def _setup(options):
global _registered, _trace_memory, mem_usage
if not _registered:
from openmdao.devtools.memory import mem_usage
mem_changes = defaultdict(lambda: [0., 0, set()])
memstack = []
callstack = []
_trace_memory = _create_profile_callback(
callstack,
_collect_methods(_get_methods(options, default='openmdao_all')),
do_call=_trace_mem_call,
do_ret=_trace_mem_ret,
context=(memstack, mem_changes))
def print_totals():
print("Memory (MB) Calls File:Line:Function")
print("---------------------------------------")
for key, (delta, ncalls, parents) in sorted(mem_changes.items(),
key=lambda x: x[1]):
if delta != 0.0:
print("%10.4g %7d %s:%d:%s" %
(delta, ncalls, key[0], key[1], key[2]))
print("---------------------------------------")
print("Memory (MB) Calls File:Line:Function")
atexit.register(print_totals)
_registered = True
def _setup(options):
global _registered, _trace_memory, mem_usage
if not _registered:
from openmdao.devtools.debug import mem_usage
mem_changes = defaultdict(lambda: [0., 0, set()])
memstack = []
callstack = []
_trace_memory = _create_profile_callback(callstack,
_collect_methods(
_get_methods(options, default='openmdao_all')),
do_call=_trace_mem_call, do_ret=_trace_mem_ret,
context=(memstack, mem_changes))
def print_totals():
print("Memory (MB) Calls File:Line:Function")
print("---------------------------------------")
for key, (delta, ncalls, parents) in sorted(mem_changes.items(), key=lambda x: x[1]):
if delta != 0.0:
print("%10.4g %7d %s:%d:%s" % (delta, ncalls, key[0], key[1], key[2]))
print("---------------------------------------")
print("Memory (MB) Calls File:Line:Function")
atexit.register(print_totals)
_registered = True
def setup(methods=None, verbose=False):
"""
Setup call tracing.
Parameters
----------
methods : list of (glob, (classes...)) or None
Methods to be traced, based on glob patterns and isinstance checks.
verbose : bool
If True, show function locals and return values.
"""
global _registered, _trace_calls
if not _registered:
if methods is None:
methods = func_group['openmdao']
elif isinstance(methods, string_types):
methods = func_group.get(methods)
if methods is None:
methods = func_group['openmdao']
call_stack = []
qual_cache = {}
method_counts = defaultdict(int)
class_counts = defaultdict(set)
if verbose:
do_ret = _trace_return
else:
do_ret = None
_trace_calls = _create_profile_callback(
call_stack,
_collect_methods(methods),
do_call=_trace_call,
do_ret=do_ret,
context=(qual_cache, method_counts, class_counts, verbose))
def _setup(options):
if not func_group:
_setup_func_group()
global _registered, _trace_calls, _printer
verbose = options.verbose
memory = options.memory
leaks = options.leaks
if not _registered:
methods = _get_methods(options, default='openmdao')
call_stack = []
qual_cache = {}
method_counts = defaultdict(int)
class_counts = defaultdict(lambda: -1)
id2count = {}
if verbose or memory or leaks:
do_ret = _trace_return
else:
do_ret = None
if memory:
if psutil is None:
raise RuntimeError(
"Memory tracing requires the 'psutil' package. "
"Install it using 'pip install psutil'.")
memory = []
else:
memory = None
if leaks:
if objgraph is None:
raise RuntimeError(
"Leak detection requires the 'objgraph' package. "
"Install it using 'pip install objgraph'.")
leaks = []
else:
leaks = None
if options.outfile == 'stdout':
stream = sys.stdout
elif options.outfile == 'stderr':
stream = sys.stderr
else:
stream = open(options.outfile, 'w')
_printer = _get_printer(stream, options.rank)
_trace_calls = _create_profile_callback(
call_stack,
_collect_methods(methods),
do_call=_trace_call,
do_ret=do_ret,
context=(qual_cache, method_counts, class_counts, id2count,
verbose, memory, leaks, stream))
def setup(prefix='iprof', methods=None, prof_dir=None, finalize=True):
"""
Instruments certain important openmdao methods for profiling.
Parameters
----------
prefix : str ('iprof')
Prefix used for the raw profile data. Process rank will be appended
to it to get the actual filename. When not using MPI, rank=0.
methods : list, optional
A list of tuples of profiled methods to override the default set. The first
entry is the method name or glob pattern and the second is a tuple of class
objects used for isinstance checking. The default set of methods is:
::
[
"*": (System, Jacobian, Matrix, Solver, Driver, Problem),
]
prof_dir : str
Directory where the profile files will be written. Defaults to the
current directory.
finallize : bool
If True, register a function to finalize the profile before exit.
"""
global _profile_prefix, _matches
global _profile_setup, _profile_total, _profile_out
if _profile_setup:
raise RuntimeError("profiling is already set up.")
if prof_dir is None:
_profile_prefix = os.path.join(os.getcwd(), prefix)
else:
_profile_prefix = os.path.join(os.path.abspath(prof_dir), prefix)
_profile_setup = True
if methods is None:
methods = func_group['openmdao']
rank = MPI.COMM_WORLD.rank if MPI else 0
_profile_out = open("%s.%s" % (_profile_prefix, rank), 'wb')
if finalize:
atexit.register(_finalize_profile)
_matches = _collect_methods(methods)
def _setup(options, finalize=True):
global _profile_prefix, _matches
global _profile_setup, _profile_total, _profile_out
if _profile_setup:
raise RuntimeError("profiling is already set up.")
_profile_prefix = os.path.join(os.getcwd(), 'iprof')
_profile_setup = True
methods = _get_methods(options, default='openmdao')
rank = MPI.COMM_WORLD.rank if MPI else 0
_profile_out = open("%s.%s" % (_profile_prefix, rank), 'wb')
if finalize:
atexit.register(_finalize_profile)
_matches = _collect_methods(methods)
def _setup(options, finalize=True):
global _profile_prefix, _matches
global _profile_setup, _profile_total, _profile_out
if _profile_setup:
raise RuntimeError("profiling is already set up.")
_profile_prefix = os.path.join(os.getcwd(), 'iprof')
_profile_setup = True
methods = _get_methods(options, default='openmdao')
rank = MPI.COMM_WORLD.rank if MPI else 0
_profile_out = open("%s.%s" % (_profile_prefix, rank), 'wb')
if finalize:
atexit.register(_finalize_profile)
_matches = _collect_methods(methods)
def setup(methods=None):
"""
Setup memory profiling.
Parameters
----------
methods : list of (glob, (classes...)) or None
Methods to be profiled, based on glob patterns and isinstance checks.
"""
global _registered, _trace_memory, mem_usage
if not _registered:
from openmdao.devtools.debug import mem_usage
if methods is None:
methods = func_group['openmdao_all']
mem_changes = defaultdict(lambda: [0., 0, set()])
memstack = []
callstack = []
_trace_memory = _create_profile_callback(callstack,
_collect_methods(methods),
do_call=_trace_mem_call,
do_ret=_trace_mem_ret,
context=(memstack,
mem_changes))
def print_totals():
print("Memory (MB) Calls File:Line:Function")
print("---------------------------------------")
for key, (delta, ncalls, parents) in sorted(mem_changes.items(),
key=lambda x: x[1]):
if delta != 0.0:
print("%10.4g %7d %s:%d:%s" %
(delta, ncalls, key[0], key[1], key[2]))
print("---------------------------------------")
print("Memory (MB) Calls File:Line:Function")
atexit.register(print_totals)
_registered = True
def _setup(options):
if not func_group:
_setup_func_group()
global _registered, _trace_calls
verbose=options.verbose
if not _registered:
methods = _get_methods(options, default='openmdao')
call_stack = []
qual_cache = {}
method_counts = defaultdict(int)
class_counts = defaultdict(set)
if verbose:
do_ret = _trace_return
else:
do_ret = None
_trace_calls = _create_profile_callback(call_stack, _collect_methods(methods),
do_call=_trace_call,
do_ret=do_ret,
context=(qual_cache, method_counts,
class_counts, verbose))
