method_meta add uses_backend function (pytorch#8198)

Summary:

For a runtime that supports models of a couple different types it helps to be able to check ahead of time whether certain backend types are present. In our case, there are processors that can use this information to make scheduling decisions without having the actual required backend implementations present.

Differential Revision: D69143825

Author: cmt0

runtime/executor/method_meta.cpp

@@ -248,5 +248,16 @@ size_t MethodMeta::num_instructions() const {
   return num_instructions;
 }
 
+bool MethodMeta::uses_backend(const char* backend_name) const {
+  const auto delegates = s_plan_->delegates();
+  for (size_t i = 0; i < delegates->size(); i++) {
+    auto delegate = delegates->Get(i);
+    if (strcmp(delegate->id()->c_str(), backend_name) == 0) {
+      return true;
+    }
+  }
+  return false;
+}
+
 } // namespace runtime
 } // namespace executorch

runtime/executor/method_meta.h

@@ -192,6 +192,13 @@ class MethodMeta final {
    */
   ET_EXPERIMENTAL size_t num_instructions() const;
 
+  /**
+   * Check to see if a backend is used in this method.
+   *
+   * @returns true if a backend is used in this method, otherwise false.
+   */
+  ET_EXPERIMENTAL bool uses_backend(const char* backend_name) const;
+
   /**
    * DEPRECATED: Use num_memory_planned_buffers() instead.
    */

runtime/executor/test/backend_integration_test.cpp

@@ -338,6 +338,10 @@ TEST_P(BackendIntegrationTest, BasicInitSucceeds) {
   Result<Program> program = Program::load(&loader.get());
   ASSERT_EQ(program.error(), Error::Ok);
 
+  auto method_meta = program->method_meta("forward");
+  EXPECT_EQ(method_meta->uses_backend(StubBackend::kName), true);
+  EXPECT_EQ(method_meta->uses_backend("INVALID_BACKEND_NAME"), false);
+
   ManagedMemoryManager mmm(kDefaultNonConstMemBytes, kDefaultRuntimeMemBytes);
   Result<Method> method_res = program->load_method("forward", &mmm.get());
   EXPECT_EQ(method_res.error(), Error::Ok);