+  type: "DummyData"
+  top: "data"
+  dummy_data_param { shape { dim: 1 dim: 1 dim: 10 dim: 10 } }
+}
+layer {
+  name: "NoLevel"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "NoLevel"
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "Level0Only"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "Level0Only"
+  include { min_level: 0 max_level: 0 }
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "Level1Only"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "Level1Only"
+  include { min_level: 1 max_level: 1 }
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "Level>=0"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "Level>=0"
+  include { min_level: 0 }
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "Level>=1"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "Level>=1"
+  include { min_level: 1 }
+  inner_product_param { num_output: 1 }
+}
+"""
+
+    def setUp(self):
+        self.f = tempfile.NamedTemporaryFile(mode='w+')
+        self.f.write(self.TEST_NET)
+        self.f.flush()
+
+    def tearDown(self):
+        self.f.close()
+
+    def check_net(self, net, blobs):
+        net_blobs = [b for b in net.blobs.keys() if 'data' not in b]
+        self.assertEqual(net_blobs, blobs)
+
+    def test_0(self):
+        net = caffe.Net(self.f.name, caffe.TEST)
+        self.check_net(net, ['NoLevel', 'Level0Only', 'Level>=0'])
+
+    def test_1(self):
+        net = caffe.Net(self.f.name, caffe.TEST, level=1)
+        self.check_net(net, ['NoLevel', 'Level1Only', 'Level>=0', 'Level>=1'])
+
+
+class TestStages(unittest.TestCase):
+
+    TEST_NET = """
+layer {
+  name: "data"
+  type: "DummyData"
+  top: "data"
+  dummy_data_param { shape { dim: 1 dim: 1 dim: 10 dim: 10 } }
+}
+layer {
+  name: "A"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "A"
+  include { stage: "A" }
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "B"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "B"
+  include { stage: "B" }
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "AorB"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "AorB"
+  include { stage: "A" }
+  include { stage: "B" }
+  inner_product_param { num_output: 1 }
+}
+layer {
+  name: "AandB"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "AandB"
+  include { stage: "A" stage: "B" }
+  inner_product_param { num_output: 1 }
+}
+"""
+
+    def setUp(self):
+        self.f = tempfile.NamedTemporaryFile(mode='w+')
+        self.f.write(self.TEST_NET)
+        self.f.flush()
+
+    def tearDown(self):
+        self.f.close()
+
+    def check_net(self, net, blobs):
+        net_blobs = [b for b in net.blobs.keys() if 'data' not in b]
+        self.assertEqual(net_blobs, blobs)
+
+    def test_A(self):
+        net = caffe.Net(self.f.name, caffe.TEST, stages=['A'])
+        self.check_net(net, ['A', 'AorB'])
+
+    def test_B(self):
+        net = caffe.Net(self.f.name, caffe.TEST, stages=['B'])
+        self.check_net(net, ['B', 'AorB'])
+
+    def test_AandB(self):
+        net = caffe.Net(self.f.name, caffe.TEST, stages=['A', 'B'])
+        self.check_net(net, ['A', 'B', 'AorB', 'AandB'])
+
+
+class TestAllInOne(unittest.TestCase):
+
+    TEST_NET = """
+layer {
+  name: "train_data"
+  type: "DummyData"
+  top: "data"
+  top: "label"
+  dummy_data_param {
+    shape { dim: 1 dim: 1 dim: 10 dim: 10 }
+    shape { dim: 1 dim: 1 dim: 1 dim: 1 }
+  }
+  include { phase: TRAIN stage: "train" }
+}
+layer {
+  name: "val_data"
+  type: "DummyData"
+  top: "data"
+  top: "label"
+  dummy_data_param {
+    shape { dim: 1 dim: 1 dim: 10 dim: 10 }
+    shape { dim: 1 dim: 1 dim: 1 dim: 1 }
+  }
+  include { phase: TEST stage: "val" }
+}
+layer {
+  name: "deploy_data"
+  type: "Input"
+  top: "data"
+  input_param { shape { dim: 1 dim: 1 dim: 10 dim: 10 } }
+  include { phase: TEST stage: "deploy" }
+}
+layer {
+  name: "ip"
+  type: "InnerProduct"
+  bottom: "data"
+  top: "ip"
+  inner_product_param { num_output: 2 }
+}
+layer {
+  name: "loss"
+  type: "SoftmaxWithLoss"
+  bottom: "ip"
+  bottom: "label"
+  top: "loss"
+  include: { phase: TRAIN stage: "train" }
+  include: { phase: TEST stage: "val" }
+}
+layer {
+  name: "pred"
+  type: "Softmax"
+  bottom: "ip"
+  top: "pred"
+  include: { phase: TEST stage: "deploy" }
+}
+"""
+
+    def setUp(self):
+        self.f = tempfile.NamedTemporaryFile(mode='w+')
+        self.f.write(self.TEST_NET)
+        self.f.flush()
+
+    def tearDown(self):
+        self.f.close()
+
+    def check_net(self, net, outputs):
+        self.assertEqual(list(net.blobs['data'].shape), [1,1,10,10])
+        self.assertEqual(net.outputs, outputs)
+
+    def test_train(self):
+        net = caffe.Net(self.f.name, caffe.TRAIN, stages=['train'])
+        self.check_net(net, ['loss'])
+
+    def test_val(self):
+        net = caffe.Net(self.f.name, caffe.TEST, stages=['val'])
+        self.check_net(net, ['loss'])
+
+    def test_deploy(self):
+        net = caffe.Net(self.f.name, caffe.TEST, stages=['deploy'])
+        self.check_net(net, ['pred'])
+

src/caffe/net.cpp

@@ -28,11 +28,20 @@ Net<Dtype>::Net(const NetParameter& param, const Net* root_net)
 }
 
 template <typename Dtype>
-Net<Dtype>::Net(const string& param_file, Phase phase, const Net* root_net)
+Net<Dtype>::Net(const string& param_file, Phase phase,
+    const int level, const vector<string>* stages,
+    const Net* root_net)
     : root_net_(root_net) {
   NetParameter param;
   ReadNetParamsFromTextFileOrDie(param_file, &param);
+  // Set phase, stages and level
   param.mutable_state()->set_phase(phase);
+  if (stages != NULL) {
+    for (int i = 0; i < stages->size(); i++) {
+      param.mutable_state()->add_stage((*stages)[i]);
+    }
+  }
+  param.mutable_state()->set_level(level);
   Init(param);
 }