def launch_hyperparameter_scan(hyperparameter_input_csv, hyperparameter_output_log, generate_input, job_chunk_size, interest_cols, categorical, reset_all, torque, gpu, gpu_node, nohup, n_jobs_relaunch, crossover_p, model_complexity_factor,n_jobs, val_loss_column, add_softmax, additional_command, cuda, hyperparameter_yaml, randomseed, additional_opts, max_epochs):
"""Run randomized hyperparameter scan of neural network hyperparameters."""
from methylnet.hyperparameter_scans import coarse_scan, find_top_jobs
custom_jobs=[]
if n_jobs_relaunch:
custom_jobs=find_top_jobs(hyperparameter_input_csv, hyperparameter_output_log,n_jobs_relaunch, crossover_p, val_loss_column)
if os.path.exists(hyperparameter_yaml):
from ruamel.yaml import safe_load as load
with open(hyperparameter_yaml) as f:
new_grid = load(f.read())
else:
new_grid = {}
coarse_scan(hyperparameter_input_csv, hyperparameter_output_log, generate_input, job_chunk_size, interest_cols, reset_all, torque, gpu, gpu_node, nohup, mlp=True, custom_jobs=custom_jobs, model_complexity_factor=model_complexity_factor,n_jobs=n_jobs, categorical=categorical,add_softmax=add_softmax, additional_command=additional_command, cuda=cuda, new_grid=new_grid, randomseed=randomseed, additional_opts=additional_opts, max_epochs=max_epochs)
def launch_hyperparameter_scan(
hyperparameter_input_csv, hyperparameter_output_log, generate_input,
job_chunk_size, stratify_column, reset_all, torque, gpu, gpu_node,
nohup, model_complexity_factor, set_beta, n_jobs, n_jobs_relaunch,
crossover_p, val_loss_column, additional_command, cuda,
hyperparameter_yaml, randomseed, additional_opts, max_epochs):
"""Launch randomized grid search of neural network hyperparameters."""
from methylnet.hyperparameter_scans import coarse_scan, find_top_jobs
custom_jobs = []
if n_jobs_relaunch:
custom_jobs = find_top_jobs(hyperparameter_input_csv,
hyperparameter_output_log, n_jobs_relaunch,
crossover_p, val_loss_column)
if os.path.exists(hyperparameter_yaml):
from ruamel.yaml import safe_load as load
with open(hyperparameter_yaml) as f:
new_grid = load(f)
#print(new_grid)
else:
new_grid = {}
coarse_scan(hyperparameter_input_csv,
hyperparameter_output_log,
generate_input,
job_chunk_size,
stratify_column,
reset_all,
torque,
gpu,
gpu_node,
nohup,
mlp=False,
model_complexity_factor=model_complexity_factor,
set_beta=set_beta,
n_jobs=n_jobs,
custom_jobs=custom_jobs,
additional_command=additional_command,
cuda=cuda,
new_grid=new_grid,
randomseed=randomseed,
additional_opts=additional_opts,
max_epochs=max_epochs)