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[TASK] Fix dependencies for tensorflow/protobuf in gretel-synthetics
Co-authored-by: Gretel GitHub Bot <devops+github-bot@gretel.ai> GitOrigin-RevId: d774159dd71d219d7f7db5ab8da94c0d670b4457
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README.md

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- [Train your model](https://gretel-synthetics.readthedocs.io/en/stable/api/train.html)
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- [Generate synthetic records](https://gretel-synthetics.readthedocs.io/en/stable/api/generate.html)
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## Try it out now!
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## Try it out now
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If you want to quickly discover gretel-synthetics, simply click the button below and follow the tutorials!
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By default, we do not install certain core requirements, the following dependencies should be installed _external to the installation_
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of `gretel-synthetics`, depending on which model(s) you plan to use.
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- Tensorflow: Used by the LSTM model, we recommend version 2.11.x
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- Tensorflow: Used by the LSTM model, we recommend version 2.12.x
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- Torch: Used by Timeseries DGAN and ACTGAN (for ACTGAN, Torch is installed by SDV), we recommend version 2.0
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- SDV (Synthetic Data Vault): Used by ACTGAN, we recommend version 0.17.x
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These dependencies can be installed by doing the following:
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```
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pip install tensorflow==2.11 # for LSTM
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pip install tensorflow==2.12.1 # for LSTM
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pip install sdv<0.18 # for ACTGAN
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pip install torch==2.0 # for Timeseries DGAN
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```
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_then..._
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```
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$ pip install jupyter
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$ jupyter notebook
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pip install jupyter
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jupyter notebook
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```
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When the UI launches in your browser, navigate to `examples/synthetic_records.ipynb` and get generating!
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1. Create a virtual environment (e.g. using `conda`)
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```
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$ conda create --name tf python=3.9
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conda create --name tf python=3.9
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```
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2. Activate the virtual environment
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```
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$ conda activate tf
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conda activate tf
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```
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3. Run the setup script `./setup-utils/setup-gretel-synthetics-tensorflow24-with-gpu.sh`

requirements/base.txt

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category-encoders==2.2.2
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joblib==1.4.2
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numpy>=1.18.0,<1.24
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packaging==21.3
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packaging<22.0
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pandas>=1.1.0,<2
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rdt>=1.2,<1.3
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sdv>=0.17,<0.18

requirements/tensorflow.txt

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protobuf>=3.9.2,<3.20
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dash==2.18.1
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ipykernel==6.29.5
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protobuf>=4,<=4.24.0
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tensorflow==2.12.1
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tensorflow_estimator==2.12.0
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tensorflow_privacy==0.7.3

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