# This code is part of Qiskit.
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"""
Routines for running Python functions in parallel using process pools
from the multiprocessing library.
"""
import os
from concurrent.futures import ProcessPoolExecutor
import sys
from qiskit.exceptions import QiskitError
from qiskit.utils.multiprocessing import local_hardware_info
from qiskit.tools.events.pubsub import Publisher
from qiskit import user_config
def get_platform_parallel_default():
"""
Returns the default parallelism flag value for the current platform.
Returns:
parallel_default: The default parallelism flag value for the
current platform.
"""
# Default False on Windows
if sys.platform == "win32":
parallel_default = False
# On macOS default false on Python >=3.8
elif sys.platform == "darwin":
parallel_default = False
# On linux (and other OSes) default to True
else:
parallel_default = True
return parallel_default
CONFIG = user_config.get_config()
if os.getenv("QISKIT_PARALLEL", None) is not None:
PARALLEL_DEFAULT = os.getenv("QISKIT_PARALLEL", None).lower() == "true"
else:
PARALLEL_DEFAULT = get_platform_parallel_default()
# Set parallel flag
if os.getenv("QISKIT_IN_PARALLEL") is None:
os.environ["QISKIT_IN_PARALLEL"] = "FALSE"
if os.getenv("QISKIT_NUM_PROCS") is not None:
CPU_COUNT = int(os.getenv("QISKIT_NUM_PROCS"))
else:
CPU_COUNT = CONFIG.get("num_process", local_hardware_info()["cpus"])
def _task_wrapper(param):
(task, value, task_args, task_kwargs) = param
return task(value, *task_args, **task_kwargs)
[documentos]def parallel_map( # pylint: disable=dangerous-default-value
task, values, task_args=(), task_kwargs={}, num_processes=CPU_COUNT
):
"""
Parallel execution of a mapping of `values` to the function `task`. This
is functionally equivalent to::
result = [task(value, *task_args, **task_kwargs) for value in values]
On Windows this function defaults to a serial implementation to avoid the
overhead from spawning processes in Windows.
Args:
task (func): Function that is to be called for each value in ``values``.
values (array_like): List or array of values for which the ``task``
function is to be evaluated.
task_args (list): Optional additional arguments to the ``task`` function.
task_kwargs (dict): Optional additional keyword argument to the ``task`` function.
num_processes (int): Number of processes to spawn.
Returns:
result: The result list contains the value of
``task(value, *task_args, **task_kwargs)`` for
each value in ``values``.
Raises:
QiskitError: If user interrupts via keyboard.
Events:
terra.parallel.start: The collection of parallel tasks are about to start.
terra.parallel.update: One of the parallel task has finished.
terra.parallel.finish: All the parallel tasks have finished.
Examples:
.. code-block:: python
import time
from qiskit.tools.parallel import parallel_map
def func(_):
time.sleep(0.1)
return 0
parallel_map(func, list(range(10)));
"""
if len(values) == 0:
return []
if len(values) == 1:
return [task(values[0], *task_args, **task_kwargs)]
Publisher().publish("terra.parallel.start", len(values))
nfinished = [0]
def _callback(_):
nfinished[0] += 1
Publisher().publish("terra.parallel.done", nfinished[0])
# Run in parallel if not Win and not in parallel already
if (
num_processes > 1
and os.getenv("QISKIT_IN_PARALLEL") == "FALSE"
and CONFIG.get("parallel_enabled", PARALLEL_DEFAULT)
):
os.environ["QISKIT_IN_PARALLEL"] = "TRUE"
try:
results = []
with ProcessPoolExecutor(max_workers=num_processes) as executor:
param = ((task, value, task_args, task_kwargs) for value in values)
future = executor.map(_task_wrapper, param)
results = list(future)
Publisher().publish("terra.parallel.done", len(results))
except (KeyboardInterrupt, Exception) as error:
if isinstance(error, KeyboardInterrupt):
Publisher().publish("terra.parallel.finish")
os.environ["QISKIT_IN_PARALLEL"] = "FALSE"
raise QiskitError("Keyboard interrupt in parallel_map.") from error
# Otherwise just reset parallel flag and error
os.environ["QISKIT_IN_PARALLEL"] = "FALSE"
raise error
Publisher().publish("terra.parallel.finish")
os.environ["QISKIT_IN_PARALLEL"] = "FALSE"
return results
# Cannot do parallel on Windows , if another parallel_map is running in parallel,
# or len(values) == 1.
results = []
for _, value in enumerate(values):
result = task(value, *task_args, **task_kwargs)
results.append(result)
_callback(0)
Publisher().publish("terra.parallel.finish")
return results