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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