diff --git a/examples/usecases/accelerate-training-of-large-embedding-tables-by-LazyAdam.ipynb b/examples/usecases/accelerate-training-of-large-embedding-tables-by-LazyAdam.ipynb
index a59e5d8cd8..8d9ef54246 100644
--- a/examples/usecases/accelerate-training-of-large-embedding-tables-by-LazyAdam.ipynb
+++ b/examples/usecases/accelerate-training-of-large-embedding-tables-by-LazyAdam.ipynb
@@ -64,9 +64,15 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2022-09-28 21:36:00.826297: I tensorflow/core/platform/cpu_feature_guard.cc:194] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE3 SSE4.1 SSE4.2 AVX\n",
+      "/usr/lib/python3/dist-packages/requests/__init__.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!\n",
+      "  warnings.warn(\"urllib3 ({}) or chardet ({}) doesn't match a supported \"\n",
+      "2022-10-20 19:37:18.414599: I tensorflow/core/platform/cpu_feature_guard.cc:194] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE3 SSE4.1 SSE4.2 AVX\n",
       "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
-      "2022-09-28 21:36:03.012876: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 16255 MB memory:  -> device: 0, name: Tesla V100-SXM2-32GB-LS, pci bus id: 0000:86:00.0, compute capability: 7.0\n"
+      "2022-10-20 19:37:21.731176: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0\n",
+      "2022-10-20 19:37:21.731361: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8080 MB memory:  -> device: 0, name: Tesla V100-SXM2-16GB-N, pci bus id: 0000:0a:00.0, compute capability: 7.0\n",
+      "/usr/local/lib/python3.8/dist-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n",
+      "None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.\n"
      ]
     }
    ],
@@ -74,6 +80,7 @@
     "import os\n",
     "\n",
     "import tensorflow as tf\n",
+    "os.environ[\"TF_GPU_ALLOCATOR\"]=\"cuda_malloc_async\"\n",
     "\n",
     "import merlin.models.tf as mm\n",
     "from merlin.datasets.synthetic import generate_data\n",
diff --git a/tests/unit/torch/features/test_embedding.py b/tests/unit/torch/features/test_embedding.py
index f8416f8382..c1f8ce8b9b 100644
--- a/tests/unit/torch/features/test_embedding.py
+++ b/tests/unit/torch/features/test_embedding.py
@@ -161,6 +161,7 @@ def test_soft_embedding_invalid_embeddings_dim():
 
 
 def test_soft_embedding():
+    torch.manual_seed(0)
     embeddings_dim = 16
     num_embeddings = 64