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2 changes: 1 addition & 1 deletion jupyter_execute/hps_tf/notebooks/hierarchical_parameter_server_demo.ipynb
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"\n",
"### Get HPS from NGC\n",
"\n",
"The HPS Python module is preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"The HPS Python module is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_tf/notebooks/hps_multi_table_sparse_input_demo.ipynb
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"\n",
"### Get HPS from NGC\n",
"\n",
"The HPS Python module is preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"The HPS Python module is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_tf/notebooks/hps_pretrained_model_training_demo.ipynb
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"\n",
"### Get HPS from NGC\n",
"\n",
"The HPS Python module is preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"The HPS Python module is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_tf/notebooks/hps_table_fusion_demo.ipynb
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"\n",
"### Get HPS from NGC\n",
"\n",
"The HPS Python module is preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"The HPS Python module is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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14 changes: 7 additions & 7 deletions jupyter_execute/hps_tf/notebooks/hps_tensorflow_triton_deployment_demo.ipynb
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"\n",
"### Get HPS from NGC\n",
"\n",
"The HPS Python module is preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"The HPS Python module is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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"INFO:tensorflow:Automatic mixed precision has been deactivated.\n",
"2022-11-23 01:37:23.028482: I tensorflow/core/grappler/devices.cc:66] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
"2022-11-23 01:37:23.028568: I tensorflow/core/grappler/clusters/single_machine.cc:358] Starting new session\n",
"2022-11-23 01:37:23.121909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 30991 MB memory: -> device: 0, name: Tesla V100-SXM2-32GB, pci bus id: 0000:06:00.0, compute capability: 7.0\n",
"2022-11-23 01:37:23.128593: W tensorflow/compiler/tf2tensorrt/convert/trt_optimization_pass.cc:198] Calibration with FP32 or FP16 is not implemented. Falling back to use_calibration = False.Note that the default value of use_calibration is True.\n",
"2022-11-23 01:37:23.129761: W tensorflow/compiler/tf2tensorrt/segment/segment.cc:952] \n",
"2022-11-23 01:37:24.041909: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 30991 MB memory: -> device: 0, name: Tesla V100-SXM2-32GB, pci bus id: 0000:06:00.0, compute capability: 7.0\n",
"2022-11-23 01:37:24.048593: W tensorflow/compiler/tf2tensorrt/convert/trt_optimization_pass.cc:198] Calibration with FP32 or FP16 is not implemented. Falling back to use_calibration = False.Note that the default value of use_calibration is True.\n",
"2022-11-23 01:37:24.049761: W tensorflow/compiler/tf2tensorrt/segment/segment.cc:952] \n",
"\n",
"################################################################################\n",
"TensorRT unsupported/non-converted OP Report:\n",
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"For more information see https://docs.nvidia.com/deeplearning/frameworks/tf-trt-user-guide/index.html#supported-ops.\n",
"################################################################################\n",
"\n",
"2022-11-23 01:37:23.129860: W tensorflow/compiler/tf2tensorrt/segment/segment.cc:1280] The environment variable TF_TRT_MAX_ALLOWED_ENGINES=20 has no effect since there are only 1 TRT Engines with at least minimum_segment_size=3 nodes.\n",
"2022-11-23 01:37:23.129893: I tensorflow/compiler/tf2tensorrt/convert/convert_graph.cc:799] Number of TensorRT candidate segments: 1\n",
"2022-11-23 01:37:23.120667: I tensorflow/compiler/tf2tensorrt/convert/convert_graph.cc:916] Replaced segment 0 consisting of 9 nodes by TRTEngineOp_000_000.\n"
"2022-11-23 01:37:24.049860: W tensorflow/compiler/tf2tensorrt/segment/segment.cc:1280] The environment variable TF_TRT_MAX_ALLOWED_ENGINES=20 has no effect since there are only 1 TRT Engines with at least minimum_segment_size=3 nodes.\n",
"2022-11-23 01:37:24.049893: I tensorflow/compiler/tf2tensorrt/convert/convert_graph.cc:799] Number of TensorRT candidate segments: 1\n",
"2022-11-23 01:37:24.040667: I tensorflow/compiler/tf2tensorrt/convert/convert_graph.cc:916] Replaced segment 0 consisting of 9 nodes by TRTEngineOp_000_000.\n"
]
},
{
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_tf/notebooks/sok_to_hps_dlrm_demo.ipynb
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"\n",
"### Get SOK from NGC\n",
"\n",
"Both SOK and HPS Python modules are preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"Both SOK and HPS Python modules are preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_torch/notebooks/hps_torch_demo.ipynb
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"\n",
"### Get HPS from NGC\n",
"\n",
"The HPS Python module is preinstalled in the 23.12 and later [Merlin PyTorch Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-pytorch): `nvcr.io/nvidia/merlin/merlin-pytorch:23.12`.\n",
"The HPS Python module is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container.\n",
"\n",
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10 changes: 5 additions & 5 deletions jupyter_execute/hps_trt/notebooks/benchmark_tf_trained_large_model.ipynb
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" ```shell\n",
" git clone https://github.com/NVIDIA-Merlin/Merlin.git\n",
" cd Merlin/docker\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-base:23.12 -f dockerfile.merlin .\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-tensorflow:23.12 -f dockerfile.tf .\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-base:24.04 -f dockerfile.merlin.ctr .\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-hugectr:24.04 -f dockerfile.ctr .\n",
" cd ../..\n",
" ```\n",
"- **Option B (G+H optimized HugeCTR)**:\n",
" ```shell\n",
" git clone https://github.com/NVIDIA-Merlin/Merlin.git\n",
" cd Merlin/docker\n",
" sed -i -e 's/\" -DENABLE_INFERENCE=ON/\" -DUSE_HUGE_PAGES=ON -DENABLE_INFERENCE=ON/g' dockerfile.merlin\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-base:23.12 -f dockerfile.merlin .\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-tensorflow:23.12 -f dockerfile.tf .\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-base:24.04 -f dockerfile.merlin.ctr .\n",
" docker build -t nvcr.io/nvstaging/merlin/merlin-hugectr:24.04 -f dockerfile.ctr .\n",
" cd ../..\n",
" ````"
]
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"\n",
"Your filesystem or system environment might impose constraints. The following command just serves as an example. It assumes HugeCTR was downloaded from GitHub into the current working directory (`git clone https://github.com/NVIDIA-Merlin/HugeCTR.git`). To allow writing files, we first give root user (inside the docker image you are root) to access to the notebook folder (this folder), and then startup a suitable Jupyter server.\n",
"```shell\n",
"export HCTR_SRC=\"${PWD}/HugeCTR\" && chmod -R 777 \"${HCTR_SRC}/hps_trt/notebooks\" && docker run -it --rm --gpus all --network=host -v ${HCTR_SRC}:/hugectr nvcr.io/nvstaging/merlin/merlin-tensorflow:23.12 jupyter-lab --allow-root --ip 0.0.0.0 --port 8888 --no-browser --notebook-dir=/hugectr/hps_trt/notebooks\n",
"export HCTR_SRC=\"${PWD}/HugeCTR\" && chmod -R 777 \"${HCTR_SRC}/hps_trt/notebooks\" && docker run -it --rm --gpus all --network=host -v ${HCTR_SRC}:/hugectr nvcr.io/nvstaging/merlin/merlin-hugectr:24.04 jupyter-lab --allow-root --ip 0.0.0.0 --port 8888 --no-browser --notebook-dir=/hugectr/hps_trt/notebooks\n",
"``` "
]
},
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_trt/notebooks/demo_for_hugectr_trained_model.ipynb
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"\n",
"### Use NGC\n",
"\n",
"The HPS TensorRT plugin is preinstalled in the 23.12 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:23.12`.\n",
"The HPS TensorRT plugin is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container."
]
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_trt/notebooks/demo_for_pytorch_trained_model.ipynb
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"\n",
"### Use NGC\n",
"\n",
"The HPS TensorRT plugin is preinstalled in the 23.12 and later [Merlin PyTorch Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-pytorch): `nvcr.io/nvidia/merlin/merlin-pytorch:23.12`.\n",
"The HPS TensorRT plugin is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container."
]
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2 changes: 1 addition & 1 deletion jupyter_execute/hps_trt/notebooks/demo_for_tf_trained_model.ipynb
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"\n",
"### Use NGC\n",
"\n",
"The HPS TensorRT plugin is preinstalled in the 23.12 and later [Merlin TensorFlow Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow): `nvcr.io/nvidia/merlin/merlin-tensorflow:23.12`.\n",
"The HPS TensorRT plugin is preinstalled in the 24.04 and later [Merlin HugeCTR Container](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-hugectr): `nvcr.io/nvidia/merlin/merlin-hugectr:24.04`.\n",
"\n",
"You can check the existence of the required libraries by running the following Python code after launching this container."
]
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6 changes: 1 addition & 5 deletions v23.06.00/QAList.html
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Expand Up @@ -345,16 +345,12 @@ <h2>32. What does the log “memory pool is empty” imply for HugeCTR inference
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Expand Up @@ -241,16 +241,12 @@ <h1>Source code for hierarchical_parameter_server.core.lookup_layer</h1><div cla
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Expand Up @@ -126,16 +126,12 @@ <h1>All modules for which code is available</h1>
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Expand Up @@ -142,16 +142,12 @@ <h1>Additional Resources<a class="headerlink" href="#additional-resources" title
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Expand Up @@ -1404,16 +1404,12 @@ <h2>GroupDenseLayer<a class="headerlink" href="#groupdenselayer" title="Permalin
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Expand Up @@ -321,16 +321,12 @@ <h1>HugeCTR API Documentation<a class="headerlink" href="#hugectr-api-documentat
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6 changes: 1 addition & 5 deletions v23.06.00/api/python_interface.html
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Expand Up @@ -1447,16 +1447,12 @@ <h3>DataSourceParams class<a class="headerlink" href="#datasourceparams-class" t
<div class="rst-other-versions">
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<dt>Branches</dt>
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