diff --git a/examples/Building-and-deploying-multi-stage-RecSys/01-Building-Recommender-Systems-with-Merlin.ipynb b/examples/Building-and-deploying-multi-stage-RecSys/01-Building-Recommender-Systems-with-Merlin.ipynb
index 3dbe42dc5..9a0038917 100644
--- a/examples/Building-and-deploying-multi-stage-RecSys/01-Building-Recommender-Systems-with-Merlin.ipynb
+++ b/examples/Building-and-deploying-multi-stage-RecSys/01-Building-Recommender-Systems-with-Merlin.ipynb
@@ -146,7 +146,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "2023-06-29 19:20:02.816099: 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",
+ "2023-06-29 19:49:32.836544: 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",
"/usr/local/lib/python3.8/dist-packages/merlin/dtypes/mappings/torch.py:43: UserWarning: PyTorch dtype mappings did not load successfully due to an error: No module named 'torch'\n",
" warn(f\"PyTorch dtype mappings did not load successfully due to an error: {exc.msg}\")\n"
@@ -167,12 +167,12 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "2023-06-29 19:20:07.245419: 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",
+ "2023-06-29 19:49:37.094972: 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",
- "2023-06-29 19:20:08.267091: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
- "2023-06-29 19:20:08.267138: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 24576 MB memory: -> device: 0, name: Quadro RTX 8000, pci bus id: 0000:15:00.0, compute capability: 7.5\n",
- "2023-06-29 19:20:08.268109: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
- "2023-06-29 19:20:08.268137: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 24576 MB memory: -> device: 1, name: Quadro RTX 8000, pci bus id: 0000:2d:00.0, compute capability: 7.5\n",
+ "2023-06-29 19:49:38.134481: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
+ "2023-06-29 19:49:38.134526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 24576 MB memory: -> device: 0, name: Quadro RTX 8000, pci bus id: 0000:15:00.0, compute capability: 7.5\n",
+ "2023-06-29 19:49:38.135533: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
+ "2023-06-29 19:49:38.135562: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 24576 MB memory: -> device: 1, name: Quadro RTX 8000, pci bus id: 0000:2d:00.0, compute capability: 7.5\n",
"/usr/local/lib/python3.8/dist-packages/tqdm/auto.py:21: 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"
]
@@ -235,7 +235,7 @@
"DATA_FOLDER = os.environ.get(\"DATA_FOLDER\", \"/workspace/data/\")\n",
"# set up the base dir for feature store\n",
"BASE_DIR = os.environ.get(\n",
- " \"BASE_DIR\", \"/raid/workshared/merlin/examples/Building-and-deploying-multi-stage-RecSys/\"\n",
+ " \"BASE_DIR\", \"/Merlin/examples/Building-and-deploying-multi-stage-RecSys/\"\n",
")"
]
},
@@ -424,7 +424,7 @@
"
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" 6 | \n",
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+ " 590 | \n",
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@@ -433,11 +433,11 @@
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- " 2023-06-29 19:20:20.311986 | \n",
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+ " 171 | \n",
+ " 293 | \n",
+ " 31 | \n",
+ " 2023-06-29 19:49:50.300270 | \n",
+ " 2023-06-29 19:49:50.303330 | \n",
"
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" \n",
"\n",
@@ -445,16 +445,16 @@
],
"text/plain": [
" user_id user_shops user_profile user_group user_gender user_age \\\n",
- "6 7 530 1 1 1 1 \n",
+ "6 7 590 1 1 1 1 \n",
"\n",
" user_consumption_1 user_consumption_2 user_is_occupied user_geography \\\n",
"6 1 1 1 1 \n",
"\n",
" user_intentions user_brands user_categories datetime \\\n",
- "6 154 264 28 2023-06-29 19:20:20.311986 \n",
+ "6 171 293 31 2023-06-29 19:49:50.300270 \n",
"\n",
" created \n",
- "6 2023-06-29 19:20:20.314307 "
+ "6 2023-06-29 19:49:50.303330 "
]
},
"execution_count": 11,
@@ -549,48 +549,48 @@
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" 1 | \n",
" 1 | \n",
- " 2023-06-29 19:20:20.413296 | \n",
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+ " 6 | \n",
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+ " 2023-06-29 19:49:50.412307 | \n",
"
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+ " 12 | \n",
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+ " 284 | \n",
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"
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+ " 18 | \n",
+ " 1236 | \n",
+ " 426 | \n",
+ " 197 | \n",
+ " 2023-06-29 19:49:50.410715 | \n",
+ " 2023-06-29 19:49:50.412307 | \n",
"
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- " 26 | \n",
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- " 2023-06-29 19:20:20.414521 | \n",
+ " 24 | \n",
+ " 1648 | \n",
+ " 568 | \n",
+ " 263 | \n",
+ " 2023-06-29 19:49:50.410715 | \n",
+ " 2023-06-29 19:49:50.412307 | \n",
"
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" \n",
"\n",
@@ -599,17 +599,17 @@
"text/plain": [
" item_id item_category item_shop item_brand item_intention \\\n",
"0 1 1 1 1 1 \n",
- "1 2 7 457 158 73 \n",
- "2 3 13 914 315 146 \n",
- "3 4 20 1371 473 219 \n",
- "4 5 26 1828 630 292 \n",
+ "1 2 6 412 142 66 \n",
+ "2 3 12 824 284 132 \n",
+ "3 4 18 1236 426 197 \n",
+ "4 5 24 1648 568 263 \n",
"\n",
" datetime created \n",
- "0 2023-06-29 19:20:20.413296 2023-06-29 19:20:20.414521 \n",
- "1 2023-06-29 19:20:20.413296 2023-06-29 19:20:20.414521 \n",
- "2 2023-06-29 19:20:20.413296 2023-06-29 19:20:20.414521 \n",
- "3 2023-06-29 19:20:20.413296 2023-06-29 19:20:20.414521 \n",
- "4 2023-06-29 19:20:20.413296 2023-06-29 19:20:20.414521 "
+ "0 2023-06-29 19:49:50.410715 2023-06-29 19:49:50.412307 \n",
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+ "2 2023-06-29 19:49:50.410715 2023-06-29 19:49:50.412307 \n",
+ "3 2023-06-29 19:49:50.410715 2023-06-29 19:49:50.412307 \n",
+ "4 2023-06-29 19:49:50.410715 2023-06-29 19:49:50.412307 "
]
},
"execution_count": 15,
@@ -890,13 +890,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "9/9 [==============================] - 10s 275ms/step - loss: 8.9538 - recall_at_10: 0.0055 - ndcg_at_10: 0.0038 - regularization_loss: 0.0000e+00 - loss_batch: 8.8710 - val_loss: 8.9181 - val_recall_at_10: 0.0165 - val_ndcg_at_10: 0.0109 - val_regularization_loss: 0.0000e+00 - val_loss_batch: 8.5802\n"
+ "9/9 [==============================] - 11s 275ms/step - loss: 8.9538 - recall_at_10: 0.0101 - ndcg_at_10: 0.0067 - regularization_loss: 0.0000e+00 - loss_batch: 8.8711 - val_loss: 8.9179 - val_recall_at_10: 0.0212 - val_ndcg_at_10: 0.0155 - val_regularization_loss: 0.0000e+00 - val_loss_batch: 8.5806\n"
]
},
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 26,
@@ -1038,13 +1038,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "5/5 [==============================] - 5s 312ms/step - loss: 0.6931 - auc: 0.4991 - regularization_loss: 0.0000e+00 - loss_batch: 0.6932 - val_loss: 0.6931 - val_auc: 0.4983 - val_regularization_loss: 0.0000e+00 - val_loss_batch: 0.6931\n"
+ "5/5 [==============================] - 5s 305ms/step - loss: 0.6932 - auc: 0.5005 - regularization_loss: 0.0000e+00 - loss_batch: 0.6932 - val_loss: 0.6931 - val_auc: 0.5029 - val_regularization_loss: 0.0000e+00 - val_loss_batch: 0.6931\n"
]
},
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 31,
@@ -1067,7 +1067,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 32,
"id": "00447c12-ea80-4d98-ab47-cc1a982a6958",
"metadata": {},
"outputs": [],
@@ -1093,7 +1093,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 33,
"id": "e62f65f8-e8f1-447e-9500-5960807c36f2",
"metadata": {},
"outputs": [],
@@ -1107,17 +1107,86 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 34,
"id": "e02f0957-6665-400a-80c0-60b307466caf",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
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+ "
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+ "453 945 [0.012117806822061539, -0.02241620607674122, 0...\n",
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+ "457 1469 [0.012117806822061539, -0.02241620607674122, 0..."
+ ]
+ },
+ "execution_count": 34,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"item_embeddings.tail()"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 35,
"id": "66d7271e-0ea6-4568-ac5a-04089735f542",
"metadata": {},
"outputs": [],
@@ -1144,7 +1213,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 36,
"id": "4ee27d67-e35a-42c5-8025-ed73f35c8e13",
"metadata": {},
"outputs": [],
@@ -1195,7 +1264,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 37,
"id": "48a5927c-840d-410c-8f5b-bebce4f79640",
"metadata": {},
"outputs": [],
@@ -1246,10 +1315,19 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 38,
"id": "57133c1e-18d9-4ccb-9704-cdebd271985e",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Requirement already satisfied: seedir in /usr/local/lib/python3.8/dist-packages (0.4.2)\n",
+ "Requirement already satisfied: natsort in /usr/local/lib/python3.8/dist-packages (from seedir) (8.4.0)\n"
+ ]
+ }
+ ],
"source": [
"# install seedir\n",
"!pip install seedir"
@@ -1257,10 +1335,33 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 39,
"id": "986d53ea-c946-4046-a390-6d3b8801d280",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "feast_repo/\n",
+ "├─README.md\n",
+ "├─__init__.py\n",
+ "└─feature_repo/\n",
+ " ├─__init__.py\n",
+ " ├─__pycache__/\n",
+ " │ ├─__init__.cpython-38.pyc\n",
+ " │ ├─example_repo.cpython-38.pyc\n",
+ " │ └─test_workflow.cpython-38.pyc\n",
+ " ├─data/\n",
+ " │ ├─item_features.parquet\n",
+ " │ └─user_features.parquet\n",
+ " ├─feature_store.yaml\n",
+ " ├─item_features.py\n",
+ " ├─test_workflow.py\n",
+ " └─user_features.py\n"
+ ]
+ }
+ ],
"source": [
"import seedir as sd\n",
"\n",
diff --git a/examples/Building-and-deploying-multi-stage-RecSys/02-Deploying-multi-stage-RecSys-with-Merlin-Systems.ipynb b/examples/Building-and-deploying-multi-stage-RecSys/02-Deploying-multi-stage-RecSys-with-Merlin-Systems.ipynb
index 3d1d417b0..15f0060d3 100644
--- a/examples/Building-and-deploying-multi-stage-RecSys/02-Deploying-multi-stage-RecSys-with-Merlin-Systems.ipynb
+++ b/examples/Building-and-deploying-multi-stage-RecSys/02-Deploying-multi-stage-RecSys-with-Merlin-Systems.ipynb
@@ -99,7 +99,7 @@
" _descriptor.FieldDescriptor(\n",
"/usr/local/lib/python3.8/dist-packages/cudf/utils/metadata/orc_column_statistics_pb2.py:30: DeprecationWarning: Call to deprecated create function Descriptor(). Note: Create unlinked descriptors is going to go away. Please use get/find descriptors from generated code or query the descriptor_pool.\n",
" _INTEGERSTATISTICS = _descriptor.Descriptor(\n",
- "2023-06-29 19:13:17.254704: 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",
+ "2023-06-29 19:50:56.885234: 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",
"/usr/local/lib/python3.8/dist-packages/tensorflow/core/framework/tensor_shape_pb2.py:18: DeprecationWarning: Call to deprecated create function FileDescriptor(). Note: Create unlinked descriptors is going to go away. Please use get/find descriptors from generated code or query the descriptor_pool.\n",
" DESCRIPTOR = _descriptor.FileDescriptor(\n",
@@ -186,10 +186,10 @@
"output_type": "stream",
"text": [
"/raid/workshared/merlin/examples/Building-and-deploying-multi-stage-RecSys/feast_repo/feature_repo\n",
- "Created entity \u001b[1m\u001b[32mitem_id\u001b[0m\n",
"Created entity \u001b[1m\u001b[32muser_id\u001b[0m\n",
- "Created feature view \u001b[1m\u001b[32mitem_features\u001b[0m\n",
+ "Created entity \u001b[1m\u001b[32mitem_id\u001b[0m\n",
"Created feature view \u001b[1m\u001b[32muser_features\u001b[0m\n",
+ "Created feature view \u001b[1m\u001b[32mitem_features\u001b[0m\n",
"\n",
"Created sqlite table \u001b[1m\u001b[32mfeast_repo_item_features\u001b[0m\n",
"Created sqlite table \u001b[1m\u001b[32mfeast_repo_user_features\u001b[0m\n",
@@ -228,10 +228,10 @@
"text": [
"Materializing \u001b[1m\u001b[32m2\u001b[0m feature views from \u001b[1m\u001b[32m1995-01-01 01:01:01+00:00\u001b[0m to \u001b[1m\u001b[32m2025-01-01 01:01:01+00:00\u001b[0m into the \u001b[1m\u001b[32msqlite\u001b[0m online store.\n",
"\n",
- "\u001b[1m\u001b[32mitem_features\u001b[0m:\n",
- "100%|███████████████████████████████████████████████████████████| 450/450 [00:00<00:00, 5815.84it/s]\n",
"\u001b[1m\u001b[32muser_features\u001b[0m:\n",
- "100%|███████████████████████████████████████████████████████████| 448/448 [00:00<00:00, 1758.64it/s]\n"
+ "100%|███████████████████████████████████████████████████████████| 460/460 [00:00<00:00, 2521.27it/s]\n",
+ "\u001b[1m\u001b[32mitem_features\u001b[0m:\n",
+ "100%|███████████████████████████████████████████████████████████| 458/458 [00:00<00:00, 3335.12it/s]\n"
]
}
],
@@ -338,7 +338,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 9,
"id": "0b6cc5bf-d07c-4963-a748-6e2b4827ee36",
"metadata": {},
"outputs": [
@@ -346,7 +346,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "WARNING clustering 450 points to 32 centroids: please provide at least 1248 training points\n"
+ "WARNING clustering 458 points to 32 centroids: please provide at least 1248 training points\n"
]
}
],
@@ -354,7 +354,7 @@
"from merlin.systems.dag.ops.faiss import QueryFaiss, setup_faiss \n",
"\n",
"item_embeddings = pd.read_parquet(os.path.join(BASE_DIR, \"item_embeddings.parquet\"))\n",
- "setup_faiss(item_embeddings, faiss_index_path)"
+ "setup_faiss(item_embeddings, faiss_index_path, embedding_column=\"output_1\")"
]
},
{
@@ -367,7 +367,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 10,
"id": "3bc00e04-c70c-4882-9952-66f4dbb97bdc",
"metadata": {},
"outputs": [],
@@ -385,7 +385,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 11,
"id": "3decbe7b-03e3-4978-baac-03f6a0b078c9",
"metadata": {},
"outputs": [
@@ -393,9 +393,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Materializing \u001b[1m\u001b[32m1\u001b[0m feature views to \u001b[1m\u001b[32m2023-06-29 19:14:10+00:00\u001b[0m into the \u001b[1m\u001b[32msqlite\u001b[0m online store.\n",
+ "Materializing \u001b[1m\u001b[32m1\u001b[0m feature views to \u001b[1m\u001b[32m2023-06-29 19:51:06+00:00\u001b[0m into the \u001b[1m\u001b[32msqlite\u001b[0m online store.\n",
"\n",
- "\u001b[1m\u001b[32muser_features\u001b[0m from \u001b[1m\u001b[32m2025-01-01 01:01:01+00:00\u001b[0m to \u001b[1m\u001b[32m2023-06-29 19:14:10+00:00\u001b[0m:\n"
+ "\u001b[1m\u001b[32muser_features\u001b[0m from \u001b[1m\u001b[32m2025-01-01 01:01:01+00:00\u001b[0m to \u001b[1m\u001b[32m2023-06-29 19:51:06+00:00\u001b[0m:\n"
]
},
{
@@ -419,7 +419,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 12,
"id": "f11299b6-20d4-4687-bb0e-b855a9bcb9eb",
"metadata": {},
"outputs": [],
@@ -441,7 +441,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 13,
"id": "21139caa-3a51-42e6-b006-21a92c95f1bc",
"metadata": {},
"outputs": [
@@ -451,7 +451,7 @@
""
]
},
- "execution_count": 14,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -466,7 +466,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 14,
"id": "47c2d9b1-51dc-4549-977d-d7941ee6486c",
"metadata": {},
"outputs": [
@@ -474,10 +474,10 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "2023-06-29 19:14:11.423802: 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",
+ "2023-06-29 19:51:07.269579: 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",
- "2023-06-29 19:14:14.615977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 24576 MB memory: -> device: 0, name: Quadro RTX 8000, pci bus id: 0000:15:00.0, compute capability: 7.5\n",
- "2023-06-29 19:14:14.616886: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 24576 MB memory: -> device: 1, name: Quadro RTX 8000, pci bus id: 0000:2d:00.0, compute capability: 7.5\n",
+ "2023-06-29 19:51:10.430459: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 24576 MB memory: -> device: 0, name: Quadro RTX 8000, pci bus id: 0000:15:00.0, compute capability: 7.5\n",
+ "2023-06-29 19:51:10.431356: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1621] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 24576 MB memory: -> device: 1, name: Quadro RTX 8000, pci bus id: 0000:2d:00.0, compute capability: 7.5\n",
"WARNING:absl:Found untraced functions such as restored_function_body, restored_function_body, restored_function_body, restored_function_body, restored_function_body while saving (showing 5 of 52). These functions will not be directly callable after loading.\n"
]
},
@@ -485,14 +485,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO:tensorflow:Assets written to: /tmp/tmpqzazhnjq/assets\n"
+ "INFO:tensorflow:Assets written to: /tmp/tmpdalflmaz/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
- "INFO:tensorflow:Assets written to: /tmp/tmpqzazhnjq/assets\n"
+ "INFO:tensorflow:Assets written to: /tmp/tmpdalflmaz/assets\n"
]
}
],
@@ -517,7 +517,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 15,
"id": "b270f663-0ae1-4356-acd4-5f8c986abf4d",
"metadata": {},
"outputs": [
@@ -525,9 +525,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Materializing \u001b[1m\u001b[32m1\u001b[0m feature views to \u001b[1m\u001b[32m2023-06-29 19:14:18+00:00\u001b[0m into the \u001b[1m\u001b[32msqlite\u001b[0m online store.\n",
+ "Materializing \u001b[1m\u001b[32m1\u001b[0m feature views to \u001b[1m\u001b[32m2023-06-29 19:51:14+00:00\u001b[0m into the \u001b[1m\u001b[32msqlite\u001b[0m online store.\n",
"\n",
- "\u001b[1m\u001b[32mitem_features\u001b[0m from \u001b[1m\u001b[32m2025-01-01 01:01:01+00:00\u001b[0m to \u001b[1m\u001b[32m2023-06-29 19:14:18+00:00\u001b[0m:\n"
+ "\u001b[1m\u001b[32mitem_features\u001b[0m from \u001b[1m\u001b[32m2025-01-01 01:01:01+00:00\u001b[0m to \u001b[1m\u001b[32m2023-06-29 19:51:14+00:00\u001b[0m:\n"
]
},
{
@@ -550,7 +550,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 16,
"id": "0d0a4531-665c-48a1-98a9-216c955449b7",
"metadata": {},
"outputs": [],
@@ -569,7 +569,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 17,
"id": "eb0ef434-03a5-4a36-afb9-e19a43243c64",
"metadata": {},
"outputs": [],
@@ -604,7 +604,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 18,
"id": "ce31723e-af4d-4827-bb60-3a9fafcd9da6",
"metadata": {},
"outputs": [
@@ -619,14 +619,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "INFO:tensorflow:Assets written to: /tmp/tmp6epm9p86/assets\n"
+ "INFO:tensorflow:Assets written to: /tmp/tmpqdd_jn5e/assets\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
- "INFO:tensorflow:Assets written to: /tmp/tmp6epm9p86/assets\n"
+ "INFO:tensorflow:Assets written to: /tmp/tmpqdd_jn5e/assets\n"
]
}
],
@@ -644,7 +644,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 19,
"id": "7f65598b-e3e7-4238-a73e-19d00c3deb26",
"metadata": {},
"outputs": [],
@@ -676,7 +676,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 20,
"id": "b28c452f-543c-45a4-9995-130ca6919669",
"metadata": {},
"outputs": [],
@@ -695,7 +695,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 21,
"id": "9c8b7b94-5559-4587-a272-4d9de2d53dd1",
"metadata": {},
"outputs": [],
@@ -709,7 +709,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 22,
"id": "6c64d686-aed5-42f8-b517-482b4237c69f",
"metadata": {},
"outputs": [
@@ -743,7 +743,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 23,
"id": "89182219-40a6-458c-af0e-7a8e83f364aa",
"metadata": {},
"outputs": [
@@ -872,7 +872,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 24,
"id": "d08a8975-9c32-467b-99ec-df66319f854b",
"metadata": {},
"outputs": [
@@ -905,20 +905,20 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 25,
"id": "74ec62f2-5935-45c6-8058-e1cdade6f80f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "{'ordered_ids': array([[ 52, 102, 42, 204, 312, 117, 414, 258, 14, 450]], dtype=int32),\n",
- " 'ordered_scores': array([[0.5010059 , 0.5018582 , 0.5001918 , 0.50212526, 0.5004832 ,\n",
- " 0.5006511 , 0.50049436, 0.5014268 , 0.5005215 , 0.5017036 ]],\n",
+ "{'ordered_ids': array([[100, 168, 324, 79, 361, 294, 267, 289, 397, 189]], dtype=int32),\n",
+ " 'ordered_scores': array([[0.5016385 , 0.50176895, 0.5017176 , 0.5024097 , 0.5018236 ,\n",
+ " 0.5018286 , 0.50162375, 0.5015677 , 0.50175667, 0.5014358 ]],\n",
" dtype=float32)}"
]
},
- "execution_count": 26,
+ "execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}