Enable sharing for InferenceCalculatorGlAdvanced

Allows sharing the same instance of GpuInferenceRunner in InferenceCalculatorGlAdvanced between multiple instances in the same graph or other graphs.

PiperOrigin-RevId: 701024167

mediapipe/calculators/tensor/BUILD

@@ -633,6 +633,7 @@ cc_library(
         ":inference_io_mapper",
         ":inference_on_disk_cache_helper",
         ":tensor_span",
+        "//mediapipe/calculators/tensor:inference_runner",
         "//mediapipe/framework:calculator_framework",
         "//mediapipe/framework:mediapipe_profiling",
         "//mediapipe/framework/api2:packet",

mediapipe/calculators/tensor/inference_calculator_gl_advanced.cc

@@ -25,6 +25,7 @@
 #include "mediapipe/calculators/tensor/inference_calculator.h"
 #include "mediapipe/calculators/tensor/inference_io_mapper.h"
 #include "mediapipe/calculators/tensor/inference_on_disk_cache_helper.h"
+#include "mediapipe/calculators/tensor/inference_runner.h"
 #include "mediapipe/calculators/tensor/tensor_span.h"
 #include "mediapipe/framework/api2/packet.h"
 #include "mediapipe/framework/calculator_framework.h"
@@ -63,17 +64,17 @@ class InferenceCalculatorGlAdvancedImpl
 
  private:
   // Helper class that wraps everything related to GPU inference acceleration.
-  class GpuInferenceRunner {
+  class GpuInferenceRunner : public InferenceRunner {
    public:
     ~GpuInferenceRunner();
 
     absl::Status Init(CalculatorContext* cc,
                       std::shared_ptr<GlContext> gl_context);
 
-    absl::StatusOr<std::vector<Tensor>> Process(
-        CalculatorContext* cc, const TensorSpan& input_tensors);
+    absl::StatusOr<std::vector<Tensor>> Run(
+        CalculatorContext* cc, const TensorSpan& input_tensors) override;
 
-    const InputOutputTensorNames& GetInputOutputTensorNames() const;
+    const InputOutputTensorNames& GetInputOutputTensorNames() const override;
 
    private:
     absl::Status InitTFLiteGPURunner(
@@ -99,7 +100,7 @@ class InferenceCalculatorGlAdvancedImpl
   absl::StatusOr<std::unique_ptr<GpuInferenceRunner>> CreateInferenceRunner(
       CalculatorContext* cc);
 
-  std::unique_ptr<GpuInferenceRunner> gpu_inference_runner_;
+  std::unique_ptr<InferenceRunner> inference_runner_;
   mediapipe::GlCalculatorHelper gpu_helper_;
 };
 
@@ -141,7 +142,7 @@ absl::Status InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Init(
 }
 
 absl::StatusOr<std::vector<Tensor>>
-InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Process(
+InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::Run(
     CalculatorContext* cc, const TensorSpan& input_tensors) {
   std::vector<Tensor> output_tensors;
   for (int i = 0; i < input_tensors.size(); ++i) {
@@ -267,26 +268,25 @@ absl::Status InferenceCalculatorGlAdvancedImpl::UpdateContract(
 
 absl::Status InferenceCalculatorGlAdvancedImpl::Open(CalculatorContext* cc) {
   MP_RETURN_IF_ERROR(gpu_helper_.Open(cc));
-  gpu_inference_runner_ = std::make_unique<GpuInferenceRunner>();
-  MP_RETURN_IF_ERROR(
-      gpu_inference_runner_->Init(cc, gpu_helper_.GetSharedGlContext()));
+
+  MP_ASSIGN_OR_RETURN(inference_runner_, CreateInferenceRunner(cc));
   return InferenceCalculatorNodeImpl::UpdateIoMapping(
-      cc, gpu_inference_runner_->GetInputOutputTensorNames());
+      cc, inference_runner_->GetInputOutputTensorNames());
 }
 
 absl::StatusOr<std::vector<Tensor>> InferenceCalculatorGlAdvancedImpl::Process(
     CalculatorContext* cc, const TensorSpan& tensor_span) {
   std::vector<Tensor> output_tensors;
   MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([&]() -> absl::Status {
     MP_ASSIGN_OR_RETURN(output_tensors,
-                        gpu_inference_runner_->Process(cc, tensor_span));
+                        inference_runner_->Run(cc, tensor_span));
     return absl::OkStatus();
   }));
   return output_tensors;
 }
 
 absl::Status InferenceCalculatorGlAdvancedImpl::Close(CalculatorContext* cc) {
-  gpu_inference_runner_.reset();
+  inference_runner_.reset();
 
   return absl::OkStatus();
 }