def __init__(self, output_folder, n_toy, n_input_mc, centre_of_mass, start_at=0, split=1): Job.__init__(self) self.output_folder = output_folder self.n_toy = n_toy self.centre_of_mass = centre_of_mass self.start_at = start_at self.n_input_mc = n_input_mc self.config = XSectionConfig(centre_of_mass) self.part_of_split = split
def __init__(self, input_file, output_folder, variable, n_toy, centre_of_mass, ttbar_xsection, met_type, start_at=1): Job.__init__(self) self.input_file = input_file self.output_folder = output_folder self.n_toy = n_toy self.variable = variable self.centre_of_mass = centre_of_mass self.ttbar_xsection = ttbar_xsection self.met_type = met_type self.start_at = start_at self.additional_input_files = [input_file]
def __init__(self, input_file_directory, method, channels, centre_of_mass, response, samples, variables, n_toy_data, output_folder, do_best_tau, tau_values): ''' Constructor ''' Job.__init__(self) self.input_file_directory = input_file_directory self.method = method self.centre_of_mass = centre_of_mass self.response = response self.all_samples = samples self.n_toy_data = n_toy_data self.output_folder = output_folder self.all_channels = channels self.all_variables = variables self.do_best_tau = do_best_tau self.all_tau_values = tau_values self.cross_section_config = XSectionConfig(self.centre_of_mass)
def __init__(self, input_file_name, method, channel, centre_of_mass, variable, n_toy_mc, n_toy_data, output_folder, offset_toy_mc, offset_toy_data, k_value, tau_value=-1, run_matrix=None): ''' Constructor ''' Job.__init__(self) self.input_file_name = input_file_name self.method = method self.channel = channel self.centre_of_mass = centre_of_mass self.variable = variable self.n_toy_mc = n_toy_mc self.n_toy_data = n_toy_data self.output_folder = output_folder self.offset_toy_mc = offset_toy_mc self.offset_toy_data = offset_toy_data self.k_value = k_value self.tau_value = tau_value self.run_matrix = run_matrix self.additional_input_files = [input_file_name]
def __init__(self, params): Job.__init__(self)
time_id = datetime.now().strftime("%b-%d_%H:%M:%S") base_folder = '_'.join([exp_name, time_id]) message = 'Executor: Aneeshan Sain\nDirectory: Stroke_correspondence/SBIR_QD \nDescription: Seeing basic Retrieval results for SBIR on QuickDraw-14 ' args = ['try2'] for i_exp, arg in enumerate(args): tag = '14_classes' save_dir = f'./condor_output/{base_folder}' j = Job( python_compiler, run_file, stream_output=True, can_checkpoint=True, approx_runtime=8, # in hours artifact_dir=save_dir, arguments=dict(base_dir=os.getcwd(), saved_models=os.path.join(os.getcwd(), save_dir), disable_tqdm='', batchsize=16, max_epoch=100, learning_rate=0.0001), tag='_'.join([exp_name, tag]) + '_') sess.submit(j, conf) print(f'Job {i_exp + 1} {exp_name} {tag} submitted at {str(time_id)}.') # Report the job submission # message += f'\n\nExperiment {i_exp + 1} :\n' + '\n'.join([f'{item[0]} -- {item[1]}' for item in arg.items()]) print(message) # send_email('*****@*****.**', message)