def test_trained_model_premade_pyspec(tmp_path, data_dir, config_gin,
dataspec_bias):
K.clear_session()
gin.clear_config()
bpnet_train(dataspec=str(dataspec_bias),
output_dir=str(tmp_path),
premade='bpnet9-pyspec',
config=str(config_gin),
num_workers=2)
def test_train_regions(tmp_path, data_dir, config_gin, dataspec_bias, regions):
K.clear_session()
gin.clear_config()
bpnet_train(dataspec=str(dataspec_bias),
output_dir=str(tmp_path),
premade='bpnet9',
config=str(config_gin),
override=f'bpnet_data.intervals_file="{regions}"',
num_workers=2)
def test_trained_model_bed6(tmp_path, data_dir, config_gin, dataspec_bed6):
K.clear_session()
gin.clear_config()
bpnet_train(dataspec=str(dataspec_bed6),
output_dir=str(tmp_path),
premade='bpnet9',
config=str(config_gin),
override='seq_width=100;train.batch_size=8',
num_workers=2)
def test_trained_model_vmtouch(tmp_path, data_dir, config_gin, dataspec_bias):
K.clear_session()
gin.clear_config()
bpnet_train(dataspec=str(dataspec_bias),
output_dir=str(tmp_path),
premade='bpnet9',
config=str(config_gin),
vmtouch=True,
num_workers=1)
def trained_model_w_bias(config_gin, data_dir, dataspec_bias):
K.clear_session()
gin.clear_config()
bpnet_train(dataspec=str(dataspec_bias),
output_dir=str(data_dir),
run_id='trained_model_w_bias',
premade='bpnet9',
config=str(config_gin),
num_workers=1,
overwrite=True,
)
return data_dir / 'trained_model_w_bias'
def trained_model(data_dir, dataspec_task1, config_gin):
K.clear_session()
gin.clear_config()
bpnet_train(dataspec=dataspec_task1,
output_dir=data_dir,
run_id='trained_model',
premade='bpnet9',
config=str(config_gin),
num_workers=1,
overwrite=True
)
return data_dir / 'trained_model'