Merge branch 'feature_wuch' into 'master'

add multi-inputs & multi-outputs support

See merge request !122

mace/dsp/hexagon_control_wrapper.cc

@@ -111,22 +111,32 @@ bool HexagonControlWrapper::SetupGraph(const NetDef& net_def) {
   }
 
   // input info
-  const InputInfo& input_info = net_def.input_info()[0];
-  input_shape_.insert(input_shape_.begin(),
-                      input_info.dims().begin(), input_info.dims().end());
-  while (input_shape_.size() < 4) {
-    input_shape_.insert(input_shape_.begin(), 1);
+  num_inputs_ = 0;
+  for (const InputInfo &input_info: net_def.input_info()) {
+    vector<index_t> input_shape;
+    input_shape.insert(input_shape.begin(),
+                       input_info.dims().begin(), input_info.dims().end());
+    while (input_shape.size() < 4) {
+      input_shape.insert(input_shape.begin(), 1);
+    }
+    input_shapes_.push_back(input_shape);
+    input_data_types_.push_back(input_info.data_type());
+    num_inputs_ += 1;
   }
-  input_data_type_ = input_info.data_type();
 
   // output info
-  const OutputInfo& output_info = net_def.output_info()[0];
-  output_shape_.insert(output_shape_.begin(),
-                       output_info.dims().begin(), output_info.dims().end());
-  while (output_shape_.size() < 4) {
-    output_shape_.insert(output_shape_.begin(), 1);
+  num_outputs_ = 0;
+  for (const OutputInfo &output_info: net_def.output_info()) {
+    vector<index_t> output_shape;
+    output_shape.insert(output_shape.begin(),
+                        output_info.dims().begin(), output_info.dims().end());
+    while (output_shape.size() < 4) {
+      output_shape.insert(output_shape.begin(), 1);
+    }
+    output_shapes_.push_back(output_shape);
+    output_data_types_.push_back(output_info.data_type());
+    num_outputs_ += 1;
   }
-  output_data_type_ = output_info.data_type();
 
   bool res =  hexagon_nn_prepare(nn_id_) == 0;
   return res;

mace/dsp/hexagon_control_wrapper.h

@@ -25,8 +25,11 @@ class HexagonControlWrapper {
   bool SetupGraph(const std::string &model_file);
   bool ExecuteGraph(const Tensor &input_tensor, Tensor *output_tensor) {
     LOG(INFO) << "Execute graph: " << nn_id_;
-    output_tensor->SetDtype(output_data_type_);
-    output_tensor->Resize(output_shape_);
+    // single input and single output
+    MACE_ASSERT(num_inputs_ == 1, "Wrong inputs num");
+    MACE_ASSERT(num_outputs_ == 1, "Wrong outputs num");
+    output_tensor->SetDtype(output_data_types_[0]);
+    output_tensor->Resize(output_shapes_[0]);
     vector<uint32_t> output_shape(4);
     uint32_t output_bytes;
     int res = hexagon_nn_execute(nn_id_,
@@ -46,13 +49,58 @@ class HexagonControlWrapper {
                                  output_tensor->raw_size(),
                                  &output_bytes);
 
-    MACE_ASSERT(output_shape == output_shape_,
+    MACE_ASSERT(output_shape == output_shapes_[0],
                 "wrong output shape inferred");
     MACE_ASSERT(output_bytes == output_tensor->raw_size(),
                 "wrong output bytes inferred.");
     return res == 0;
   };
 
+  bool ExecuteGraphNew(const Tensor *input_tensors, int num_inputs,
+                       Tensor *output_tensors, int num_outputs) {
+    LOG(INFO) << "Execute graph new: " << nn_id_;
+    MACE_ASSERT(num_inputs_ == num_inputs, "Wrong inputs num");
+    MACE_ASSERT(num_outputs_ == num_outputs, "Wrong outputs num");
+
+    hexagon_nn_tensordef *inputs = new hexagon_nn_tensordef[num_inputs];
+    hexagon_nn_tensordef *outputs = new hexagon_nn_tensordef[num_outputs];
+
+    for (int i = 0; i < num_inputs; ++i) {
+      vector<index_t> input_shape = input_tensors[i].shape();
+      inputs[i].batches = input_shape[0];
+      inputs[i].height = input_shape[1];
+      inputs[i].width = input_shape[2];
+      inputs[i].depth = input_shape[3];
+      inputs[i].data = const_cast<unsigned char *>(
+          reinterpret_cast<const unsigned char *>(input_tensors[i].raw_data()));
+      inputs[i].dataLen = input_tensors[i].raw_size();
+      inputs[i].data_valid_len = input_tensors[i].raw_size();
+      inputs[i].unused = 0;
+    }
+
+    for (int i = 0; i < num_outputs; ++i) {
+      output_tensors[i].SetDtype(output_data_types_[i]);
+      output_tensors[i].Resize(output_shapes_[i]);
+      vector<index_t> output_shape = output_tensors[0].shape();
+      outputs[i].batches = output_shape[0];
+      outputs[i].height = output_shape[1];
+      outputs[i].width = output_shape[2];
+      outputs[i].depth = output_shape[3];
+      outputs[i].data = reinterpret_cast<unsigned char *>(
+          output_tensors[i].raw_mutable_data());
+      outputs[i].dataLen = output_tensors[i].raw_size();
+      outputs[i].data_valid_len = output_tensors[i].raw_size();
+      outputs[i].unused = 0;
+    }
+
+    int res = hexagon_nn_execute_new(nn_id_, inputs, num_inputs,
+                                     outputs, num_outputs);
+
+    delete(inputs);
+    delete(outputs);
+    return res == 0;
+  };
+
   bool TeardownGraph();
   void PrintLog();
   void PrintGraph();
@@ -71,10 +119,12 @@ class HexagonControlWrapper {
   int nn_id_;
   Serializer serializer_;
 
-  vector<index_t> input_shape_;
-  vector<index_t> output_shape_;
-  DataType input_data_type_;
-  DataType output_data_type_;
+  vector<vector<index_t>> input_shapes_;
+  vector<vector<index_t>> output_shapes_;
+  vector<DataType> input_data_types_;
+  vector<DataType> output_data_types_;
+  uint32_t num_inputs_;
+  uint32_t num_outputs_;
 
  DISABLE_COPY_AND_ASSIGN(HexagonControlWrapper);
 };

mace/dsp/test/supernode_test.cc

@@ -224,7 +224,7 @@ TEST(SupernodeTest, Supernode) {
       input_data[h * 4 + w] = (uint8_t)((h == 0) ? 0 : h * 64 - 1);
   }
 
-  VLOG(0) << wrapper.ExecuteGraph(input_tensor, &output_tensor);
+  VLOG(0) << wrapper.ExecuteGraphNew(&input_tensor, 1, &output_tensor, 1);
   wrapper.PrintLog();
 
   // expect out: [[49.2095, 49.2095], [50.7905, 50.7905]]