#This file is part of the PyPhase software.
#
#Copyright (c) Max Langer (2019)
#
#max.langer@creatis.insa-lyon.fr
#
#This software is a computer program whose purpose is to allow development,
#implementation, and deployment of phase retrieval algorihtms.
#
#This software is governed by the CeCILL license under French law and
#abiding by the rules of distribution of free software. You can use,
#modify and/ or redistribute the software under the terms of the CeCILL
#license as circulated by CEA, CNRS and INRIA at the following URL
#"http://www.cecill.info".
#
#As a counterpart to the access to the source code and rights to copy,
#modify and redistribute granted by the license, users are provided only
#with a limited warranty and the software's author, the holder of the
#economic rights, and the successive licensors have only limited
#liability.
#
#In this respect, the user's attention is drawn to the risks associated
#with loading, using, modifying and/or developing or reproducing the
#software by the user in light of its specific status of free software,
#that may mean that it is complicated to manipulate, and that also
#therefore means that it is reserved for developers and experienced
#professionals having in-depth computer knowledge. Users are therefore
#encouraged to load and test the software's suitability as regards their
#requirements in conditions enabling the security of their systems and/or
#data to be ensured and, more generally, to use and operate it in the
#same conditions as regards security.
#
#The fact that you are presently reading this means that you have had
#knowledge of the CeCILL license and that you accept its terms.
import os
import math
import glob
import time
import pyphase.config as config
from functools import wraps
import pathlib
import pickle
import numpy as np
[docs]
def Serial(func):
"""Decorator for serial processing. Parallelisation decorators work on
functions with signature (self, *, dataset, projections)"""
@wraps(func)
def wrapper(*argv, **kwargs):
func(*argv, **kwargs)
return wrapper
[docs]
def SLURM(func):
"""Decorator for parallellisation on SLURM"""
@wraps(func)
def wrapper(*argv, **kwargs):
# Create a "worker" script that just calls align_projections
print('SLURM')
job_number = str(np.random.randint(0, 1e9))
projections = kwargs.pop('projections') #Necessary argument
parent_object = argv[0]
current_dir = os.getcwd()
tmpdir = '/.pyphase/SLURM/'
serialisation_filename = 'pyphase_'+ job_number+'.pickle'
pathlib.Path(current_dir+tmpdir).mkdir(parents=True, exist_ok=True)
with open(current_dir+tmpdir+serialisation_filename, 'wb') as f:
pickle.dump([parent_object, kwargs], f, protocol=pickle.HIGHEST_PROTOCOL)
pathlib.Path(current_dir+tmpdir).mkdir(parents=True, exist_ok=True)
worker_file_name = current_dir + tmpdir + 'pyphase_worker_'+job_number+'.py'
with open(worker_file_name, 'w') as worker_file:
print("import sys", file=worker_file)
print("import dataset", file=worker_file)
print("import phaseretrieval", file=worker_file)
print("import pickle", file=worker_file)
print("with open('{}', 'rb') as f:".format(current_dir+tmpdir+serialisation_filename), file=worker_file)
print(" stream = pickle.load(f)", file=worker_file)
print("projections = [int(sys.argv[1]), int(sys.argv[2])]", file=worker_file)
print("print(str(sys.argv))", file=worker_file)
print("stream[0].{}.__wrapped__(stream[0], projections=projections, **stream[1])".format(func.__name__), file=worker_file)
# Create a SLURM batch file
number_of_CPU_per_node = min(config.number_of_nodes*config.number_of_cores, int(math.floor(config.memory_per_node/config.min_memory_per_core))) # Use the number of CPU corresponding to memory needs
slurm_batch_file_name = current_dir + tmpdir + 'pyphase_slurm_'+job_number+'.sh'
tasks = int(projections[1]) - int(projections[0]) + 1
number_of_CPU = min(number_of_CPU_per_node * config.number_of_nodes, tasks)
step = tasks // number_of_CPU - 1
remainder = tasks % (number_of_CPU)
with open(slurm_batch_file_name, 'w') as slurm_batch_file:
print("#!/bin/sh", file=slurm_batch_file)
print("#SBATCH -N {}".format(config.number_of_nodes), file=slurm_batch_file)
#print("#SBATCH --exclusive", file=slurm_batch_file)
print("#SBATCH --mem-per-cpu {}".format(config.min_memory_per_core), file=slurm_batch_file)
print("#SBATCH --tasks-per-node {}".format(number_of_CPU_per_node), file=slurm_batch_file)
print("#SBATCH -t 20:00:00", file=slurm_batch_file)
print("#SBATCH -J pyphase", file=slurm_batch_file)
print("#SBATCH -o {}pyphase_%j.out".format(current_dir+tmpdir), file=slurm_batch_file)
print("#SBATCH -e {}pyphase_%j.out".format(current_dir+tmpdir), file=slurm_batch_file)
print("cat $0", file=slurm_batch_file)
print("export tasks={}".format(tasks), file=slurm_batch_file)
print("export start={}".format(projections[0]), file=slurm_batch_file)
print("export step={}".format(step), file=slurm_batch_file)
print("export remainder={}".format(remainder), file=slurm_batch_file)
print("for (( i=0; i<{}; i++ ))".format(number_of_CPU), file=slurm_batch_file)
print("do", file=slurm_batch_file)
print("export end=$(( start+step+(i<remainder) ))", file=slurm_batch_file)
print("srun -Q --exclusive -n 1 -N 1 python {} $start $end &> {}pyphase_worker_${{SLURM_JOB_ID}}_${{i}} &".format(worker_file_name, current_dir+tmpdir), file=slurm_batch_file)
print("echo \"python {} $start $end\"".format(worker_file_name), file=slurm_batch_file)
print("export start=$(( end+1 ))", file=slurm_batch_file)
print("sleep 1", file=slurm_batch_file)
print("done", file=slurm_batch_file)
print("wait", file=slurm_batch_file)
print("touch {}pyphase_{}.sig".format(current_dir+tmpdir, job_number), file= slurm_batch_file)
# Submit
cmd="sbatch ."+tmpdir+"pyphase_slurm_"+job_number+".sh"
print("Executing: " + cmd)
os.system(cmd)
timer=0
sigfile = 'pyphase_'+job_number+'.sig'
while not os.path.exists(current_dir+tmpdir+sigfile):
#if not(timer%30):
# print("Executing: " + func.__name__ + ", {} s".format(timer), end='\r')
time.sleep(1)
timer += 1
os.remove(current_dir+tmpdir+sigfile)
os.remove(current_dir+tmpdir+serialisation_filename)
return wrapper
# pass
[docs]
class OAR:
"""Legacy class for parallellisation on OAR. Will be reimplemented as
decorator"""
def __init__(self):
self.cores = 100
self.executable_name = 'pyphase'
self.path = os.path.split(os.path.realpath(__file__))[0]
self.executable = os.path.join(self.path, self.executable_name)
pass
[docs]
def WriteOarFiles(self, DS):
pass
#TODO: Don likne this implementation at all. Should probably be a decorator?
[docs]
def Launch(self, dataset, operator, **kwargs):
# algorithm='', parameter='', distance=''
#TODO: Don't like this solution at all, needs reimplementation... this is not elegant
#TODO: standardised file names...oars
#fname = dataset.path+'/'+dataset.name+'_/'+dataset.name+'_'+dataset.version+'_'+operator
if operator=='retrieve':
command_prefix = '{} {}'.format(operator, dataset.name)
command_postfix = ''
fname = dataset.phase_prefix
if 'algorithm' in kwargs:
command_postfix+=' --algorithm {}'.format(kwargs.get('algorithm'))
elif operator=='retrieve_difference':
fname = dataset.update_prefix
if 'algorithm' in kwargs:
command+=' --algorithm {}'.format(kwargs.get('algorithm'))
elif operator=='propagate':
fname = dataset.propagated_prefix # TODO:surely needs distance somehow?
if 'algorithm' in kwargs:
command+=' --algorithm {}'.format(kwargs.get('algorithm'))
elif operator=='difference':
fname = dataset.difference_prefix
if 'distance' in kwargs:
command+=' --distance {}'.format(kwargs.get('distance'))
#TODO: remove edf files (?)
if os.path.exists(fname+"_.oar"):
os.remove(fname+"_.oar")
with open(fname+'_.oar', 'w') as oar_file:
print("#!/bin/bash", file=oar_file)
print("#OAR -l {mem_core_mb>=8000}/core=1,walltime=24", file=oar_file)
print("#OAR -l {mem_core_mb>=4000 and mem_core_mb <8000}/nodes=1/core=2,walltime=48", file=oar_file)
print("#OAR --array-param-file {}".format(fname+'_.params'), file=oar_file)
print("#OAR --name {}".format(dataset.name), file=oar_file)
print("#OAR --type besteffort", file=oar_file)
print("#OAR --type idempotent", file=oar_file)
print("{} $@".format(self.executable), file=oar_file)
if os.path.exists(fname+"_.params"):
os.remove(fname+"_.params")
with open(fname+'_.params', 'w') as oar_file:
interval = math.ceil(dataset.nbprojections/self.cores)
for x in range(self.cores):
print(command_prefix+' -p {} {} '.format(x*interval, (x+1)*interval)+command_postfix, file=oar_file)
#with open(fname+'.params', 'w') as oar_file:
# print("/mntdirect/_users/mlanger/Python/pyPhase/main.py 0 1", file=oar_file)
# remove edf files before launching
if operator in ('difference', 'propagate'):
for file in glob.glob(fname+'_'+str(kwargs.get('distance'))+"_????.edf"):
os.remove(file)
else:
for file in glob.glob(fname+"_????.edf"):
os.remove(file)
os.chmod(fname+'_.oar', 511)
os.chmod(fname+'_.params', 511)
# submit oar job that runs a script to signal end of job somehow
#program_path=os.path.dirname(__file__)
cmd="oarsub -S "+fname+"_.oar > /dev/null"
print("Executing: " + cmd)
os.system(cmd)
# wait for job to finish (track number of edf's finally, I guess)
# progress bar for niceness
#TODO: this won't work now. Needs proper file name handling
edfCounter = 0
if operator in ('difference', 'propagate'):
nbprojections=dataset.nbprojections
while edfCounter < nbprojections:
config.utilities.update(operator.capitalize() + ' Distance ' + str(kwargs.get('distance')), edfCounter, nbprojections)
edfCounter = len(glob.glob(fname+'_'+str(kwargs.get('distance'))+"_????.edf"))
time.sleep(1)
config.utilities.update(operator.capitalize() + ' Distance ' + str(kwargs.get('distance')), edfCounter, nbprojections)
else:
while edfCounter < dataset.nbprojections:
config.utilities.update(operator.capitalize(), edfCounter, dataset.nbprojections)
edfCounter = len(glob.glob(fname+"_????.edf"))
time.sleep(1)
config.utilities.update(operator.capitalize(), edfCounter, dataset.nbprojections)