def generate_pipeline():
# Create a Pipeline object
p = Pipeline()
# Create a Stage object
s1 = Stage()
# Create a Task object which creates a file named 'output.txt' of size 1 MB
t1 = Task()
t1.executable = ['mv']
t1.arguments = ['temp','/tmp/']
t1.upload_input_data = ['%s/temp'%cur_dir]
# Add the Task to the Stage
s1.add_tasks(t1)
# Add Stage to the Pipeline
p.add_stages(s1)
return p
def generate_pipeline():
# Create a Pipeline object
p = Pipeline()
# Create a Stage object
s1 = Stage()
# Create a Task object which creates a file named 'output.txt' of size 1 MB
t1 = Task()
t1.executable = 'mv'
t1.arguments = ['temp','/tmp/']
t1.upload_input_data = ['%s/temp' % cur_dir]
# Add the Task to the Stage
s1.add_tasks(t1)
# Add Stage to the Pipeline
p.add_stages(s1)
return p
def setup_replicas(replicas, min_temp, max_temp, timesteps, basename):
writeInputs.writeInputs(max_temp=max_temp, min_temp=min_temp, replicas=replicas, timesteps=timesteps, basename=basename)
tar = tarfile.open("input_files.tar", "w")
for name in [basename + ".prmtop", basename + ".inpcrd", basename + ".mdin"]:
tar.add(name)
for r in range(replicas):
tar.add('mdin-{replica}-{cycle}'.format(replica=r, cycle=0))
tar.close()
for r in range(replicas):
os.remove('mdin-{replica}-{cycle}'.format(replica=r, cycle=0))
setup_p = Pipeline()
setup_p.name = 'untarPipe'
repo = git.Repo('.', search_parent_directories=True)
aux_function_path = repo.working_tree_dir
untar_stg = Stage()
untar_stg.name = 'untarStg'
#Untar Task
untar_tsk = Task()
untar_tsk.name = 'untarTsk'
untar_tsk.executable = ['python']
untar_tsk.upload_input_data = ['untar_input_files.py', 'input_files.tar']
untar_tsk.arguments = ['untar_input_files.py', 'input_files.tar']
untar_tsk.cpu_reqs = 1
untar_tsk.post_exec = []
untar_stg.add_tasks(untar_tsk)
setup_p.add_stages(untar_stg)
global replica_sandbox
replica_sandbox='$Pipeline_%s_Stage_%s_Task_%s'%(setup_p.name, untar_stg.name, untar_tsk.name)
print replica_sandbox
return setup_p
def test_assignment_exceptions():
t = Task()
data_type = [1, 'a', True, list()]
for data in data_type:
if not isinstance(data, str):
with pytest.raises(TypeError):
t.name = data
if not isinstance(data, list):
with pytest.raises(TypeError):
t.pre_exec = data
with pytest.raises(TypeError):
t.executable = data
with pytest.raises(TypeError):
t.arguments = data
with pytest.raises(TypeError):
t.post_exec = data
with pytest.raises(TypeError):
t.upload_input_data = data
with pytest.raises(TypeError):
t.copy_input_data = data
with pytest.raises(TypeError):
t.link_input_data = data
with pytest.raises(TypeError):
t.copy_output_data = data
with pytest.raises(TypeError):
t.download_output_data = data
def generate_task(self):
task = Task()
task.name = self.name
task.pre_exec = [
'env > env.log', 'export PATH=/home/dakka/miniconda3/bin:$PATH',
'export LD_LIBRARY_PATH=/home/dakka/miniconda3/lib:$LD_LIBRARY_PATH',
'source activate ve_hyperspace'
]
task.executable = ['python']
task.arguments = [
'optimize.py', '--data_path', self.data_path, '--results_dir',
self.results_dir
]
task.cpu_reqs = {
'processes': self.hyperparameters**2,
'process_type': None,
'threads_per_process': 32,
'thread_type': 'MPI'
}
task.upload_input_data = [self.optimization_file]
return task
def test_input_list_from_task():
"""
**Purpose**: Test if the 'get_input_list_from_task' function generates the correct RP input transfer directives
when given a Task
"""
pipeline = str(ru.generate_id('pipeline'))
stage = str(ru.generate_id('stage'))
task = str(ru.generate_id('task'))
placeholder_dict = {
pipeline: {
stage: {
task: '/home/vivek/some_file.txt'
}
}
}
for t in [1, 'a', list(), dict(), True]:
with pytest.raises(TypeError):
t = list()
get_input_list_from_task(t, placeholder_dict)
# Test link input data
t = Task()
t.link_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.link_input_data[0]
assert ip_list[0]['action'] == rp.LINK
assert ip_list[0]['target'] == os.path.basename(t.link_input_data[0])
t = Task()
t.link_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.link_input_data[0].split('>')[0].strip()
assert ip_list[0]['action'] == rp.LINK
assert ip_list[0]['target'] == os.path.basename(t.link_input_data[0].split('>')[1].strip())
# Test copy input data
t = Task()
t.copy_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.copy_input_data[0]
assert ip_list[0]['action'] == rp.COPY
assert ip_list[0]['target'] == os.path.basename(t.copy_input_data[0])
t = Task()
t.copy_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.copy_input_data[0].split('>')[0].strip()
assert ip_list[0]['action'] == rp.COPY
assert ip_list[0]['target'] == os.path.basename(t.copy_input_data[0].split('>')[1].strip())
# Test move input data
t = Task()
t.move_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.move_input_data[0]
assert ip_list[0]['action'] == rp.MOVE
assert ip_list[0]['target'] == os.path.basename(t.move_input_data[0])
t = Task()
t.move_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.move_input_data[0].split('>')[0].strip()
assert ip_list[0]['action'] == rp.MOVE
assert ip_list[0]['target'] == os.path.basename(t.move_input_data[0].split('>')[1].strip())
# Test upload input data
t = Task()
t.upload_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.upload_input_data[0]
assert 'action' not in ip_list[0]
assert ip_list[0]['target'] == os.path.basename(t.upload_input_data[0])
t = Task()
t.upload_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholder_dict)
assert ip_list[0]['source'] == t.upload_input_data[0].split('>')[0].strip()
assert 'action' not in ip_list[0]
assert ip_list[0]['target'] == os.path.basename(t.upload_input_data[0].split('>')[1].strip())
def InitCycle(self, Replicas, Replica_Cores, md_executable, ExchangeMethod, timesteps): # "Cycle" = 1 MD stage plus the subsequent exchange computation
"""
Initial cycle consists of:
1) Create tarball of MD input data
2) Transfer the tarball to pilot sandbox
3) Untar the tarball
4) Run first Cycle
"""
#Initialize Pipeline
#self._prof.prof('InitTar', uid=self._uid)
p = Pipeline()
p.name = 'initpipeline'
md_dict = dict() #Bookkeeping
tar_dict = dict() #Bookkeeping
##Write the input files
self._prof.prof('InitWriteInputs', uid=self._uid)
writeInputs.writeInputs(max_temp=350,min_temp=250,replicas=Replicas,timesteps=timesteps)
self._prof.prof('EndWriteInputs', uid=self._uid)
self._prof.prof('InitTar', uid=self._uid)
#Create Tarball of input data
tar = tarfile.open("Input_Files.tar","w")
for name in ["prmtop", "inpcrd", "mdin"]:
tar.add(name)
for r in range (Replicas):
tar.add('mdin_{0}'.format(r))
tar.close()
#delete all input files outside the tarball
for r in range (Replicas):
os.remove('mdin_{0}'.format(r))
self._prof.prof('EndTar', uid=self._uid)
#Create Untar Stage
untar_stg = Stage()
untar_stg.name = 'untarStg'
#Untar Task
untar_tsk = Task()
untar_tsk.name = 'untartsk'
untar_tsk.executable = ['python']
untar_tsk.upload_input_data = ['untar_input_files.py','Input_Files.tar']
untar_tsk.arguments = ['untar_input_files.py','Input_Files.tar']
untar_tsk.cores = 1
untar_stg.add_tasks(untar_tsk)
p.add_stages(untar_stg)
tar_dict[0] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.name,
untar_stg.name,
untar_tsk.name)
# First MD stage: needs to be defined separately since workflow is not built from a predetermined order
md_stg = Stage()
md_stg.name = 'mdstg0'
self._prof.prof('InitMD_0', uid=self._uid)
# MD tasks
for r in range (Replicas):
md_tsk = AMBERTask(cores=Replica_Cores, MD_Executable=md_executable)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r,cycle=0)
md_tsk.link_input_data += [
'%s/inpcrd'%tar_dict[0],
'%s/prmtop'%tar_dict[0],
'%s/mdin_{0}'.format(r)%tar_dict[0] #Use for full temperature exchange
#'%s/mdin'%tar_dict[0] #Testing only
]
md_tsk.arguments = ['-O','-p','prmtop', '-i', 'mdin_{0}'.format(r), # Use this for full Temperature Exchange
'-c','inpcrd','-o','out_{0}'.format(r),
'-inf','mdinfo_{0}'.format(r)]
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.name, md_stg.name, md_tsk.name)
md_stg.add_tasks(md_tsk)
self.md_task_list.append(md_tsk)
#print md_tsk.uid
p.add_stages(md_stg)
#stage_uids.append(md_stg.uid)
# First Exchange Stage
ex_stg = Stage()
ex_stg.name = 'exstg0'
self._prof.prof('InitEx_0', uid=self._uid)
#with open('logfile.log', 'a') as logfile:
# logfile.write( '%.5f' %time.time() + ',' + 'InitEx0' + '\n')
# Create Exchange Task. Exchange task performs a Metropolis Hastings thermodynamic balance condition
# check and spits out the exchangePairs.dat file that contains a sorted list of ordered pairs.
# Said pairs then exchange configurations by linking output configuration files appropriately.
ex_tsk = Task()
ex_tsk.name = 'extsk0'
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = [ExchangeMethod]
for r in range (Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(md_dict[r],r)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas), '0']
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs_0.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
self.ex_task_list.append(ex_tsk)
#self.ex_task_uids.append(ex_tsk.uid)
self.Book.append(md_dict)
return p
def InitCycle(
self, Replicas, Replica_Cores, md_executable, ExchangeMethod, timesteps
): # "Cycle" = 1 MD stage plus the subsequent exchange computation
"""
Initial cycle consists of:
1) Create tarball of MD input data
2) Transfer the tarball to pilot sandbox
3) Untar the tarball
4) Run first Cycle
"""
#Initialize Pipeline
#self._prof.prof('InitTar', uid=self._uid)
p = Pipeline()
p.name = 'initpipeline'
md_dict = dict() #Bookkeeping
tar_dict = dict() #Bookkeeping
##Write the input files
self._prof.prof('InitWriteInputs', uid=self._uid)
writeInputs.writeInputs(max_temp=350,
min_temp=250,
replicas=Replicas,
timesteps=timesteps)
self._prof.prof('EndWriteInputs', uid=self._uid)
self._prof.prof('InitTar', uid=self._uid)
#Create Tarball of input data
tar = tarfile.open("Input_Files.tar", "w")
for name in ["prmtop", "inpcrd", "mdin"]:
tar.add(name)
for r in range(Replicas):
tar.add('mdin_{0}'.format(r))
tar.close()
#delete all input files outside the tarball
for r in range(Replicas):
os.remove('mdin_{0}'.format(r))
self._prof.prof('EndTar', uid=self._uid)
#Create Untar Stage
untar_stg = Stage()
untar_stg.name = 'untarStg'
#Untar Task
untar_tsk = Task()
untar_tsk.name = 'untartsk'
untar_tsk.executable = ['python']
untar_tsk.upload_input_data = [
'untar_input_files.py', 'Input_Files.tar'
]
untar_tsk.arguments = ['untar_input_files.py', 'Input_Files.tar']
untar_tsk.cores = 1
untar_stg.add_tasks(untar_tsk)
p.add_stages(untar_stg)
tar_dict[0] = '$Pipeline_%s_Stage_%s_Task_%s' % (
p.name, untar_stg.name, untar_tsk.name)
# First MD stage: needs to be defined separately since workflow is not built from a predetermined order
md_stg = Stage()
md_stg.name = 'mdstg0'
self._prof.prof('InitMD_0', uid=self._uid)
# MD tasks
for r in range(Replicas):
md_tsk = AMBERTask(cores=Replica_Cores,
MD_Executable=md_executable)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r, cycle=0)
md_tsk.link_input_data += [
'%s/inpcrd' % tar_dict[0],
'%s/prmtop' % tar_dict[0],
'%s/mdin_{0}'.format(r) %
tar_dict[0] #Use for full temperature exchange
#'%s/mdin'%tar_dict[0] #Testing only
]
md_tsk.arguments = [
'-O',
'-p',
'prmtop',
'-i',
'mdin_{0}'.format(r), # Use this for full Temperature Exchange
'-c',
'inpcrd',
'-o',
'out_{0}'.format(r),
'-inf',
'mdinfo_{0}'.format(r)
]
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s' % (
p.name, md_stg.name, md_tsk.name)
md_stg.add_tasks(md_tsk)
self.md_task_list.append(md_tsk)
#print md_tsk.uid
p.add_stages(md_stg)
#stage_uids.append(md_stg.uid)
# First Exchange Stage
ex_stg = Stage()
ex_stg.name = 'exstg0'
self._prof.prof('InitEx_0', uid=self._uid)
#with open('logfile.log', 'a') as logfile:
# logfile.write( '%.5f' %time.time() + ',' + 'InitEx0' + '\n')
# Create Exchange Task. Exchange task performs a Metropolis Hastings thermodynamic balance condition
# check and spits out the exchangePairs.dat file that contains a sorted list of ordered pairs.
# Said pairs then exchange configurations by linking output configuration files appropriately.
ex_tsk = Task()
ex_tsk.name = 'extsk0'
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = [ExchangeMethod]
for r in range(Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (md_dict[r], r)]
ex_tsk.arguments = ['TempEx.py', '{0}'.format(Replicas), '0']
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs_0.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
self.ex_task_list.append(ex_tsk)
#self.ex_task_uids.append(ex_tsk.uid)
self.Book.append(md_dict)
return p
def test_task_exceptions(s,l,i,b):
"""
**Purpose**: Test if all attribute assignments raise exceptions for invalid values
"""
t = Task()
data_type = [s,l,i,b]
for data in data_type:
if not isinstance(data,str):
with pytest.raises(TypeError):
t.name = data
with pytest.raises(TypeError):
t.path = data
with pytest.raises(TypeError):
t.parent_stage = data
with pytest.raises(TypeError):
t.parent_pipeline = data
with pytest.raises(TypeError):
t.stdout = data
with pytest.raises(TypeError):
t.stderr = data
if not isinstance(data,list):
with pytest.raises(TypeError):
t.pre_exec = data
with pytest.raises(TypeError):
t.arguments = data
with pytest.raises(TypeError):
t.post_exec = data
with pytest.raises(TypeError):
t.upload_input_data = data
with pytest.raises(TypeError):
t.copy_input_data = data
with pytest.raises(TypeError):
t.link_input_data = data
with pytest.raises(TypeError):
t.move_input_data = data
with pytest.raises(TypeError):
t.copy_output_data = data
with pytest.raises(TypeError):
t.download_output_data = data
with pytest.raises(TypeError):
t.move_output_data = data
if not isinstance(data, str) and not isinstance(data, list):
with pytest.raises(TypeError):
t.executable = data
if not isinstance(data, str) and not isinstance(data, unicode):
with pytest.raises(ValueError):
t.cpu_reqs = {
'processes': 1,
'process_type': data,
'threads_per_process': 1,
'thread_type': None
}
t.cpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': 1,
'thread_type': data
}
t.gpu_reqs = {
'processes': 1,
'process_type': data,
'threads_per_process': 1,
'thread_type': None
}
t.gpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': 1,
'thread_type': data
}
if not isinstance(data, int):
with pytest.raises(TypeError):
t.cpu_reqs = {
'processes': data,
'process_type': None,
'threads_per_process': 1,
'thread_type': None
}
t.cpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': data,
'thread_type': None
}
t.gpu_reqs = {
'processes': data,
'process_type': None,
'threads_per_process': 1,
'thread_type': None
}
t.gpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': data,
'thread_type': None
}
def general_cycle(self, replicas, replica_cores, cycle, python_path, md_executable, exchange_method, pre_exec):
"""
All cycles after the initial cycle
Pulls up exchange pairs file and generates the new workflow
"""
self._prof.prof('InitcreateMDwokflow_{0}'.format(cycle), uid=self._uid)
with open('exchangePairs_{0}.dat'.format(cycle),
'r') as f: # Read exchangePairs.dat
exchange_array = []
for line in f:
exchange_array.append(int(line.split()[1]))
#exchange_array.append(line)
#print exchange_array
q = Pipeline()
q.name = 'genpipeline{0}'.format(cycle)
#bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
md_dict = dict()
#Create MD stage
md_stg = Stage()
md_stg.name = 'mdstage{0}'.format(cycle)
self._prof.prof('InitMD_{0}'.format(cycle), uid=self._uid)
for r in range(replicas):
md_tsk = AMBERTask(cores=replica_cores, md_executable=md_executable, pre_exec=pre_exec)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(
replica=r, cycle=cycle)
md_tsk.link_input_data = [
'%s/restrt > inpcrd' %
(self.book[cycle - 1][exchange_array[r]]),
'%s/prmtop' % (self.book[0][r]),
'%s/mdin_{0}'.format(r) % (self.book[0][r])
]
### The Following softlinking scheme is to be used ONLY if node local file system is to be used: not fully supported yet.
#md_tsk.link_input_data = ['$NODE_LFS_PATH/rstrt-{replica}-{cycle}'.format(replica=exchange_array[r],cycle=cycle-1) > '$NODE_LFS_PATH/inpcrd',
# #'%s/restrt > inpcrd'%(self.book[cycle-1][exchange_array[r]]),
# '%s/prmtop'%(self.book[0][r]),
# '%s/mdin_{0}'.format(r)%(self.Book[0][r])]
md_tsk.arguments = [
'-O',
'-i',
'mdin_{0}'.format(r),
'-p',
'prmtop',
'-c',
'inpcrd',
#'-c', 'rstrt-{replica}-{cycle}'.format(replica=r,cycle=cycle-1),
'-o',
'out-{replica}-{cycle}'.format(replica=r, cycle=cycle),
'-r',
'restrt',
#'-r', 'rstrt-{replica}-{cycle}'.format(replica=r,cycle=cycle),
'-x',
'mdcrd-{replica}-{cycle}'.format(replica=r, cycle=cycle),
'-inf',
'mdinfo_{0}'.format(r)
]
#md_tsk.tag = 'mdtsk-{replica}-{cycle}'.format(replica=r,cycle=0)
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s' % (
q.name, md_stg.name, md_tsk.name)
self.md_task_list.append(md_tsk)
md_stg.add_tasks(md_tsk)
q.add_stages(md_stg)
ex_stg = Stage()
ex_stg.name = 'exstg{0}'.format(cycle + 1)
#Create Exchange Task
ex_tsk = Task()
ex_tsk.name = 'extsk{0}'.format(cycle + 1)
ex_tsk.executable = [python_path]#['/usr/bin/python'] #['/opt/python/bin/python']
ex_tsk.upload_input_data = [exchange_method]
for r in range(replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (md_dict[r], r)]
ex_tsk.pre_exec = ['mv *.py exchange_method.py']
ex_tsk.arguments = [
'exchange_method.py', '{0}'.format(replicas), '{0}'.format(cycle + 1)
]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = [
'exchangePairs_{0}.dat'.format(cycle + 1)
] # Finds exchange partners, also Generates exchange history trace
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
self.ex_task_list.append(ex_tsk)
q.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
self.book.append(md_dict)
#self._prof.prof('EndEx_{0}'.format(cycle), uid=self._uid)
#print d
#print self.book
return q
def GenerateTask(tcfg, ecfg, pipe_name, stage_name, task_name):
# Initialize a task object
t = Task()
# Define magic variable dictionary
mvar_dict = {"PIPELINE_ID": pipe_name}
# Give this task object a name
t.name = task_name
# Pre exec let you load modules, set environment before executing the workload
if tcfg['pre_exec'] != "":
t.pre_exec = [tcfg['pre_exec']]
# Executable to use for the task
t.executable = tcfg['executable']
# If there's a user-defined input file (likely for genmod modules), add it to the
# options list and upload file list if needed
if "input_data_file" in tcfg['options']:
tcfg['upload_input_data'].append(
os.path.join(ecfg['exp_dir'], "input", ecfg['input_data_file']))
# List of arguments for the executable
t.arguments = [tcfg['script']] + match_options(tcfg['options'],
ecfg['options'])
# CPU requirements for this task
t.cpu_threads = {
'processes': tcfg['cpu']['processes'],
'process-type': tcfg['cpu']['process-type'],
'threads-per-process': tcfg['cpu']['threads-per-process'],
'thread-type': tcfg['cpu']['thread-type'],
}
# Upload data from your local machine to the remote machine
# Note: Remote machine can be the local machine
t.upload_input_data = tcfg['upload_input_data']
# Copy data from other stages/tasks for use in this task
copy_list = []
if "copy_input_data" in tcfg.keys():
for copy_stage in tcfg['copy_input_data'].keys():
for copy_task in tcfg['copy_input_data'][copy_stage].keys():
loc = "$Pipeline_{0}_Stage_{1}_Task_{2}".format(
pipe_name, copy_stage, copy_task)
copy_list.extend([
'{0}/{1}'.format(loc, mvar_replace_dict(mvar_dict, x))
for x in tcfg['copy_input_data'][copy_stage][copy_task]
])
# Append the copy list (if any) to the task object
t.copy_input_data = copy_list
# Set the download data for the task
download_list = []
outdir = os.path.join(ecfg['exp_dir'], "output")
if "download_output_data" in tcfg.keys():
download_list.extend([
'{0} > {1}/{0}'.format(mvar_replace_dict(mvar_dict, x), outdir)
for x in tcfg['download_output_data']
])
# Append the download list to this task
t.download_output_data = download_list
# Return the task object
return (t)
def init_cycle():
# Create Pipeline Obj
p = Pipeline()
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
d = dict()
dict_tarball = dict()
#Create Tarball stage
tar_stg = Stage()
#Create Tar/untar task
tar_tsk = Task()
tar_tsk.executable = ['python']
tar_tsk.upload_input_data = ['Input_Files.tar', 'untar_input_files.py']
tar_tsk.arguments = ['untar_input_files.py', 'Input_Files.tar']
tar_tsk.cores = 1
tar_stg.add_tasks(tar_tsk)
#task_uids.append(tar_tsk.uid)
p.add_stages(tar_stg)
#stage_uids.append(tar_stg.uid)
dict_tarball[0] = '$Pipeline_%s_Stage_%s_Task_%s' % (p.uid, tar_stg.uid,
tar_tsk.uid)
#Create initial MD stage
md_stg = Stage()
#Create MD task
for n0 in range(Replicas):
md_tsk = Task()
md_tsk.executable = [
'/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'
] #MD Engine, BW
#md_tsk.executable = ['/usr/local/packages/amber/16/INTEL-140-MVAPICH2-2.0/bin/pmemd.MPI'] #MD Engine, SuperMIC
#md_tsk.executable = ['/opt/amber/bin/pmemd.MPI']
#md_tsk.upload_input_data = ['inpcrd', 'prmtop', 'mdin_{0}'.format(n0)]
#md_tsk.upload_input_data = ['inpcrd','prmtop','mdin']
md_tsk.link_input_data += [
'%s/inpcrd' % dict_tarball[0],
'%s/prmtop' % dict_tarball[0],
'%s/mdin' % dict_tarball[0]
]
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/']
#md_tsk.pre_exec = ['module load amber']
#md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0), '-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.arguments = [
'-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o',
'out_{0}'.format(n0), '-inf', 'mdinfo_{0}'.format(n0)
]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
d[n0] = '$Pipeline_%s_Stage_%s_Task_%s' % (p.uid, md_stg.uid,
md_tsk.uid)
md_stg.add_tasks(md_tsk)
task_uids.append(md_tsk.uid)
p.add_stages(md_stg)
stage_uids.append(md_stg.uid)
#print d
#Create Exchange Stage
ex_stg = Stage()
#Create Exchange Task
ex_tsk = Task()
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
for n1 in range(Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (d[n1], n1)]
ex_tsk.arguments = ['TempEx.py', '{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
stage_uids.append(ex_stg.uid)
Book.append(d)
#print Book
return p
def Cycle(Replicas, Replica_Cores, Cycles, MD_Executable, ExchangeMethod):
"""
All cycles after the initial cycle
"""
with open("exchangePairs.dat","r") as f: # Read exchangePairs.dat
ExchangeArray = []
for line in f:
ExchangeArray.append(int(line.split()[1]))
#ExchangeArray.append(line)
#print ExchangeArray
q = Pipeline()
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
md_dict = dict()
#Create initial MD stage
md_stg = Stage()
for r in range (Replicas):
md_tsk = Task()
md_tsk.executable = [MD_Executable] #MD Engine, Blue Waters
md_tsk.link_input_data = ['%s/restrt > inpcrd'%(Book[Cycle-1][ExchangeArray[r]]),
'%s/prmtop'%(Book[Cycle-1][r]),
#'%s/mdin_{0}'.format(r)%(Book[k-1][r])]
'%s/mdin'%(Book[Cycle-1][r])]
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/'] # Should be abstracted from user?
#md_tsk.pre_exec = ['module load amber']
#md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0),'-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(r),'-inf', 'mdinfo_{0}'.format(r)]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid, md_stg.uid, md_tsk.uid)
md_stg.add_tasks(md_tsk)
#task_uids.append(md_tsk.uid)
q.add_stages(md_stg)
ex_stg= Stage()
#Create Exchange Task
ex_tsk = Task()
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
for n1 in range (Replicas):
#print d[n1]
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(d[n1],n1)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
q.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
Book.append(md_dict)
#print d
#print Book
return q
#p = InitCycle(Replicas, Replica_Cores, MD_Executable, ExchangeMethod)
#q = Cycle(Replicas, Replica_Cores, Cycles, MD_Executable, ExchangeMethod)
#return (p, q)
def generate_pipeline(cfg):
cfg_file = cfg['run_cfg_file'] # resource and workload config
run_file = cfg['run_file'] # runs for this campaign
# setup S1 workload
cfg = ru.Config(cfg=ru.read_json(cfg_file))
runs = check_runs(cfg_file, run_file)
if not runs:
print('S1: nothing to run, exiting.')
return
# for each run in the campaign:
# - create cfg with requested receptor and smiles
# - create a number of masters as EnTK tasks and add them to a pipeline
# - submit configured number of masters with that cfg
# setup EnTK pipeline
p = Pipeline()
p.name = 'S1-RAPTOR'
s = Stage()
# create cfg
subs = dict()
rurl = cfg.fs_url + cfg.workload.results
d = rs.filesystem.Directory(rurl)
ls = [str(u).split('/')[-1] for u in d.list()]
workload = cfg.workload
for receptor, smiles, nodes, runtime in runs:
print('%30s %s' % (receptor, smiles))
name = '%s_-_%s' % (receptor, smiles)
tgt = '%s.%s.gz' % (name, workload.output)
# rec = False
# if tgt in ls:
# if workload.recompute:
# rec += 1
# d.move(tgt, tgt + '.bak')
# else:
# print('skip 1 %s' % name)
# continue
# if smiles in ls:
# if smiles not in subs:
# subs[smiles] = [str(u).split('/')[-1] for u in d.list('%s/*' % smiles)]
# if tgt in subs[smiles]:
# if workload.recompute:
# rec += 2
# d.move('%s/%s' % (smiles, tgt),
# '%s/%s.bak' % (smiles, tgt))
# else:
# print('skip 2 %s' % name)
# continue
## if os.path.exists('results/%s.%s.gz' % (name, wofkload.output)):
## print('skip 3 %s' % name)
## continue
#if rec: print('recompute %d %s' % (rec, name))
#else : print('compute 2 %s' % name)
cpn = cfg.cpn
gpn = cfg.gpn
n_masters = cfg.n_masters
cfg.workload.receptor = receptor
cfg.workload.smiles = smiles
cfg.workload.name = name
cfg.nodes = nodes
cfg.runtime = runtime
cfg.n_workers = int(nodes / n_masters - 1)
print('n_workers: %d' % cfg.n_workers)
ru.write_json(cfg, 'configs/wf0.%s.cfg' % name)
for i in range(n_masters):
t = Task()
t.pre_exec = [
'. /gpfs/alpine/scratch/mturilli1/med110/radical.pilot.sandbox/s1.to/bin/activate'
]
t.executable = "python3"
t.arguments = ['wf0_master.py', i]
t.cpu_threads = cpn
t.upload_input_data = [
'wf0_master.py', 'wf0_worker.py',
'configs/wf0.%s.cfg > wf0.cfg' % name, 'read_ligand_dict.py'
]
t.link_input_data = ['%s > input_dir' % workload.input_dir]
t.download_output_data = [
'%s.%s.gz > results/%s.%s.gz' %
(name, workload.output, name, workload.output)
]
# t.input_staging = [{'source': 'wf0_master.py',
# 'target': 'wf0_master.py',
# 'action': rp.TRANSFER,
# 'flags' : rp.DEFAULT_FLAGS},
# {'source': 'wf0_worker.py',
# 'target': 'wf0_worker.py',
# 'action': rp.TRANSFER,
# 'flags' : rp.DEFAULT_FLAGS},
# {'source': 'configs/wf0.%s.cfg' % name,
# 'target': 'wf0.cfg',
# 'action': rp.TRANSFER,
# 'flags' : rp.DEFAULT_FLAGS},
# {'source': workload.input_dir,
# 'target': 'input_dir',
# 'action': rp.LINK,
# 'flags' : rp.DEFAULT_FLAGS},
# {'source': workload.impress_dir,
# 'target': 'impress_md',
# 'action': rp.LINK,
# 'flags' : rp.DEFAULT_FLAGS},
# {'source': 'read_ligand_dict.py',
# 'target': 'read_ligand_dict.py',
# 'action': rp.TRANSFER,
# 'flags' : rp.DEFAULT_FLAGS},
# ]
# t.output_staging = [{'source': '%s.%s.gz' % (name, workload.output),
# 'target': 'results/%s.%s.gz' % (name, workload.output),
# 'action': rp.TRANSFER,
# 'flags' : rp.DEFAULT_FLAGS}]
s.add_tasks(t)
p.add_stages(s)
return p
def cycle(k):
#read exchangePairs.dat
#
with open("exchangePairs.dat", "r") as f:
ExchangeArray = []
for line in f:
ExchangeArray.append(int(line.split()[1]))
#ExchangeArray.append(line)
#print ExchangeArray
p = Pipeline()
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
d = dict()
#Create initial MD stage
md_stg = Stage()
#Create MD task
for n0 in range(Replicas):
md_tsk = Task()
md_tsk.executable = [
'/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'
] #MD Engine, Blue Waters
#md_tsk.executable = ['/usr/local/packages/amber/16/INTEL-140-MVAPICH2-2.0/bin/pmemd.MPI'] #MD Engine, SuperMIC
#md_tsk.executable = ['/opt/amber/bin/pmemd.MPI']
md_tsk.link_input_data = [
'%s/restrt > inpcrd' % (Book[k - 1][ExchangeArray[n0]]),
'%s/prmtop' % (Book[k - 1][n0]),
#'%s/mdin_{0}'.format(n0)%(Book[k-1][n0])]
'%s/mdin' % (Book[k - 1][n0])
]
##Above: Copy from previous PIPELINE, make sure bookkeeping is correct
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/'
] #Preexec, BLue Waters
#md_tsk.pre_exec = ['module load amber']
#md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0),'-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.arguments = [
'-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o',
'out_{0}'.format(n0), '-inf', 'mdinfo_{0}'.format(n0)
]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
d[n0] = '$Pipeline_%s_Stage_%s_Task_%s' % (p.uid, md_stg.uid,
md_tsk.uid)
#print d
md_stg.add_tasks(md_tsk)
task_uids.append(md_tsk.uid)
p.add_stages(md_stg)
stage_uids.append(md_stg.uid)
#Create exchange stage
ex_stg = Stage()
#Create Exchange Task
ex_tsk = Task()
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
for n1 in range(Replicas):
#print d[n1]
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (d[n1], n1)]
ex_tsk.arguments = ['TempEx.py', '{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
stage_uids.append(ex_stg.uid)
Book.append(d)
#print d
#print Book
return p
def init_cycle():
# Create Pipeline Obj
p = Pipeline()
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
d = dict()
dict_tarball = dict()
#Create Tarball stage
tar_stg = Stage()
#Create Tar/untar task
tar_tsk = Task()
tar_tsk.executable = ['python']
tar_tsk.upload_input_data = ['Input_Files.tar', 'untar_input_files.py']
tar_tsk.arguments = ['untar_input_files.py','Input_Files.tar']
tar_tsk.cores = 1
tar_stg.add_tasks(tar_tsk)
#task_uids.append(tar_tsk.uid)
p.add_stages(tar_stg)
#stage_uids.append(tar_stg.uid)
dict_tarball[0] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid,tar_stg.uid,tar_tsk.uid)
#Create initial MD stage
md_stg = Stage()
#Create MD task
for n0 in range (Replicas):
md_tsk = Task()
md_tsk.executable = ['/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'] #MD Engine, BW
#md_tsk.executable = ['/usr/local/packages/amber/16/INTEL-140-MVAPICH2-2.0/bin/pmemd.MPI'] #MD Engine, SuperMIC
#md_tsk.executable = ['/opt/amber/bin/pmemd.MPI']
#md_tsk.upload_input_data = ['inpcrd', 'prmtop', 'mdin_{0}'.format(n0)]
#md_tsk.upload_input_data = ['inpcrd','prmtop','mdin']
md_tsk.link_input_data += ['%s/inpcrd'%dict_tarball[0],
'%s/prmtop'%dict_tarball[0],
'%s/mdin'%dict_tarball[0]]
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/']
#md_tsk.pre_exec = ['module load amber']
#md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0), '-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0), '-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
d[n0] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid, md_stg.uid, md_tsk.uid)
md_stg.add_tasks(md_tsk)
task_uids.append(md_tsk.uid)
p.add_stages(md_stg)
stage_uids.append(md_stg.uid)
#print d
#Create Exchange Stage
ex_stg = Stage()
#Create Exchange Task
ex_tsk = Task()
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
for n1 in range (Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(d[n1],n1)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
stage_uids.append(ex_stg.uid)
Book.append(d)
#print Book
return p
def cycle(k):
#read exchangePairs.dat
#
with open("exchangePairs.dat","r") as f:
ExchangeArray = []
for line in f:
ExchangeArray.append(int(line.split()[1]))
#ExchangeArray.append(line)
#print ExchangeArray
p = Pipeline()
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
d = dict()
#Create initial MD stage
md_stg = Stage()
#Create MD task
for n0 in range (Replicas):
md_tsk = Task()
md_tsk.executable = ['/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'] #MD Engine, Blue Waters
#md_tsk.executable = ['/usr/local/packages/amber/16/INTEL-140-MVAPICH2-2.0/bin/pmemd.MPI'] #MD Engine, SuperMIC
#md_tsk.executable = ['/opt/amber/bin/pmemd.MPI']
md_tsk.link_input_data = ['%s/restrt > inpcrd'%(Book[k-1][ExchangeArray[n0]]),
'%s/prmtop'%(Book[k-1][n0]),
#'%s/mdin_{0}'.format(n0)%(Book[k-1][n0])]
'%s/mdin'%(Book[k-1][n0])]
##Above: Copy from previous PIPELINE, make sure bookkeeping is correct
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/'] #Preexec, BLue Waters
#md_tsk.pre_exec = ['module load amber']
#md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0),'-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0),'-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
d[n0] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid, md_stg.uid, md_tsk.uid)
#print d
md_stg.add_tasks(md_tsk)
task_uids.append(md_tsk.uid)
p.add_stages(md_stg)
stage_uids.append(md_stg.uid)
#Create exchange stage
ex_stg= Stage()
#Create Exchange Task
ex_tsk = Task()
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
for n1 in range (Replicas):
#print d[n1]
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(d[n1],n1)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
stage_uids.append(ex_stg.uid)
Book.append(d)
#print d
#print Book
return p
def test_task_to_dict():
"""
**Purpose**: Test if the 'to_dict' function of Task class converts all expected attributes of the Task into a
dictionary
"""
t = Task()
d = t.to_dict()
assert d == { 'uid': None,
'name': None,
'state': states.INITIAL,
'state_history': [states.INITIAL],
'pre_exec': [],
'executable': str(),
'arguments': [],
'post_exec': [],
'cpu_reqs': { 'processes': 1,
'process_type': None,
'threads_per_process': 1,
'thread_type': None
},
'gpu_reqs': { 'processes': 0,
'process_type': None,
'threads_per_process': 0,
'thread_type': None
},
'lfs_per_process': 0,
'upload_input_data': [],
'copy_input_data': [],
'link_input_data': [],
'move_input_data': [],
'copy_output_data': [],
'move_output_data': [],
'download_output_data': [],
'stdout': None,
'stderr': None,
'exit_code': None,
'path': None,
'tag': None,
'parent_stage': {'uid':None, 'name': None},
'parent_pipeline': {'uid':None, 'name': None}}
t = Task()
t.uid = 'test.0000'
t.name = 'new'
t.pre_exec = ['module load abc']
t.executable = ['sleep']
t.arguments = ['10']
t.cpu_reqs['processes'] = 10
t.cpu_reqs['threads_per_process'] = 2
t.gpu_reqs['processes'] = 5
t.gpu_reqs['threads_per_process'] = 3
t.lfs_per_process = 1024
t.upload_input_data = ['test1']
t.copy_input_data = ['test2']
t.link_input_data = ['test3']
t.move_input_data = ['test4']
t.copy_output_data = ['test5']
t.move_output_data = ['test6']
t.download_output_data = ['test7']
t.stdout = 'out'
t.stderr = 'err'
t.exit_code = 1
t.path = 'a/b/c'
t.tag = 'task.0010'
t.parent_stage = {'uid': 's1', 'name': 'stage1'}
t.parent_pipeline = {'uid': 'p1', 'name': 'pipeline1'}
d = t.to_dict()
assert d == { 'uid': 'test.0000',
'name': 'new',
'state': states.INITIAL,
'state_history': [states.INITIAL],
'pre_exec': ['module load abc'],
'executable': 'sleep',
'arguments': ['10'],
'post_exec': [],
'cpu_reqs': { 'processes': 10,
'process_type': None,
'threads_per_process': 2,
'thread_type': None
},
'gpu_reqs': { 'processes': 5,
'process_type': None,
'threads_per_process': 3,
'thread_type': None
},
'lfs_per_process': 1024,
'upload_input_data': ['test1'],
'copy_input_data': ['test2'],
'link_input_data': ['test3'],
'move_input_data': ['test4'],
'copy_output_data': ['test5'],
'move_output_data': ['test6'],
'download_output_data': ['test7'],
'stdout': 'out',
'stderr': 'err',
'exit_code': 1,
'path': 'a/b/c',
'tag': 'task.0010',
'parent_stage': {'uid': 's1', 'name': 'stage1'},
'parent_pipeline': {'uid': 'p1', 'name': 'pipeline1'}}
t.executable = 'sleep'
d = t.to_dict()
assert d == { 'uid': 'test.0000',
'name': 'new',
'state': states.INITIAL,
'state_history': [states.INITIAL],
'pre_exec': ['module load abc'],
'executable': 'sleep',
'arguments': ['10'],
'post_exec': [],
'cpu_reqs': { 'processes': 10,
'process_type': None,
'threads_per_process': 2,
'thread_type': None
},
'gpu_reqs': { 'processes': 5,
'process_type': None,
'threads_per_process': 3,
'thread_type': None
},
'lfs_per_process': 1024,
'upload_input_data': ['test1'],
'copy_input_data': ['test2'],
'link_input_data': ['test3'],
'move_input_data': ['test4'],
'copy_output_data': ['test5'],
'move_output_data': ['test6'],
'download_output_data': ['test7'],
'stdout': 'out',
'stderr': 'err',
'exit_code': 1,
'path': 'a/b/c',
'tag': 'task.0010',
'parent_stage': {'uid': 's1', 'name': 'stage1'},
'parent_pipeline': {'uid': 'p1', 'name': 'pipeline1'}}
def InitCycle(Replicas, Replica_Cores, MD_Executable, ExchangeMethod): # "Cycle" = 1 MD stage plus the subsequent exchange computation
#Initialize Pipeline
p = Pipeline()
md_dict = dict() #Bookkeeping
tar_dict = dict() #Bookkeeping
#Create Tarball of input data
#Create Untar Stage
untar_stg = Stage()
#Untar Task
untar_tsk = Task()
untar_tsk.executable = ['python']
untar_tsk.upload_input_data = ['untar_input_files.py','../../Input_Files.tar']
untar_tsk.arguments = ['untar_input_files.py','Input_Files.tar']
untar_tsk.cores = 1
untar_stg.add_tasks(untar_tsk)
p.add_stages(untar_stg)
tar_dict[0] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid,
untar_stg.uid,
untar_tsk.uid)
print tar_dict[0]
# First MD stage: needs to be defined separately since workflow is not built from a predetermined order
md_stg = Stage()
# MD tasks
for r in range (Replicas):
md_tsk = Task()
md_tsk.executable = [MD_Executable]
md_tsk.link_input_data += ['%s/inpcrd'%tar_dict[0],
'%s/prmtop'%tar_dict[0],
#'%s/mdin_{0}'.format(r)%tar_dict[0]
'%s/mdin'%tar_dict[0]
]
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/'] #Should be abstracted from the user?
md_tsk.arguments = ['-O','-p','prmtop', '-i', 'mdin', #'mdin_{0}'.format(r), # Use this for full Temperature Exchange
'-c','inpcrd','-o','out_{0}'.format(r),
'-inf','mdinfo_{0}'.format(r)]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid, md_stg.uid, md_tsk.uid)
md_stg.add_tasks(md_tsk)
#task_uids.append(md_tsk.uid)
p.add_stages(md_stg)
#stage_uids.append(md_stg.uid)
# First Exchange Stage
ex_stg = Stage()
# Create Exchange Task. Exchange task performs a Metropolis Hastings thermodynamic balance condition
# and spits out the exchangePairs.dat file that contains a sorted list of ordered pairs.
# Said pairs then exchange configurations by linking output configuration files appropriately.
ex_tsk = Task()
ex_tsk.executable = ['python']
#ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
ex_tsk.upload_input_data = [ExchangeMethod]
for r in range (Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(md_dict[r],r)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
Book.append(md_dict)
#print Book
return p
def test_input_list_from_task():
"""
**Purpose**: Test if the 'get_input_list_from_task' function generates the
correct RP input transfer directives when given a Task.
"""
pipeline = str(ru.generate_id('pipeline'))
stage = str(ru.generate_id('stage'))
task = str(ru.generate_id('task'))
placeholders = {pipeline: {stage: {task: '/home/vivek/some_file.txt'}}}
for t in [1, 'a', list(), dict(), True]:
with pytest.raises(TypeError):
t = list()
get_input_list_from_task(t, placeholders)
# Test link input data
t = Task()
t.link_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert ip_list[0]['action'] == rp.LINK
assert ip_list[0]['source'] == t.link_input_data[0]
assert ip_list[0]['target'] == os.path.basename(t.link_input_data[0])
t = Task()
t.link_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert ip_list[0]['action'] == rp.LINK
assert ip_list[0]['source'] == t.link_input_data[0].split('>')[0].strip()
assert ip_list[0]['target'] == os.path.basename(
t.link_input_data[0].split('>')[1].strip())
# Test copy input data
t = Task()
t.copy_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert ip_list[0]['action'] == rp.COPY
assert ip_list[0]['source'] == t.copy_input_data[0]
assert ip_list[0]['target'] == os.path.basename(t.copy_input_data[0])
t = Task()
t.copy_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert ip_list[0]['action'] == rp.COPY
assert ip_list[0]['source'] == t.copy_input_data[0].split('>')[0].strip()
assert ip_list[0]['target'] == os.path.basename(
t.copy_input_data[0].split('>')[1].strip())
# Test move input data
t = Task()
t.move_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert ip_list[0]['action'] == rp.MOVE
assert ip_list[0]['source'] == t.move_input_data[0]
assert ip_list[0]['target'] == os.path.basename(t.move_input_data[0])
t = Task()
t.move_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert ip_list[0]['action'] == rp.MOVE
assert ip_list[0]['source'] == t.move_input_data[0].split('>')[0].strip()
assert ip_list[0]['target'] == os.path.basename(
t.move_input_data[0].split('>')[1].strip())
# Test upload input data
t = Task()
t.upload_input_data = ['/home/vivek/test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert 'action' not in ip_list[0]
assert ip_list[0]['source'] == t.upload_input_data[0]
assert ip_list[0]['target'] == os.path.basename(t.upload_input_data[0])
t = Task()
t.upload_input_data = ['/home/vivek/test.dat > new_test.dat']
ip_list = get_input_list_from_task(t, placeholders)
assert 'action' not in ip_list[0]
assert ip_list[0]['source'] == t.upload_input_data[0].split('>')[0].strip()
assert ip_list[0]['target'] == os.path.basename(
t.upload_input_data[0].split('>')[1].strip())
def Cycle(Replicas, Replica_Cores, Cycles, MD_Executable, ExchangeMethod):
"""
All cycles after the initial cycle
"""
with open("exchangePairs.dat","r") as f: # Read exchangePairs.dat
ExchangeArray = []
for line in f:
ExchangeArray.append(int(line.split()[1]))
#ExchangeArray.append(line)
#print ExchangeArray
q = Pipeline()
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
md_dict = dict()
#Create initial MD stage
md_stg = Stage()
for r in range (Replicas):
md_tsk = Task()
md_tsk.executable = [MD_Executable] #MD Engine, Blue Waters
md_tsk.link_input_data = ['%s/restrt > inpcrd'%(Book[Cycle-1][ExchangeArray[r]]),
'%s/prmtop'%(Book[Cycle-1][r]),
#'%s/mdin_{0}'.format(r)%(Book[k-1][r])]
'%s/mdin'%(Book[Cycle-1][r])]
md_tsk.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/'] # Should be abstracted from user?
#md_tsk.pre_exec = ['module load amber']
#md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(n0),'-inf', 'mdinfo_{0}'.format(n0)]
md_tsk.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(r),'-inf', 'mdinfo_{0}'.format(r)]
md_tsk.cores = Replica_Cores
md_tsk.mpi = True
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s'%(p.uid, md_stg.uid, md_tsk.uid)
md_stg.add_tasks(md_tsk)
#task_uids.append(md_tsk.uid)
q.add_stages(md_stg)
ex_stg= Stage()
#Create Exchange Task
ex_tsk = Task()
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = ['exchangeMethods/TempEx.py']
for n1 in range (Replicas):
#print d[n1]
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(d[n1],n1)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
q.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
Book.append(md_dict)
#print d
#print Book
return q
def test_create_cud_from_task():
"""
**Purpose**: Test if the 'create_cud_from_task' function generates a RP
ComputeUnitDescription with the complete Task description.
"""
pipeline = 'p1'
stage = 's1'
task = 't1'
placeholders = {pipeline: {stage: {task: '/home/vivek/some_file.txt'}}}
t1 = Task()
t1.name = 't1'
t1.pre_exec = ['module load gromacs']
t1.executable = 'grompp'
t1.arguments = ['hello']
t1.cpu_reqs = {
'processes': 4,
'process_type': 'MPI',
'threads_per_process': 1,
'thread_type': 'OpenMP'
}
t1.gpu_reqs = {
'processes': 4,
'process_type': 'MPI',
'threads_per_process': 2,
'thread_type': 'OpenMP'
}
t1.post_exec = ['echo test']
t1.upload_input_data = ['upload_input.dat']
t1.copy_input_data = ['copy_input.dat']
t1.link_input_data = ['link_input.dat']
t1.copy_output_data = ['copy_output.dat']
t1.download_output_data = ['download_output.dat']
p = Pipeline()
p.name = 'p1'
s = Stage()
s.name = 's1'
s.tasks = t1
p.stages = s
cud = create_cud_from_task(t1, placeholders)
assert cud.name == '%s,%s,%s,%s,%s,%s' % (
t1.uid, t1.name, t1.parent_stage['uid'], t1.parent_stage['name'],
t1.parent_pipeline['uid'], t1.parent_pipeline['name'])
assert cud.pre_exec == t1.pre_exec
# rp returns executable as a string regardless of whether assignment was using string or list
assert cud.executable == t1.executable
assert cud.arguments == t1.arguments
assert cud.post_exec == t1.post_exec
assert cud.cpu_processes == t1.cpu_reqs['processes']
assert cud.cpu_threads == t1.cpu_reqs['threads_per_process']
assert cud.cpu_process_type == t1.cpu_reqs['process_type']
assert cud.cpu_thread_type == t1.cpu_reqs['thread_type']
assert cud.gpu_processes == t1.gpu_reqs['processes']
assert cud.gpu_threads == t1.gpu_reqs['threads_per_process']
assert cud.gpu_process_type == t1.gpu_reqs['process_type']
assert cud.gpu_thread_type == t1.gpu_reqs['thread_type']
assert {
'source': 'upload_input.dat',
'target': 'upload_input.dat'
} in cud.input_staging
assert {
'source': 'copy_input.dat',
'action': rp.COPY,
'target': 'copy_input.dat'
} in cud.input_staging
assert {
'source': 'link_input.dat',
'action': rp.LINK,
'target': 'link_input.dat'
} in cud.input_staging
assert {
'source': 'copy_output.dat',
'action': rp.COPY,
'target': 'copy_output.dat'
} in cud.output_staging
assert {
'source': 'download_output.dat',
'target': 'download_output.dat'
} in cud.output_staging
def test_create_cud_from_task():
"""
**Purpose**: Test if the 'create_cud_from_task' function generates a RP ComputeUnitDescription with the complete
Task description
"""
pipeline = 'p1'
stage = 's1'
task = 't1'
placeholder_dict = {
pipeline: {
stage: {
task: '/home/vivek/some_file.txt'
}
}
}
t1 = Task()
t1.name = 't1'
t1.pre_exec = ['module load gromacs']
t1.executable = ['grompp']
t1.arguments = ['hello']
t1.cpu_reqs = {'processes': 4,
'process_type': 'MPI',
'threads_per_process': 1,
'thread_type': 'OpenMP'
}
t1.gpu_reqs = {'processes': 4,
'process_type': 'MPI',
'threads_per_process': 2,
'thread_type': 'OpenMP'
}
t1.post_exec = ['echo test']
t1.upload_input_data = ['upload_input.dat']
t1.copy_input_data = ['copy_input.dat']
t1.link_input_data = ['link_input.dat']
t1.copy_output_data = ['copy_output.dat']
t1.download_output_data = ['download_output.dat']
p = Pipeline()
p.name = 'p1'
s = Stage()
s.name = 's1'
s.tasks = t1
p.stages = s
p._assign_uid('test')
cud = create_cud_from_task(t1, placeholder_dict)
assert cud.name == '%s,%s,%s,%s,%s,%s' % (t1.uid, t1.name,
t1.parent_stage['uid'], t1.parent_stage['name'],
t1.parent_pipeline['uid'], t1.parent_pipeline['name'])
assert cud.pre_exec == t1.pre_exec
# rp returns executable as a string regardless of whether assignment was using string or list
assert cud.executable == t1.executable
assert cud.arguments == t1.arguments
assert cud.cpu_processes == t1.cpu_reqs['processes']
assert cud.cpu_threads == t1.cpu_reqs['threads_per_process']
assert cud.cpu_process_type == t1.cpu_reqs['process_type']
assert cud.cpu_thread_type == t1.cpu_reqs['thread_type']
assert cud.gpu_processes == t1.gpu_reqs['processes']
assert cud.gpu_threads == t1.gpu_reqs['threads_per_process']
assert cud.gpu_process_type == t1.gpu_reqs['process_type']
assert cud.gpu_thread_type == t1.gpu_reqs['thread_type']
assert cud.post_exec == t1.post_exec
assert {'source': 'upload_input.dat', 'target': 'upload_input.dat'} in cud.input_staging
assert {'source': 'copy_input.dat', 'action': rp.COPY, 'target': 'copy_input.dat'} in cud.input_staging
assert {'source': 'link_input.dat', 'action': rp.LINK, 'target': 'link_input.dat'} in cud.input_staging
assert {'source': 'copy_output.dat', 'action': rp.COPY, 'target': 'copy_output.dat'} in cud.output_staging
assert {'source': 'download_output.dat', 'target': 'download_output.dat'} in cud.output_staging
p = Pipeline()
# Bookkeeping
stage_uids = list()
task_uids = dict()
Stages = 1
Replicas = 2
for N_Stg in range(Stages):
stg = Stage() ## initialization
task_uids['Stage_%s'%N_Stg] = list()
if N_Stg == 0:
for n0 in range(Replicas):
t = Task()
t.executable = ['/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'] #MD Engine
t.upload_input_data = ['inpcrd', 'prmtop', 'mdin']
t.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/']
t.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out']
t.cores = 32
t.mpi = True
stg.add_tasks(t)
task_uids['Stage_%s'%N_Stg].append(t.uid)
p.add_stages(stg)
stage_uids.append(stg.uid)
else:
for n0 in range(Replicas):
t = Task()
t.executable = ['/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'] #MD Engine
def init_cycle(self, replicas, replica_cores, python_path, md_executable, exchange_method, min_temp, max_temp, timesteps, basename, pre_exec): # "cycle" = 1 MD stage plus the subsequent exchange computation
"""
Initial cycle consists of:
1) Create tarball of MD input data
2) Transfer the tarball to pilot sandbox
3) Untar the tarball
4) Run first cycle
"""
#Initialize Pipeline
self._prof.prof('InitTar', uid=self._uid)
p = Pipeline()
p.name = 'initpipeline'
md_dict = dict() #bookkeeping
tar_dict = dict() #bookkeeping
#Write the input files
self._prof.prof('InitWriteInputs', uid=self._uid)
writeInputs.writeInputs(
max_temp=max_temp,
min_temp=min_temp,
replicas=replicas,
timesteps=timesteps,
basename=basename)
self._prof.prof('EndWriteInputs', uid=self._uid)
self._prof.prof('InitTar', uid=self._uid)
#Create Tarball of input data
tar = tarfile.open("input_files.tar", "w")
for name in [
basename + ".prmtop", basename + ".inpcrd", basename + ".mdin"
]:
tar.add(name)
for r in range(replicas):
tar.add('mdin_{0}'.format(r))
tar.close()
#delete all input files outside the tarball
for r in range(replicas):
os.remove('mdin_{0}'.format(r))
self._prof.prof('EndTar', uid=self._uid)
#Create Untar Stage
repo = git.Repo('.', search_parent_directories=True)
aux_function_path = repo.working_tree_dir
untar_stg = Stage()
untar_stg.name = 'untarStg'
#Untar Task
untar_tsk = Task()
untar_tsk.name = 'untartsk'
untar_tsk.executable = ['python']
untar_tsk.upload_input_data = [
str(aux_function_path)+'/repex/untar_input_files.py', 'input_files.tar'
]
untar_tsk.arguments = ['untar_input_files.py', 'input_files.tar']
untar_tsk.cpu_reqs = 1
#untar_tsk.post_exec = ['']
untar_stg.add_tasks(untar_tsk)
p.add_stages(untar_stg)
tar_dict[0] = '$Pipeline_%s_Stage_%s_Task_%s' % (
p.name, untar_stg.name, untar_tsk.name)
# First MD stage: needs to be defined separately since workflow is not built from a predetermined order, also equilibration needs to happen first.
md_stg = Stage()
md_stg.name = 'mdstg0'
self._prof.prof('InitMD_0', uid=self._uid)
# MD tasks
for r in range(replicas):
md_tsk = AMBERTask(cores=replica_cores, md_executable=md_executable, pre_exec=pre_exec)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r, cycle=0)
md_tsk.link_input_data += [
'%s/inpcrd' % tar_dict[0],
'%s/prmtop' % tar_dict[0],
'%s/mdin_{0}'.format(r) %
tar_dict[0] #Use for full temperature exchange
]
md_tsk.arguments = [
'-O',
'-p',
'prmtop',
'-i',
'mdin_{0}'.format(r),
'-c',
'inpcrd',
'-o',
'out-{replica}-{cycle}'.format(replica=r, cycle=0),
'-r',
'restrt'.format(replica=r, cycle=0),
#'-r', 'rstrt-{replica}-{cycle}'.format(replica=r,cycle=0),
'-x',
'mdcrd-{replica}-{cycle}'.format(replica=r, cycle=0),
#'-o', '$NODE_LFS_PATH/out-{replica}-{cycle}'.format(replica=r,cycle=0),
#'-r', '$NODE_LFS_PATH/rstrt-{replica}-{cycle}'.format(replica=r,cycle=0),
#'-x', '$NODE_LFS_PATH/mdcrd-{replica}-{cycle}'.format(replica=r,cycle=0),
'-inf',
'mdinfo_{0}'.format(r)
]
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s' % (
p.name, md_stg.name, md_tsk.name)
md_stg.add_tasks(md_tsk)
self.md_task_list.append(md_tsk)
#print md_tsk.uid
p.add_stages(md_stg)
#stage_uids.append(md_stg.uid)
# First Exchange Stage
ex_stg = Stage()
ex_stg.name = 'exstg0'
self._prof.prof('InitEx_0', uid=self._uid)
# Create Exchange Task
ex_tsk = Task()
ex_tsk.name = 'extsk0'
#ex_tsk.pre_exec = ['module load python/2.7.10']
ex_tsk.executable = [python_path]
ex_tsk.upload_input_data = [exchange_method]
for r in range(replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (md_dict[r], r)]
ex_tsk.pre_exec = ['mv *.py exchange_method.py']
ex_tsk.arguments = ['exchange_method.py', '{0}'.format(replicas), '0']
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs_0.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
self.ex_task_list.append(ex_tsk)
#self.ex_task_uids.append(ex_tsk.uid)
self.book.append(md_dict)
return p
def test_task_exceptions(s, l, i, b):
"""
**Purpose**: Test if all attribute assignments raise exceptions for invalid values
"""
t = Task()
data_type = [s, l, i, b]
for data in data_type:
if not isinstance(data, str):
with pytest.raises(TypeError):
t.name = data
with pytest.raises(TypeError):
t.path = data
with pytest.raises(TypeError):
t.parent_stage = data
with pytest.raises(TypeError):
t.parent_pipeline = data
with pytest.raises(TypeError):
t.stdout = data
with pytest.raises(TypeError):
t.stderr = data
if not isinstance(data, list):
with pytest.raises(TypeError):
t.pre_exec = data
with pytest.raises(TypeError):
t.executable = data
with pytest.raises(TypeError):
t.arguments = data
with pytest.raises(TypeError):
t.post_exec = data
with pytest.raises(TypeError):
t.upload_input_data = data
with pytest.raises(TypeError):
t.copy_input_data = data
with pytest.raises(TypeError):
t.link_input_data = data
with pytest.raises(TypeError):
t.move_input_data = data
with pytest.raises(TypeError):
t.copy_output_data = data
with pytest.raises(TypeError):
t.download_output_data = data
with pytest.raises(TypeError):
t.move_output_data = data
if not isinstance(data, str) and not isinstance(data, unicode):
with pytest.raises(ValueError):
t.cpu_reqs = {
'processes': 1,
'process_type': data,
'threads_per_process': 1,
'thread_type': None
}
t.cpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': 1,
'thread_type': data
}
t.gpu_reqs = {
'processes': 1,
'process_type': data,
'threads_per_process': 1,
'thread_type': None
}
t.gpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': 1,
'thread_type': data
}
if not isinstance(data, int):
with pytest.raises(TypeError):
t.cpu_reqs = {
'processes': data,
'process_type': None,
'threads_per_process': 1,
'thread_type': None
}
t.cpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': data,
'thread_type': None
}
t.gpu_reqs = {
'processes': data,
'process_type': None,
'threads_per_process': 1,
'thread_type': None
}
t.gpu_reqs = {
'processes': 1,
'process_type': None,
'threads_per_process': data,
'thread_type': None
}
def GeneralCycle(self, Replicas, Replica_Cores, Cycle, MD_Executable,
ExchangeMethod):
"""
All cycles after the initial cycle
Pulls up exchange pairs file and generates the new workflow
"""
self._prof.prof('InitcreateMDwokflow_{0}'.format(Cycle), uid=self._uid)
with open('exchangePairs_{0}.dat'.format(Cycle),
'r') as f: # Read exchangePairs.dat
ExchangeArray = []
for line in f:
ExchangeArray.append(int(line.split()[1]))
#ExchangeArray.append(line)
#print ExchangeArray
q = Pipeline()
q.name = 'genpipeline{0}'.format(Cycle)
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
md_dict = dict()
#Create initial MD stage
md_stg = Stage()
md_stg.name = 'mdstage{0}'.format(Cycle)
self._prof.prof('InitMD_{0}'.format(Cycle), uid=self._uid)
for r in range(Replicas):
md_tsk = AMBERTask(cores=Replica_Cores,
MD_Executable=MD_Executable)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r,
cycle=Cycle)
md_tsk.link_input_data = [
'%s/restrt > inpcrd' %
(self.Book[Cycle - 1][ExchangeArray[r]]),
'%s/prmtop' % (self.Book[0][r]),
#'%s/prmtop'%(self.Tarball_path[0]),
'%s/mdin_{0}'.format(r) % (self.Book[0][r])
]
#'%s/mdin'%(self.Book[0][r])]
#'%s/mdin'%(self.Tarball_path[0])]
md_tsk.arguments = [
'-O', '-i', 'mdin_{0}'.format(r), '-p', 'prmtop', '-c',
'inpcrd', '-o', 'out_{0}'.format(r), '-inf',
'mdinfo_{0}'.format(r)
]
#md_tsk.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(r),'-inf', 'mdinfo_{0}'.format(r)]
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s' % (
q.name, md_stg.name, md_tsk.name)
self.md_task_list.append(md_tsk)
md_stg.add_tasks(md_tsk)
q.add_stages(md_stg)
ex_stg = Stage()
ex_stg.name = 'exstg{0}'.format(Cycle + 1)
#Create Exchange Task
ex_tsk = Task()
ex_tsk.name = 'extsk{0}'.format(Cycle + 1)
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = [ExchangeMethod]
for r in range(Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (md_dict[r], r)]
ex_tsk.arguments = [
'TempEx.py', '{0}'.format(Replicas), '{0}'.format(Cycle + 1)
]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = [
'exchangePairs_{0}.dat'.format(Cycle + 1)
] # Finds exchange partners, also Generates exchange history trace
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
self.ex_task_list.append(ex_tsk)
q.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
self.Book.append(md_dict)
#self._prof.prof('EndEx_{0}'.format(Cycle), uid=self._uid)
#print d
#print self.Book
return q
# Bookkeeping
stage_uids = list()
task_uids = dict()
Stages = 3
Replicas = 4
for N_Stg in range(Stages):
stg = Stage() ## initialization
task_uids['Stage_%s' % N_Stg] = list()
if N_Stg == 0:
for n0 in range(Replicas):
t = Task()
t.executable = [
'/usr/local/packages/gromacs/5.1.4/INTEL-140-MVAPICH2-2.0/bin/gmx_mpi_d'
] #MD Engine
t.upload_input_data = [
'in.gro', 'in.top', 'FNF.itp', 'martini_v2.2.itp', 'in.mdp'
]
t.pre_exec = [
'module load gromacs',
'/usr/local/packages/gromacs/5.1.4/INTEL-140-MVAPICH2-2.0/bin/gmx_mpi_d grompp -f in.mdp -c in.gro -o in.tpr -p in.top'
]
t.arguments = ['mdrun', '-s', 'in.tpr', '-deffnm', 'out']
t.cores = 32
stg.add_tasks(t)
task_uids['Stage_%s' % N_Stg].append(t.uid)
p.add_stages(stg)
stage_uids.append(stg.uid)
else:
for n0 in range(Replicas):
def general_cycle(self, replicas, replica_cores, cycle, python_path,
md_executable, exchange_method, pre_exec):
"""
All cycles after the initial cycle
Pulls up exchange pairs file and generates the new workflow
"""
self._prof.prof('InitcreateMDwokflow_{0}'.format(cycle), uid=self._uid)
with open('exchangePairs_{0}.dat'.format(cycle),
'r') as f: # Read exchangePairs.dat
exchange_array = []
for line in f:
exchange_array.append(int(line.split()[1]))
#exchange_array.append(line)
#print exchange_array
q = Pipeline()
q.name = 'genpipeline{0}'.format(cycle)
#bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
md_dict = dict()
#Create MD stage
md_stg = Stage()
md_stg.name = 'mdstage{0}'.format(cycle)
self._prof.prof('InitMD_{0}'.format(cycle), uid=self._uid)
for r in range(replicas):
md_tsk = AMBERTask(cores=replica_cores,
md_executable=md_executable,
pre_exec=pre_exec)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r,
cycle=cycle)
md_tsk.link_input_data = [
'%s/restrt > inpcrd' %
(self.book[cycle - 1][exchange_array[r]]),
'%s/prmtop' % (self.book[0][r]),
'%s/mdin_{0}'.format(r) % (self.book[0][r])
]
### The Following softlinking scheme is to be used ONLY if node local file system is to be used: not fully supported yet.
#md_tsk.link_input_data = ['$NODE_LFS_PATH/rstrt-{replica}-{cycle}'.format(replica=exchange_array[r],cycle=cycle-1) > '$NODE_LFS_PATH/inpcrd',
# #'%s/restrt > inpcrd'%(self.book[cycle-1][exchange_array[r]]),
# '%s/prmtop'%(self.book[0][r]),
# '%s/mdin_{0}'.format(r)%(self.Book[0][r])]
md_tsk.arguments = [
'-O',
'-i',
'mdin_{0}'.format(r),
'-p',
'prmtop',
'-c',
'inpcrd',
#'-c', 'rstrt-{replica}-{cycle}'.format(replica=r,cycle=cycle-1),
'-o',
'out-{replica}-{cycle}'.format(replica=r, cycle=cycle),
'-r',
'restrt',
#'-r', 'rstrt-{replica}-{cycle}'.format(replica=r,cycle=cycle),
'-x',
'mdcrd-{replica}-{cycle}'.format(replica=r, cycle=cycle),
'-inf',
'mdinfo_{0}'.format(r)
]
#md_tsk.tag = 'mdtsk-{replica}-{cycle}'.format(replica=r,cycle=0)
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s' % (
q.name, md_stg.name, md_tsk.name)
self.md_task_list.append(md_tsk)
md_stg.add_tasks(md_tsk)
q.add_stages(md_stg)
ex_stg = Stage()
ex_stg.name = 'exstg{0}'.format(cycle + 1)
#Create Exchange Task
ex_tsk = Task()
ex_tsk.name = 'extsk{0}'.format(cycle + 1)
ex_tsk.executable = [
python_path
] #['/usr/bin/python'] #['/opt/python/bin/python']
ex_tsk.upload_input_data = [exchange_method]
for r in range(replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (md_dict[r], r)]
ex_tsk.pre_exec = ['mv *.py exchange_method.py']
ex_tsk.arguments = [
'exchange_method.py', '{0}'.format(replicas),
'{0}'.format(cycle + 1)
]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = [
'exchangePairs_{0}.dat'.format(cycle + 1)
] # Finds exchange partners, also Generates exchange history trace
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
self.ex_task_list.append(ex_tsk)
q.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
self.book.append(md_dict)
#self._prof.prof('EndEx_{0}'.format(cycle), uid=self._uid)
#print d
#print self.book
return q
def generate_pipeline(cfg):
cfg_file = cfg['run_cfg_file'] # resource and workload config
run_file = cfg['run_file'] # runs for this campaign
# setup S1 workload
cfg = ru.Config(cfg=ru.read_json(cfg_file))
runs = check_runs(cfg_file, run_file)
if not runs:
print('S1: nothing to run, exiting.')
return
# for each run in the campaign:
# - create cfg with requested receptor and smiles
# - create a number of masters as EnTK tasks and add them to a pipeline
# - submit configured number of masters with that cfg
# setup EnTK pipeline
p = Pipeline()
p.name = 'S1.RAPTOR'
s = Stage()
# create cfg
subs = dict()
rurl = cfg.fs_url + cfg.workload.results
d = rs.filesystem.Directory(rurl)
ls = [str(u).split('/')[-1] for u in d.list()]
workload = cfg.workload
for receptor, smiles, n_workers, runtime in runs:
print('%30s %s' % (receptor, smiles))
name = '%s_-_%s' % (receptor, smiles)
tgt = '%s.%s.gz' % (name, workload.output)
cpw = cfg.cpw
gpw = cfg.gpw
n_masters = cfg.n_masters
cfg.workload.receptor = receptor
cfg.workload.smiles = smiles
cfg.workload.name = name
cfg.runtime = runtime
cfg.n_workers = n_workers
print('n_workers: %d' % cfg.n_workers)
ru.write_json(cfg, 'configs/wf0.%s.cfg' % name)
for i in range(n_masters):
t = Task()
t.pre_exec = [
'. /gpfs/alpine/scratch/mturilli1/med110/radical.pilot.sandbox/s1.to/bin/activate'
]
t.executable = "python3"
t.arguments = ['wf0_master.py', i]
t.cpu_reqs = {
'processes': 1,
'threads_per_process': 4,
'thread_type': None,
'process_type': None
}
t.upload_input_data = [
'wf0_master.py', 'wf0_worker.py',
'configs/wf0.%s.cfg > wf0.cfg' % name, 'read_ligand_dict.py'
]
t.link_input_data = ['%s > input_dir' % workload.input_dir]
#t.download_output_data = ['%s.%s.gz > results/%s.%s.gz' %
# (name, workload.output, name, workload.output)]
s.add_tasks(t)
p.add_stages(s)
return p
def test_task_to_dict():
"""
**Purpose**: Test if the 'to_dict' function of Task class converts all expected attributes of the Task into a
dictionary
"""
t = Task()
d = t.to_dict()
assert d == {
'uid': None,
'name': None,
'state': states.INITIAL,
'state_history': [states.INITIAL],
'pre_exec': [],
'executable': [],
'arguments': [],
'post_exec': [],
'cpu_reqs': {
'processes': 1,
'process_type': None,
'threads_per_process': 1,
'thread_type': None
},
'gpu_reqs': {
'processes': 0,
'process_type': None,
'threads_per_process': 0,
'thread_type': None
},
'lfs_per_process': 0,
'upload_input_data': [],
'copy_input_data': [],
'link_input_data': [],
'move_input_data': [],
'copy_output_data': [],
'move_output_data': [],
'download_output_data': [],
'stdout': None,
'stderr': None,
'exit_code': None,
'path': None,
'tag': None,
'parent_stage': {
'uid': None,
'name': None
},
'parent_pipeline': {
'uid': None,
'name': None
}
}
t = Task()
t.uid = 'test.0000'
t.name = 'new'
t.pre_exec = ['module load abc']
t.executable = ['sleep']
t.arguments = ['10']
t.cpu_reqs['processes'] = 10
t.cpu_reqs['threads_per_process'] = 2
t.gpu_reqs['processes'] = 5
t.gpu_reqs['threads_per_process'] = 3
t.lfs_per_process = 1024
t.upload_input_data = ['test1']
t.copy_input_data = ['test2']
t.link_input_data = ['test3']
t.move_input_data = ['test4']
t.copy_output_data = ['test5']
t.move_output_data = ['test6']
t.download_output_data = ['test7']
t.stdout = 'out'
t.stderr = 'err'
t.exit_code = 1
t.path = 'a/b/c'
t.tag = 'task.0010'
t.parent_stage = {'uid': 's1', 'name': 'stage1'}
t.parent_pipeline = {'uid': 'p1', 'name': 'pipeline1'}
d = t.to_dict()
assert d == {
'uid': 'test.0000',
'name': 'new',
'state': states.INITIAL,
'state_history': [states.INITIAL],
'pre_exec': ['module load abc'],
'executable': ['sleep'],
'arguments': ['10'],
'post_exec': [],
'cpu_reqs': {
'processes': 10,
'process_type': None,
'threads_per_process': 2,
'thread_type': None
},
'gpu_reqs': {
'processes': 5,
'process_type': None,
'threads_per_process': 3,
'thread_type': None
},
'lfs_per_process': 1024,
'upload_input_data': ['test1'],
'copy_input_data': ['test2'],
'link_input_data': ['test3'],
'move_input_data': ['test4'],
'copy_output_data': ['test5'],
'move_output_data': ['test6'],
'download_output_data': ['test7'],
'stdout': 'out',
'stderr': 'err',
'exit_code': 1,
'path': 'a/b/c',
'tag': 'task.0010',
'parent_stage': {
'uid': 's1',
'name': 'stage1'
},
'parent_pipeline': {
'uid': 'p1',
'name': 'pipeline1'
}
}
def init_cycle(
self, replicas, replica_cores, python_path, md_executable,
exchange_method, min_temp, max_temp, timesteps, basename, pre_exec
): # "cycle" = 1 MD stage plus the subsequent exchange computation
"""
Initial cycle consists of:
1) Create tarball of MD input data
2) Transfer the tarball to pilot sandbox
3) Untar the tarball
4) Run first cycle
"""
#Initialize Pipeline
self._prof.prof('InitTar', uid=self._uid)
p = Pipeline()
p.name = 'initpipeline'
md_dict = dict() #bookkeeping
tar_dict = dict() #bookkeeping
#Write the input files
self._prof.prof('InitWriteInputs', uid=self._uid)
writeInputs.writeInputs(max_temp=max_temp,
min_temp=min_temp,
replicas=replicas,
timesteps=timesteps,
basename=basename)
self._prof.prof('EndWriteInputs', uid=self._uid)
self._prof.prof('InitTar', uid=self._uid)
#Create Tarball of input data
tar = tarfile.open("input_files.tar", "w")
for name in [
basename + ".prmtop", basename + ".inpcrd", basename + ".mdin"
]:
tar.add(name)
for r in range(replicas):
tar.add('mdin_{0}'.format(r))
tar.close()
#delete all input files outside the tarball
for r in range(replicas):
os.remove('mdin_{0}'.format(r))
self._prof.prof('EndTar', uid=self._uid)
#Create Untar Stage
repo = git.Repo('.', search_parent_directories=True)
aux_function_path = repo.working_tree_dir
untar_stg = Stage()
untar_stg.name = 'untarStg'
#Untar Task
untar_tsk = Task()
untar_tsk.name = 'untartsk'
untar_tsk.executable = ['python']
untar_tsk.upload_input_data = [
str(aux_function_path) + '/repex/untar_input_files.py',
'input_files.tar'
]
untar_tsk.arguments = ['untar_input_files.py', 'input_files.tar']
untar_tsk.cpu_reqs = 1
#untar_tsk.post_exec = ['']
untar_stg.add_tasks(untar_tsk)
p.add_stages(untar_stg)
tar_dict[0] = '$Pipeline_%s_Stage_%s_Task_%s' % (
p.name, untar_stg.name, untar_tsk.name)
# First MD stage: needs to be defined separately since workflow is not built from a predetermined order, also equilibration needs to happen first.
md_stg = Stage()
md_stg.name = 'mdstg0'
self._prof.prof('InitMD_0', uid=self._uid)
# MD tasks
for r in range(replicas):
md_tsk = AMBERTask(cores=replica_cores,
md_executable=md_executable,
pre_exec=pre_exec)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r, cycle=0)
md_tsk.link_input_data += [
'%s/inpcrd' % tar_dict[0],
'%s/prmtop' % tar_dict[0],
'%s/mdin_{0}'.format(r) %
tar_dict[0] #Use for full temperature exchange
]
md_tsk.arguments = [
'-O',
'-p',
'prmtop',
'-i',
'mdin_{0}'.format(r),
'-c',
'inpcrd',
'-o',
'out-{replica}-{cycle}'.format(replica=r, cycle=0),
'-r',
'restrt'.format(replica=r, cycle=0),
#'-r', 'rstrt-{replica}-{cycle}'.format(replica=r,cycle=0),
'-x',
'mdcrd-{replica}-{cycle}'.format(replica=r, cycle=0),
#'-o', '$NODE_LFS_PATH/out-{replica}-{cycle}'.format(replica=r,cycle=0),
#'-r', '$NODE_LFS_PATH/rstrt-{replica}-{cycle}'.format(replica=r,cycle=0),
#'-x', '$NODE_LFS_PATH/mdcrd-{replica}-{cycle}'.format(replica=r,cycle=0),
'-inf',
'mdinfo_{0}'.format(r)
]
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s' % (
p.name, md_stg.name, md_tsk.name)
md_stg.add_tasks(md_tsk)
self.md_task_list.append(md_tsk)
#print md_tsk.uid
p.add_stages(md_stg)
#stage_uids.append(md_stg.uid)
# First Exchange Stage
ex_stg = Stage()
ex_stg.name = 'exstg0'
self._prof.prof('InitEx_0', uid=self._uid)
# Create Exchange Task
ex_tsk = Task()
ex_tsk.name = 'extsk0'
#ex_tsk.pre_exec = ['module load python/2.7.10']
ex_tsk.executable = [python_path]
ex_tsk.upload_input_data = [exchange_method]
for r in range(replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s' % (md_dict[r], r)]
ex_tsk.pre_exec = ['mv *.py exchange_method.py']
ex_tsk.arguments = ['exchange_method.py', '{0}'.format(replicas), '0']
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs_0.dat']
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
p.add_stages(ex_stg)
self.ex_task_list.append(ex_tsk)
#self.ex_task_uids.append(ex_tsk.uid)
self.book.append(md_dict)
return p
Replica_Cores = 1
Pilot_Cores = Replicas * Replica_Cores
for N_Stg in range(Stages):
stg = Stage() ## initialization
task_uids['Stage_%s'%N_Stg] = list()
#####Initial MD stage
if N_Stg == 0:
for n0 in range(Replicas):
t = Task()
t.executable = ['/u/sciteam/mushnoor/amber/amber14/bin/sander.MPI'] #MD Engine
t.upload_input_data = ['inpcrd', 'prmtop', 'mdin_{0}'.format(n0)]
t.pre_exec = ['export AMBERHOME=$HOME/amber/amber14/']
t.arguments = ['-O', '-i', 'mdin_{0}'.format(n0), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out']
t.cores = Replica_Cores
stg.add_tasks(t)
task_uids['Stage_%s'%N_Stg].append(t.uid)
p.add_stages(stg)
stage_uids.append(stg.uid)
#####Exchange Stages
elif N_Stg != 0 and N_Stg%2 = 1:
t = Task()
t.executable = ['python']
t.upload_input_data = ['exchangeMethods/RandEx.py']
def GeneralCycle(self, Replicas, Replica_Cores, Cycle, MD_Executable, ExchangeMethod):
"""
All cycles after the initial cycle
Pulls up exchange pairs file and generates the new workflow
"""
self._prof.prof('InitcreateMDwokflow_{0}'.format(Cycle), uid=self._uid)
with open('exchangePairs_{0}.dat'.format(Cycle),'r') as f: # Read exchangePairs.dat
ExchangeArray = []
for line in f:
ExchangeArray.append(int(line.split()[1]))
#ExchangeArray.append(line)
#print ExchangeArray
q = Pipeline()
q.name = 'genpipeline{0}'.format(Cycle)
#Bookkeeping
stage_uids = list()
task_uids = list() ## = dict()
md_dict = dict()
#Create initial MD stage
md_stg = Stage()
md_stg.name = 'mdstage{0}'.format(Cycle)
self._prof.prof('InitMD_{0}'.format(Cycle), uid=self._uid)
for r in range (Replicas):
md_tsk = AMBERTask(cores=Replica_Cores, MD_Executable=MD_Executable)
md_tsk.name = 'mdtsk-{replica}-{cycle}'.format(replica=r,cycle=Cycle)
md_tsk.link_input_data = ['%s/restrt > inpcrd'%(self.Book[Cycle-1][ExchangeArray[r]]),
'%s/prmtop'%(self.Book[0][r]),
#'%s/prmtop'%(self.Tarball_path[0]),
'%s/mdin_{0}'.format(r)%(self.Book[0][r])]
#'%s/mdin'%(self.Book[0][r])]
#'%s/mdin'%(self.Tarball_path[0])]
md_tsk.arguments = ['-O', '-i', 'mdin_{0}'.format(r), '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(r),'-inf', 'mdinfo_{0}'.format(r)]
#md_tsk.arguments = ['-O', '-i', 'mdin', '-p', 'prmtop', '-c', 'inpcrd', '-o', 'out_{0}'.format(r),'-inf', 'mdinfo_{0}'.format(r)]
md_dict[r] = '$Pipeline_%s_Stage_%s_Task_%s'%(q.name, md_stg.name, md_tsk.name)
self.md_task_list.append(md_tsk)
md_stg.add_tasks(md_tsk)
q.add_stages(md_stg)
ex_stg = Stage()
ex_stg.name = 'exstg{0}'.format(Cycle+1)
#Create Exchange Task
ex_tsk = Task()
ex_tsk.name = 'extsk{0}'.format(Cycle+1)
ex_tsk.executable = ['python']
ex_tsk.upload_input_data = [ExchangeMethod]
for r in range (Replicas):
ex_tsk.link_input_data += ['%s/mdinfo_%s'%(md_dict[r],r)]
ex_tsk.arguments = ['TempEx.py','{0}'.format(Replicas), '{0}'.format(Cycle+1)]
ex_tsk.cores = 1
ex_tsk.mpi = False
ex_tsk.download_output_data = ['exchangePairs_{0}.dat'.format(Cycle+1)] # Finds exchange partners, also Generates exchange history trace
ex_stg.add_tasks(ex_tsk)
#task_uids.append(ex_tsk.uid)
self.ex_task_list.append(ex_tsk)
q.add_stages(ex_stg)
#stage_uids.append(ex_stg.uid)
self.Book.append(md_dict)
#self._prof.prof('EndEx_{0}'.format(Cycle), uid=self._uid)
#print d
#print self.Book
return q
# Create a Pipeline object
p = Pipeline()
# Bookkeeping
stage_uids = list()
task_uids = dict()
Stages = 3
Replicas = 4
for N_Stg in range(Stages):
stg = Stage() ## initialization
task_uids['Stage_%s'%N_Stg] = list()
if N_Stg == 0:
for n0 in range(Replicas):
t = Task()
t.executable = ['/usr/local/packages/gromacs/5.1.4/INTEL-140-MVAPICH2-2.0/bin/gmx_mpi_d'] #MD Engine
t.upload_input_data = ['in.gro', 'in.top', 'FNF.itp', 'martini_v2.2.itp', 'in.mdp']
t.pre_exec = ['module load gromacs', '/usr/local/packages/gromacs/5.1.4/INTEL-140-MVAPICH2-2.0/bin/gmx_mpi_d grompp -f in.mdp -c in.gro -o in.tpr -p in.top']
t.arguments = ['mdrun', '-s', 'in.tpr', '-deffnm', 'out']
t.cores = 32
stg.add_tasks(t)
task_uids['Stage_%s'%N_Stg].append(t.uid)
p.add_stages(stg)
stage_uids.append(stg.uid)
else:
for n0 in range(Replicas):
t = Task()
t.executable = ['/usr/local/packages/gromacs/5.1.4/INTEL-140-MVAPICH2-2.0/bin/gmx_mpi_d'] #MD Engine
def generate_pipeline(name, stages): #generate the pipeline of prediction and blob detection
# Create a Pipeline object
p = Pipeline()
p.name = name
for s_cnt in range(stages):
if(s_cnt==0):
# Create a Stage object
s0 = Stage()
s0.name = 'Stage %s'%s_cnt
# Create Task 1, training
t1 = Task()
t1.name = 'Predictor'
t1.pre_exec = ['module load psc_path/1.1',
'module load slurm/default',
'module load intel/17.4',
'module load python3',
'module load cuda',
'mkdir -p classified_images/crabeater',
'mkdir -p classified_images/weddel',
'mkdir -p classified_images/pack-ice',
'mkdir -p classified_images/other',
'source /pylon5/mc3bggp/paraskev/pytorchCuda/bin/activate'
]
t1.executable = 'python3' # Assign executable to the task
# Assign arguments for the task executable
t1.arguments = ['pt_predict.py','-class_names','crabeater','weddel','pack-ice','other']
t1.link_input_data = ['/pylon5/mc3bggp/paraskev/seal_test/nn_model.pth.tar',
'/pylon5/mc3bggp/paraskev/nn_images',
'/pylon5/mc3bggp/paraskev/seal_test/test_images'
]
t1.upload_input_data = ['pt_predict.py','sealnet_nas_scalable.py']
t1.cpu_reqs = {'processes': 1,'threads_per_process': 1, 'thread_type': 'OpenMP'}
t1.gpu_reqs = {'processes': 1,'threads_per_process': 1, 'thread_type': 'OpenMP'}
s0.add_tasks(t1)
# Add Stage to the Pipeline
p.add_stages(s0)
else:
# Create a Stage object
s1 = Stage()
s1.name = 'Stage %s'%s_cnt
# Create Task 2,
t2 = Task()
t2.pre_exec = ['module load psc_path/1.1',
'module load slurm/default',
'module load intel/17.4',
'module load python3',
'module load cuda',
'module load opencv',
'source /pylon5/mc3bggp/paraskev/pytorchCuda/bin/activate',
'mkdir -p blob_detected'
]
t2.name = 'Blob_detector'
t2.executable = ['python3'] # Assign executable to the task
# Assign arguments for the task executable
t2.arguments = ['blob_detector.py']
t2.upload_input_data = ['blob_detector.py']
t2.link_input_data = ['$Pipeline_%s_Stage_%s_Task_%s/classified_images'%(p.uid, s0.uid, t1.uid)]
t2.download_output_data = ['blob_detected/'] #Download resuting images
t2.cpu_reqs = {'processes': 1,'threads_per_process': 1, 'thread_type': 'OpenMP'}
t2.gpu_reqs = {'processes': 1, 'threads_per_process': 1, 'thread_type': 'OpenMP'}
s1.add_tasks(t2)
# Add Stage to the Pipeline
p.add_stages(s1)
return p
