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* script executor improvements
* move ScriptExecutor to job_config
* rename ScriptExecutor to ScriptRunner, add TF versions of in process and ex process executors
* fix dead links
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Co-authored-by: Chester Chen <[email protected]>
### 1. [Federated averaging using the script executor](./fedavg_script_executor_cifar10.py)
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### 1. [Federated averaging using the script executor](./fedavg_script_runner_cifar10.py)
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html).
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### 2. [Federated averaging using script executor and differential privacy filter](./fedavg_script_executor_dp_filter_cifar10.py)
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### 2. [Federated averaging using script executor and differential privacy filter](./fedavg_script_runner_dp_filter_cifar10.py)
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html)
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with additional [differential privacy filters](https://arxiv.org/abs/1910.00962) on the client side.
### 3. [Swarm learning using script executor](./swarm_script_executor_cifar10.py)
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### 3. [Swarm learning using script executor](./swarm_script_runner_cifar10.py)
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Implementation of [swarm learning](https://www.nature.com/articles/s41586-021-03583-3) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html)
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```commandline
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python swarm_script_executor_cifar10.py
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python swarm_script_runner_cifar10.py
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```
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### 4. [Cyclic weight transfer using script executor](./cyclic_cc_script_executor_cifar10.py)
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### 4. [Cyclic weight transfer using script executor](./cyclic_cc_script_runner_cifar10.py)
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Implementation of [cyclic weight transfer](https://arxiv.org/abs/1709.05929) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html)
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```commandline
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python cyclic_cc_script_executor_cifar10.py
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python cyclic_cc_script_runner_cifar10.py
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```
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### 5. [Federated averaging using model learning](./fedavg_model_learner_xsite_val_cifar10.py))
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [model learner class](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/model_learner.html),
Copy file name to clipboardexpand all lines: examples/getting_started/pt/README.md
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We provide several examples to quickly get you started using NVFlare's Job API.
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All examples in this folder are based on using [PyTorch](https://pytorch.org/) as the model training framework.
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Furthermore, we support [PyTorch Lightning](https://lightning.ai).
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## Setup environment
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First, install nvflare and dependencies:
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```commandline
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pip install -r requirements.txt
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```
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## Tutorials
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A good starting point for understanding the Job API scripts and NVFlare components are the following tutorials.
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### 1. [Federated averaging using script executor](./nvflare_pt_getting_started.ipynb)
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Tutorial on [FedAvg](https://arxiv.org/abs/1602.05629) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html).
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### 2. [Federated averaging using script executor with Lightning API](./nvflare_lightning_getting_started.ipynb)
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Tutorial on [FedAvg](https://arxiv.org/abs/1602.05629) using the [Lightning Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html#id4)
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## Examples
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You can also run any of the below scripts directly using
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```commandline
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python "script_name.py"
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```
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### 1. [Federated averaging using script executor](./fedavg_script_executor_cifar10.py)
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html).
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```commandline
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python fedavg_script_executor_cifar10.py
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```
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### 2. [Federated averaging using script executor with Lightning API](./fedavg_script_executor_lightning_cifar10.py)
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [Lightning Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html#id4)
### 3. [Federated averaging using the script executor for all clients](./fedavg_script_executor_cifar10_all.py)
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html).
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Here, we deploy the same configuration to all clients.
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```commandline
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python fedavg_script_executor_cifar10_all.py
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```
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### 4. [Federated averaging using script executor and differential privacy filter](./fedavg_script_executor_dp_filter_cifar10.py)
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html)
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with additional [differential privacy filters](https://arxiv.org/abs/1910.00962) on the client side.
### 5. [Swarm learning using script executor](./swarm_script_executor_cifar10.py)
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Implementation of [swarm learning](https://www.nature.com/articles/s41586-021-03583-3) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html)
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```commandline
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python swarm_script_executor_cifar10.py
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```
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### 6. [Cyclic weight transfer using script executor](./cyclic_cc_script_executor_cifar10.py)
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Implementation of [cyclic weight transfer](https://arxiv.org/abs/1709.05929) using the [Client API](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/client_api.html)
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```commandline
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python cyclic_cc_script_executor_cifar10.py
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```
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### 7. [Federated averaging using model learning](./fedavg_model_learner_xsite_val_cifar10.py))
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Implementation of [FedAvg](https://arxiv.org/abs/1602.05629) using the [model learner class](https://nvflare.readthedocs.io/en/main/programming_guide/execution_api_type/model_learner.html),
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followed by [cross site validation](https://nvflare.readthedocs.io/en/main/programming_guide/controllers/cross_site_model_evaluation.html)
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for federated model evaluation.
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```commandline
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python fedavg_model_learner_xsite_val_cifar10.py
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```
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> [!NOTE]
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> More examples can be found at https://nvidia.github.io/NVFlare.
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