This is Nod's Tensorflow version of DLRM which is based on OpenRec DLRM model. We extract the Openrec DRML source code and fixed some bugs in their model definition to make it work with tensorflow-gpu==2.2 and python3.7
First, clone noddlrm using git:
git clone https://github.com/NodLabs/tensorflow-dlrmThen, cd to the tensorflow-dlrm folder and run the install command(if you want to install
noddlrm to your python lib):
cd tensorflow-dlrm
python setup.py installNow you have installed noddlrm to you system.
All datasets can be downloaded from Google drive here. In our example, we use the dataset criteo.
Edit the dlrm_criteo_gpu/tpu.py to use your dataset criteo path Then run the example script we have provided.
cd tensorflow-dlrm/
export PYTHONPATH="$PWD"
python3 dlrm_criteo_gpu.py
# python3 dlrm_criteo_tpu.pypython3 dlrm_criteo_gpu.py
2020-07-14 08:10:32.701182: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-07-14 08:10:32.729195: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-07-14 08:10:32.729514: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 computeCapability: 7.5
coreClock: 1.59GHz coreCount: 46 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.29GiB/s
2020-07-14 08:10:32.729734: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/chi/bin/vulkansdk/x86_64/lib::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2020-07-14 08:10:32.730158: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcublas.so.10'; dlerror: libcublas.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/chi/bin/vulkansdk/x86_64/lib::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2020-07-14 08:10:32.730298: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcufft.so.10'; dlerror: libcufft.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/chi/bin/vulkansdk/x86_64/lib::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2020-07-14 08:10:32.730501: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcurand.so.10'; dlerror: libcurand.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/chi/bin/vulkansdk/x86_64/lib::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2020-07-14 08:10:32.730632: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusolver.so.10'; dlerror: libcusolver.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/chi/bin/vulkansdk/x86_64/lib::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2020-07-14 08:10:32.730848: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusparse.so.10'; dlerror: libcusparse.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/chi/bin/vulkansdk/x86_64/lib::/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
2020-07-14 08:10:32.766959: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-07-14 08:10:32.766987: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1598] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2020-07-14 08:10:32.768812: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-07-14 08:10:32.799122: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 2899885000 Hz
2020-07-14 08:10:32.799874: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f2204000b20 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-07-14 08:10:32.799887: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-07-14 08:10:32.801441: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-07-14 08:10:32.801453: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]
WARNING:tensorflow:From /home/chi/nnc_env/lib/python3.7/site-packages/tensorflow/python/ops/linalg/linear_operator_lower_triangular.py:158: calling LinearOperator.__init__ (from tensorflow.python.ops.linalg.linear_operator) with graph_parents is deprecated and will be removed in a future version.
Instructions for updating:
Do not pass `graph_parents`. They will no longer be used.
Iter: 0, Loss: 0.24, AUC: 0.5614
Iter: 100, Loss: 0.19, AUC: 0.6755
Iter: 200, Loss: 0.17, AUC: 0.6976
Iter: 300, Loss: 0.17, AUC: 0.7037
Iter: 400, Loss: 0.17, AUC: 0.7062
Iter: 500, Loss: 0.17, AUC: 0.7079
Iter: 600, Loss: 0.17, AUC: 0.7080
Iter: 700, Loss: 0.17, AUC: 0.7095
Iter: 800, Loss: 0.17, AUC: 0.7099
Iter: 900, Loss: 0.17, AUC: 0.7103
2020-07-14 08:21:00.611816: W tensorflow/python/util/util.cc:329] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
WARNING:tensorflow:From /home/chi/nnc_env/lib/python3.7/site-packages/tensorflow/python/ops/resource_variable_ops.py:1817: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.
Instructions for updating:
If using Keras pass *_constraint arguments to layers.
python3 dlrm_criteo_tpu.py
2020-07-14 15:16:10.152558: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-07-14 15:16:10.179204: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 2300000000 Hz
2020-07-14 15:16:10.183868: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x38c1f20 initialized for platform Host (this does not guarantee that XLA will be used).
Devices:
2020-07-14 15:16:10.183924: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2020-07-14 15:16:10.232148: I tensorflow/core/distributed_runtime/rpc/grpc_channel.cc:301] Initialize GrpcChannelCache for job worker -> {0 -> 10.240.1.2:8470}
2020-07-14 15:16:10.232200: I tensorflow/core/distributed_runtime/rpc/grpc_channel.cc:301] Initialize GrpcChannelCache for job localhost -> {0 -> localhost:31017}
2020-07-14 15:16:10.255055: I tensorflow/core/distributed_runtime/rpc/grpc_channel.cc:301] Initialize GrpcChannelCache for job worker -> {0 -> 10.240.1.2:8470}
2020-07-14 15:16:10.255110: I tensorflow/core/distributed_runtime/rpc/grpc_channel.cc:301] Initialize GrpcChannelCache for job localhost -> {0 -> localhost:31017}
2020-07-14 15:16:10.259154: I tensorflow/core/distributed_runtime/rpc/grpc_server_lib.cc:390] Started server with target: grpc://localhost:31017
All devices: [LogicalDevice(name='/job:worker/replica:0/task:0/device:TPU:7', device_type='TPU'), LogicalDevice(name='/job:worker/replica:0/task:0/device:TPU:6', device_type='TP
U'), LogicalDevice(name='/job:worker/replica:0/task:0/device:TPU:5', device_type='TPU'), LogicalDevice(name='/job:worker/replica:0/task:0/device:TPU:4', device_type='TPU'), Logic
alDevice(name='/job:worker/replica:0/task:0/device:TPU:0', device_type='TPU'), LogicalDevice(name='/job:worker/replica:0/task:0/device:TPU:1', device_type='TPU'), LogicalDevice(n
ame='/job:worker/replica:0/task:0/device:TPU:2', device_type='TPU'), LogicalDevice(name='/job:worker/replica:0/task:0/device:TPU:3', device_type='TPU')]
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/linalg/linear_operator_lower_triangular.py:158: calling LinearOperator.__init__ (from tensorf
low.python.ops.linalg.linear_operator) with graph_parents is deprecated and will be removed in a future version.
Instructions for updating:
Do not pass `graph_parents`. They will no longer be used.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/linalg/linear_operator_lower_triangular.py:158: calling LinearOperator.__init__ (from tensorf
low.python.ops.linalg.linear_operator) with graph_parents is deprecated and will be removed in a future version.
Instructions for updating:
Do not pass `graph_parents`. They will no longer be used.
Iter: 0, Loss: 0.22, AUC: 0.4884
Iter: 100, Loss: 0.19, AUC: 0.6258
Iter: 200, Loss: 0.18, AUC: 0.6673
Iter: 300, Loss: 0.18, AUC: 0.6827
Iter: 400, Loss: 0.17, AUC: 0.6939
Iter: 500, Loss: 0.17, AUC: 0.7030
Iter: 600, Loss: 0.17, AUC: 0.7066
Iter: 700, Loss: 0.17, AUC: 0.7079
Iter: 800, Loss: 0.17, AUC: 0.7100
Iter: 900, Loss: 0.17, AUC: 0.7107
2020-07-14 15:22:10.259060: W tensorflow/python/util/util.cc:329] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/resource_variable_ops.py:1817: calling BaseResourceVariable.__init__ (from tensorflow.python.
ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.
Instructions for updating:
If using Keras pass *_constraint arguments to layers.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/ops/resource_variable_ops.py:1817: calling BaseResourceVariable.__init__ (from tensorflow.python.
ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.
Instructions for updating:
If using Keras pass *_constraint arguments to layers.