diff --git a/cpp/tests/unit_tests/thop/eagerMoeWorkspaceTest.cpp b/cpp/tests/unit_tests/thop/eagerMoeWorkspaceTest.cpp
index 36dbb43fe362..0e2e354ff1f1 100644
--- a/cpp/tests/unit_tests/thop/eagerMoeWorkspaceTest.cpp
+++ b/cpp/tests/unit_tests/thop/eagerMoeWorkspaceTest.cpp
@@ -16,6 +16,7 @@
 #include "tensorrt_llm/thop/moe/cutlass/eagerMoeWorkspace.h"
 #include "tensorrt_llm/thop/moe/cutlass/eagerMoeWorkspaceScope.h"
 
+#include <ATen/Context.h>
 #include <ATen/cuda/CUDAContext.h>
 #include <c10/cuda/CUDACachingAllocator.h>
 #include <c10/cuda/CUDAGuard.h>
@@ -153,6 +154,8 @@ TEST(EagerMoeWorkspace, ReclamationRetriesAfterReleasingScratchUnderMemoryPressu
         GTEST_SKIP() << "Uses native allocator quota and OOM counters";
     }
     constexpr int64_t kMiB = 1024 * 1024;
+    // Allocator quota queries require PyTorch's CUDA initialization.
+    at::globalContext().lazyInitDevice(c10::DeviceType::CUDA);
     auto const device = c10::cuda::current_device();
     auto const previousLimit = c10::cuda::CUDACachingAllocator::getMemoryFraction(device);
     auto restoreLimit
@@ -205,6 +208,8 @@ TEST(EagerMoeWorkspace, ConservativeReservationOomStillAllowsSmallerActualDemand
         GTEST_SKIP() << "Uses native allocator quota and OOM counters";
     }
     constexpr int64_t kMiB = 1024 * 1024;
+    // Allocator quota queries require PyTorch's CUDA initialization.
+    at::globalContext().lazyInitDevice(c10::DeviceType::CUDA);
     auto const device = c10::cuda::current_device();
     auto const previousLimit = c10::cuda::CUDACachingAllocator::getMemoryFraction(device);
     auto restoreLimit
diff --git a/tests/unittest/_torch/executor/test_resource_manager.py b/tests/unittest/_torch/executor/test_resource_manager.py
index 4b18ca1d116f..d608d644c885 100644
--- a/tests/unittest/_torch/executor/test_resource_manager.py
+++ b/tests/unittest/_torch/executor/test_resource_manager.py
@@ -1263,6 +1263,7 @@ def _reload_ckpt_source(self, server_ckpt_source, request_ckpt_source):
             peft_cache_config=self.create_peft_cache_config(),
             lora_config=LoraConfig(lora_ckpt_source=server_ckpt_source),
             model_config=self.model_config,
+            lora_model_config=_text_lora_model_config(self.model_config),
         )
         peft_cache_manager.impl = MagicMock()
         peft_cache_manager.impl.is_task_cached.return_value = False