def main():
parser = argparse.ArgumentParser()
parser.add_argument('outdir')
parser.add_argument('--datafile', default='')
args = parser.parse_args()
config = get_config(args.outdir)
task = config['tasks']
if isinstance(task, (tuple, list)):
task = task[0]
config_updates = {
'tasks': task,
'load_task_from': os.path.join(args.outdir, 'task_weights.h5'),
'save_outputs': True,
'datafile': args.datafile}
proteins.run(
'eval',
named_configs=[os.path.join(args.outdir, '1', 'config.json')],
config_updates=config_updates,
)
print(config)
if config['tasks'] == 'stability':
with open(os.path.join(args.outdir, 'outputs.pkl'), 'rb') as f:
results = pkl.load(f)
predictions = np.array(results['prediction'])
true_values = np.array(results['stability_score'])
score, _ = spearmanr(true_values, predictions)
print('stability score:', score)
if config_updates['tasks'] == 'fluorescence':
def postprocess(data):
""" Converts list of numpy arrays to flat numpy array. """
_clean = [float(i) for i in data]
clean = np.array(_clean)
return clean
with open(os.path.join(args.outdir, 'outputs.pkl'), 'rb') as f:
results = pkl.load(f)
predictions = postprocess(results['prediction'])
true_values = postprocess(results['log_fluorescence'])
score, _ = spearmanr(true_values, predictions)
print('fluorescence score:', score)
def run_single_experiment(dataset: str,
savedir: str,
named_configs: List,
config_updates: Dict[str, Any]):
from tape.__main__ import proteins
config_updates.update({
'training': {'learning_rate': 1e-4, 'use_memory_saving_gradients': True},
'num_epochs': 1000,
'steps_per_epoch': 200,
'tasks': dataset})
if not os.path.exists(savedir):
os.mkdir(savedir)
shutil.rmtree(proteins.observers[0].basedir)
proteins.observers[0] = FileStorageObserver.create(
os.path.join(savedir, dataset))
proteins.run(
named_configs=named_configs,
config_updates=config_updates)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('outdir')
parser.add_argument('--datafile', default='')
args = parser.parse_args()
config = get_config(args.outdir)
task = config['tasks']
if isinstance(task, (tuple, list)):
task = task[0]
config_updates = {
'tasks': task,
'load_task_from': os.path.join(args.outdir, 'task_weights.h5'),
'save_outputs': True,
'datafile': args.datafile
}
proteins.run(
'eval',
named_configs=[os.path.join(args.outdir, '1', 'config.json')],
config_updates=config_updates,
)
from tape.analysis import get_config
import os
from tape.__main__ import proteins
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('outdir')
parser.add_argument('--datafile', default='')
args = parser.parse_args()
config = get_config(args.outdir)
task = config['tasks']
if isinstance(task, (tuple, list)):
task = task[0]
config_updates = {
'tasks': task,
'load_task_from': os.path.join(args.outdir, 'task_weights.h5'),
'save_outputs': True,
'datafile': args.datafile
}
proteins.run('eval',
named_configs=[os.path.join(args.outdir, '1', 'config.json')],
config_updates=config_updates)