24 using AthAsynchronousAlgorithm::AthAsynchronousAlgorithm;
32 virtual StatusCode
execute(
const EventContext& ctx )
const override;
42 "dev/MLTest/2020-03-31/t10k-images-idx3-ubyte",
43 "Name of the input pixel file to load" };
46 Gaudi::Property<int>
m_batchSize {
this,
"BatchSize", 1,
"No. of elements/example in a batch"};
50 this,
"InferenceTool",
"AthInfer::TritonTool",
"Triton client tool"
An algorithm that can be suspended while work is offloaded to an accelerator.
Algorithm demonstrating the usage of the Triton Client API.
ToolHandle< AthInfer::IAthInferenceTool > m_tritonTool
Tool handle for the Triton client.
virtual StatusCode initialize() override
Function initialising the algorithm.
Gaudi::Property< std::string > m_pixelFileName
Name of the model file to load.
std::vector< std::vector< std::vector< float > > > m_input_tensor_values_notFlat
std::vector< float > flattenNestedVectors(const std::vector< std::vector< float > > &nestedVector) const
std::vector< std::vector< std::vector< float > > > read_mnist_pixel_notFlat(const std::string &full_path) const
virtual StatusCode execute(const EventContext &ctx) const override
Function executing the algorithm for a single event.
Gaudi::Property< int > m_batchSize
Following properties needed to be consdered if the .onnx model is evaluated in batch mode.