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.gitignore
View file @ d140bf44
......@@ -7,3 +7,7 @@
**/.vscode
**/leaf/
**.egg-info
2021**
2022**
**/massif.out*
*swp
README.rst
View file @ d140bf44
==============
decentralizepy
==============
decentralizepy is a framework for running distributed applications (particularly ML) on top of arbitrary topologies (decentralized, federated, parameter server).
It was primarily conceived for assessing scientific ideas on several aspects of distributed learning (communication efficiency, privacy, data heterogeneity etc.).
-------------------------
Setting up decentralizepy
-------------------------
* Fork the repository.
* Clone and enter your local repository.
* Check if you have ``python>=3.8``. ::
python --version
* (Optional) Create and activate a virtual environment. ::
python3 -m venv [venv-name]
source [venv-name]/bin/activate
* Update pip. ::
pip3 install --upgrade pip
pip install --upgrade pip
* On Mac M1, installing ``pyzmq`` fails with `pip`. Use `conda <https://conda.io>`_.
* Install decentralizepy for development. (zsh) ::
pip3 install --editable .\[dev\]
* Install decentralizepy for development. (bash) ::
pip3 install --editable .[dev]
----------------
Running the code
----------------
* Choose and modify one of the config files in ``eval/{step,epoch}_configs``.
* Modify the dataset paths and ``addresses_filepath`` in the config file.
* In eval/run.sh, modify arguments as required.
* Execute eval/run.sh on all the machines simultaneously. There is a synchronization barrier mechanism at the start so that all processes start training together.
------------
Contributing
------------
* ``isort`` and ``black`` are installed along with the package for code linting.
* While in the root directory of the repository, before committing the changes, please run ::
black .
isort .
Node
----
* The Manager. Optimizations at process level.
......@@ -19,7 +71,7 @@ Graph
Mapping
-------
* Naming. The globally unique ids of the processes <-> machine_id, local_rank
* Naming. The globally unique ids of the ``processes <-> machine_id, local_rank``
Sharing
-------
......@@ -28,3 +80,7 @@ Sharing
Communication
-------------
* IPC/Network level. Compression. Privacy. Reliability
Model
-----
* Learning Model
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eval/96_regular.edges 0 → 100644
View file @ d140bf44
96
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eval/epoch_configs/config_celeba.ini 0 → 100644
View file @ d140bf44
[DATASET]
dataset_package = decentralizepy.datasets.Celeba
dataset_class = Celeba
model_class = CNN
images_dir = /home/risharma/leaf/data/celeba/data/raw/img_align_celeba
train_dir = /home/risharma/leaf/data/celeba/per_user_data/train
test_dir = /home/risharma/leaf/data/celeba/data/test
; python list of fractions below
sizes =
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = Adam
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.GradientAccumulator
training_class = GradientAccumulator
rounds = 1
full_epochs = True
batch_size = 64
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss
[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr_6Machines.json
[SHARING]
sharing_package = decentralizepy.sharing.PartialModel
sharing_class = PartialModel
eval/epoch_configs/config_celeba_100.ini 0 → 100644
View file @ d140bf44
[DATASET]
dataset_package = decentralizepy.datasets.Celeba
dataset_class = Celeba
model_class = CNN
images_dir = /home/risharma/leaf/data/celeba/data/raw/img_align_celeba
train_dir = /home/risharma/leaf/data/celeba/per_user_data/train
test_dir = /home/risharma/leaf/data/celeba/data/test
; python list of fractions below
sizes =
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = Adam
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.Training
training_class = Training
rounds = 1
full_epochs = True
batch_size = 64
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss
[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr_6Machines.json
[SHARING]
sharing_package = decentralizepy.sharing.Sharing
sharing_class = Sharing
eval/epoch_configs/config_celeba_grow.ini 0 → 100644
View file @ d140bf44
[DATASET]
dataset_package = decentralizepy.datasets.Celeba
dataset_class = Celeba
model_class = CNN
images_dir = /home/risharma/leaf/data/celeba/data/raw/img_align_celeba
train_dir = /home/risharma/leaf/data/celeba/per_user_data/train
test_dir = /home/risharma/leaf/data/celeba/data/test
; python list of fractions below
sizes =
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = Adam
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.GradientAccumulator
training_class = GradientAccumulator
rounds = 1
full_epochs = True
batch_size = 64
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss
[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr_6Machines.json
[SHARING]
sharing_package = decentralizepy.sharing.GrowingAlpha
sharing_class = GrowingAlpha
init_alpha=0.10
max_alpha=0.75
k=6
metadata_cap=0.65
eval/epoch_configs/config_femnist.ini 0 → 100644
View file @ d140bf44
[DATASET]
dataset_package = decentralizepy.datasets.Femnist
dataset_class = Femnist
model_class = CNN
train_dir = /home/risharma/leaf/data/femnist/per_user_data/train
test_dir = /home/risharma/leaf/data/femnist/data/test
; python list of fractions below
sizes =
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = Adam
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.GradientAccumulator
training_class = GradientAccumulator
rounds = 1
full_epochs = True
batch_size = 128
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss
[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr_6Machines.json
[SHARING]
sharing_package = decentralizepy.sharing.PartialModel
sharing_class = PartialModel
config.ini → eval/epoch_configs/config_femnist_100.ini
View file @ d140bf44
......@@ -2,22 +2,22 @@
dataset_package = decentralizepy.datasets.Femnist
dataset_class = Femnist
model_class = CNN
n_procs = 12
train_dir = leaf/data/femnist/per_user_data/train
test_dir = leaf/data/femnist/data/test
train_dir = /home/risharma/leaf/data/femnist/per_user_data/train
test_dir = /home/risharma/leaf/data/femnist/data/test
; python list of fractions below
sizes =
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = Adam
lr = 0.01
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.Training
training_class = Training
epochs_per_round = 4
batch_size = 1024
rounds = 1
full_epochs = True
batch_size = 128
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss
......@@ -25,8 +25,8 @@ loss_class = CrossEntropyLoss
[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr.json
addresses_filepath = ip_addr_6Machines.json
[SHARING]
sharing_package = decentralizepy.sharing.Sharing
sharing_class = Sharing
\ No newline at end of file
sharing_class = Sharing
eval/epoch_configs/config_femnist_grow.ini 0 → 100644
View file @ d140bf44
[DATASET]
dataset_package = decentralizepy.datasets.Femnist
dataset_class = Femnist
model_class = CNN
train_dir = /home/risharma/leaf/data/femnist/per_user_data/train
test_dir = /home/risharma/leaf/data/femnist/data/test
; python list of fractions below
sizes =
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = Adam
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.GradientAccumulator
training_class = GradientAccumulator
rounds = 1
full_epochs = True
batch_size = 128
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss
[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr_6Machines.json
[SHARING]
sharing_package = decentralizepy.sharing.GrowingAlpha
sharing_class = GrowingAlpha
init_alpha=0.10
max_alpha=0.75
k=8
metadata_cap=0.65
\ No newline at end of file
graph.adj → eval/graph.adj
View file @ d140bf44
File moved
ip_addr.json → eval/ip_addr_3Machines.json
View file @ d140bf44
File moved