Internal MediaPipe Tasks change

PiperOrigin-RevId: 540083633

mediapipe/framework/formats/tensor.h

@@ -117,11 +117,18 @@ class Tensor {
     Shape() = default;
     Shape(std::initializer_list<int> dimensions) : dims(dimensions) {}
     Shape(const std::vector<int>& dimensions) : dims(dimensions) {}
+    Shape(std::initializer_list<int> dimensions, bool is_dynamic)
+        : dims(dimensions), is_dynamic(is_dynamic) {}
+    Shape(const std::vector<int>& dimensions, bool is_dynamic)
+        : dims(dimensions), is_dynamic(is_dynamic) {}
     int num_elements() const {
       return std::accumulate(dims.begin(), dims.end(), 1,
                              std::multiplies<int>());
     }
     std::vector<int> dims;
+    // The Tensor has dynamic rather than static shape so the TFLite interpreter
+    // needs to be reallocated. Only relevant for CPU.
+    bool is_dynamic = false;
   };
   // Quantization parameters corresponding to the zero_point and scale value
   // made available by TfLite quantized (uint8/int8) tensors.

mediapipe/framework/formats/tensor_test.cc

@@ -2,6 +2,7 @@
 
 #include <cstring>
 #include <string>
+#include <vector>
 
 #include "mediapipe/framework/port/gmock.h"
 #include "mediapipe/framework/port/gtest.h"
@@ -34,6 +35,17 @@ TEST(General, TestDataTypes) {
   EXPECT_EQ(t_bool.bytes(), t_bool.shape().num_elements() * sizeof(bool));
 }
 
+TEST(General, TestDynamic) {
+  Tensor t1(Tensor::ElementType::kFloat32, Tensor::Shape({1, 2, 3, 4}, true));
+  EXPECT_EQ(t1.shape().num_elements(), 1 * 2 * 3 * 4);
+  EXPECT_TRUE(t1.shape().is_dynamic);
+
+  std::vector<int> t2_dims = {4, 3, 2, 3};
+  Tensor t2(Tensor::ElementType::kFloat16, Tensor::Shape(t2_dims, true));
+  EXPECT_EQ(t2.shape().num_elements(), 4 * 3 * 2 * 3);
+  EXPECT_TRUE(t2.shape().is_dynamic);
+}
+
 TEST(Cpu, TestMemoryAllocation) {
   Tensor t1(Tensor::ElementType::kFloat32, Tensor::Shape{4, 3, 2, 3});
   auto v1 = t1.GetCpuWriteView();