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'