API
Surrogatize.DigitalEcho
— TypeDigitalEcho
The DigitalEcho model that encompass the EmbeddingSystem
and the Decoder
API for deploying job on JuliaHub
JuliaSimSurrogates.@train
— Macro@train script
Macro for capturing the code which would be submitted for running a training job on JuliaHub For adding custom serialization, we need to set the JSS_SURROGATE_PATH
enviornment variable to the path of the serialized object.
Arguments
script
: Code block enclosed in a begin..end which would be cached and submitted for running a training job on JuliaHub
Example
@train begin
using Surrogatize
surrogate = nothing
end
@train begin
using Surrogatize, JLD2
surrogate = nothing
custom_path = "models/surrogate.jld2"
jldsave(custom_path, result = surrogate)
ENV["JSS_SURROGATE_PATH"] = custom_path
end
JuliaSimSurrogates.run_training
— Functionrun_training(
directory,
batch_image::JuliaHub.BatchImage,
dataset_name;
dataset_version,
surrogate_name,
auth,
specs,
kwargs...
)
Runs a training job on JuliaHub. This function should called after calling @training
to cache in the code which needs to be run on the job. It modifies the cached code such that the dataset_name
passed is downloaded and the path for it is stored in JSS_DATASET_PATH
and the result of the code block is serialised in JLSO format. The expectation is the script ends with the call to which trains a surrogate.
The function then orchestrates a batch job on JuliaHub with the given batch image which executes the code and stores the generated surrogate as a JuliaHub.Dataset
.
Arguments
directory
: Path to the directory that would be used to upload as an appbundle. Any additional required files like FMU should be inside this directory batch_image
: Job image to be used for the batch job. This is of type JuliaHub.BatchImage
dataset_name
: Name of the dataset which gets downloaded into the job which can be used for training dataset_version
: Version of dataset_name
. Defaults to the latest version surrogate_name
: Name of the dataset in which the result of the script, i.e., the trained surrogate is serialised and uploaded auth
: Authentication object of type JuliaHub.Authentication
for verification while performing various operations on Juliahub specs
: Named Tuple giving the specifications of compute for the batch job, i.e, ncpu
, ngpu
, memory
etc.
Returns
Named tuple of job object of type JuliaHub.Job
and result surrogate dataset object of type JuliaHub.Dataset