Support batch input in model builder

JDAI-CV · May 13, 2019 · a22c6ed · a22c6ed
1 parent da2565d
commit a22c6ed
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Showing 3 changed files with 7 additions and 5 deletions.
diff --git a/dnnlibrary/include/ModelBuilder.h b/dnnlibrary/include/ModelBuilder.h
@@ -97,8 +97,9 @@ class ModelBuilder {
     Index GetBlobIndex(const std::string &blobName);
     Shape GetBlobDim(const std::string &blobName);
     Shape GetBlobDim(Index index);
-    Index AddInput(std::string name, const uint32_t height,
-                   const uint32_t width, const uint32_t depth);
+    Index AddInput(std::string name, const uint32_t batch,
+                   const uint32_t height, const uint32_t width,
+                   const uint32_t depth);
     Index AddInput(std::string name,
                    const android::nn::wrapper::OperandType &operand_type);
     // ModelBuilder auto generated methods start

diff --git a/dnnlibrary/src/DaqReader.cpp b/dnnlibrary/src/DaqReader.cpp
@@ -170,7 +170,7 @@ void AddInputs(const DNN::Model &model, ModelBuilder &builder) {
                                      quant_info.zero_point_.value_or(0));
             builder.AddInput(input_name, operand_type);
         } else {
-            builder.AddInput(input_name, shape[1], shape[2], shape[3]);
+            builder.AddInput(input_name, shape[0], shape[1], shape[2], shape[3]);
         }
     }
 }

diff --git a/dnnlibrary/src/ModelBuilder.cpp b/dnnlibrary/src/ModelBuilder.cpp
@@ -50,10 +50,11 @@ void ModelBuilder::RegisterOperand(const std::string &name,
     operand_types_.insert({name, operand_type});
 }
 
-ModelBuilder::Index ModelBuilder::AddInput(string name, const uint32_t height,
+ModelBuilder::Index ModelBuilder::AddInput(string name, const uint32_t batch,
+                                           const uint32_t height,
                                            const uint32_t width,
                                            const uint32_t depth) {
-    const vector<uint32_t> dimen{1, width, height, depth};
+    const vector<uint32_t> dimen{batch, width, height, depth};
     return AddInput(name, {Type::TENSOR_FLOAT32, dimen});
 }