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Mercury leader, worker and watcher

Project description

mcy-dist-ai

This is a package used in Mercury Protocol's vulkan repository for training AI models distributed.

Usage:

Each instance has a role: WATCHER or LEADER. Watchers do the batch training and the leader does the gradient aggregation.

The user who wants to train an AI model has to write the script in a file called user_script.py and also a user_requirements.txt where the dependencies of the user_script.py are specified. This file is used by this component to perform the training. To see how it should be written check docs/user_script_requirements.md and docs/user_script_template.py.

mcy-split-data:

mcy-split-data is command which can be used by the user to split the data into a specified number of partitions and save them as tensors.

args:
split_into: the data will be split into this many partitions
data_path: the path of the directory which contains the data
output_dir_path: the path of the directory where the split tensors will be saved
user_script_path: the path of the user_script.py file where the create_data_loader function is specified by the user

example usage:

mcy-split-data 2 path/to/data/dir path/to/output/data/dir path/to/user_script.py

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