Python gc.get_objects方法代碼示例

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def count(typename, objects=None):
    """Count objects tracked by the garbage collector with a given class name.

    Example:

        >>> count('dict')
        42
        >>> count('MyClass', get_leaking_objects())
        3

    Note that the GC does not track simple objects like int or str.

    .. versionchanged:: 1.7
       New parameter: ``objects``.

    """
    if objects is None:
        objects = gc.get_objects()
    return sum(1 for o in objects if type(o).__name__ == typename) 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def get_leaking_objects(objects=None):
    """Return objects that do not have any referents.

    These could indicate reference-counting bugs in C code.  Or they could
    be legitimate.

    Note that the GC does not track simple objects like int or str.

    .. versionadded:: 1.7
    """
    if objects is None:
        gc.collect()
        objects = gc.get_objects()
    try:
        ids = set(id(i) for i in objects)
        for i in objects:
            ids.difference_update(id(j) for j in gc.get_referents(i))
        # this then is our set of objects without referrers
        return [i for i in objects if id(i) in ids]
    finally:
        objects = i = j = None # clear cyclic references to frame 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def by_type(typename, objects=None):
    """Return objects tracked by the garbage collector with a given class name.

    Example:

        >>> by_type('MyClass')
        [<mymodule.MyClass object at 0x...>]

    Note that the GC does not track simple objects like int or str.

    .. versionchanged:: 1.7
       New parameter: ``objects``.

    """
    if objects is None:
        objects = gc.get_objects()
    return [o for o in objects if type(o).__name__ == typename] 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def memory_used():
    result = {}
    for obj in gc.get_objects():
        try:
            if torch.is_tensor(obj):
                if type(obj) not in result:
                    result[type(obj)] = 0
                count = 1
                for elem in list(obj.data.size()):
                    count *= elem
                result[type(obj.data)] += count * obj.data.element_size()
            elif hasattr(obj, 'data') and torch.is_tensor(obj.data):
                if type(obj.data) not in result:
                    result[type(obj.data)] = 0
                count = 1
                for elem in list(obj.data.size()):
                    count *= elem
                result[type(obj.data)] += count * obj.data.element_size()
        except:
            print("could not track ...")

    return result 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def cleanup_gc(self):
        gc.collect()
        leaked = [obj for obj in gc.get_objects() + gc.garbage
                  if isinstance(obj,
                                (qubes.Qubes, qubes.vm.BaseVM,
                                 libvirt.virConnect, libvirt.virDomain))]

        if leaked:
            try:
                import objgraph
                objgraph.show_backrefs(leaked,
                                       max_depth=15, extra_info=extra_info,
                                       filename='/tmp/objgraph-{}.png'.format(
                                           self.id()))
            except ImportError:
                pass

        # do not keep leaked object references in locals()
        leaked = bool(leaked)
        assert not leaked 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def host_memory_usage_in_gb():
    gc.collect()
    gc.disable() # Avoids accessing gc'd objects during traversal.
    objects = gc.get_objects()
    tensors = [obj for obj in objects if torch.is_tensor(obj)] # Debug
    host_tensors = [t for t in tensors if not t.is_cuda]
    total_mem_mb = 0
    visited_data = []

    for tensor in host_tensors:
        if tensor.is_sparse:
            continue
        # a data_ptr indicates a memory block allocated
        data_ptr = tensor.storage().data_ptr()
        if data_ptr in visited_data:
            continue
        visited_data.append(data_ptr)

        numel = tensor.storage().size()
        element_size = tensor.storage().element_size()
        mem_mb = numel*element_size /1024/1024 # 32bit=4Byte, MByte
        total_mem_mb += mem_mb

    gc.enable()
    return total_mem_mb / 1024 # in 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def test_teardown_issue1649(testdir):
    """
    Are TestCase objects cleaned up? Often unittest TestCase objects set
    attributes that are large and expensive during setUp.

    The TestCase will not be cleaned up if the test fails, because it
    would then exist in the stackframe.
    """
    testpath = testdir.makepyfile(
        """
        import unittest
        class TestCaseObjectsShouldBeCleanedUp(unittest.TestCase):
            def setUp(self):
                self.an_expensive_object = 1
            def test_demo(self):
                pass

    """
    )
    testdir.inline_run("-s", testpath)
    gc.collect()
    for obj in gc.get_objects():
        assert type(obj).__name__ != "TestCaseObjectsShouldBeCleanedUp" 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def disconnectAllHdfDBs():
    """
    Forcibly disconnect all instances of HdfDB objects

    Notes
    -----
    This is a hack to help ARMI exit gracefully when the garbage collector and h5py have
    issues destroying objects. After lots of investigation, the root cause for why this
    was having issues was never identified. It appears that when several HDF5 files are
    open in the same run (e.g.  when calling armi.init() multiple times from a
    post-processing script), when these h5py File objects were closed, the garbage
    collector would raise an exception related to the repr'ing the object. We
    get around this by using the garbage collector to manually disconnect all open HdfDB
    objects.
    """
    h5dbs = [db for db in gc.get_objects() if isinstance(db, Database3)]
    for db in h5dbs:
        db.close() 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def observation_containers(self):
        # Return the current set of 'observation containers'
        # as discussed in Notes Oct 27 2005.
        # returns a nodeset, not an idset, to avoid recursive referenes

        objs = self.gc.get_objects()
        cli = self.hv.cli_type()
        objs = (cli.select(objs, self.NodeSet, '<=') +
                cli.select(objs, ObservationList, '<=') +
                cli.select(
                    objs, self._parent.UniSet.IdentitySetSingleton, '<=')
                )
        r = self.immnodeset([x for x in objs if getattr(
            x, '_hiding_tag_', None) is self._hiding_tag_])
        del cli, objs
        return r 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def obj_referrers(klass):
    find_obj = False
    for obj in gc.get_objects():
        # closures are evil !
        if isinstance(obj, types.FunctionType) and obj.__closure__ is not None:
            for c in obj.__closure__:
                try:
                    if isinstance(c.cell_contents, klass):
                        print('!!!', obj, c.cell_contents)
                except ValueError:
                    print("Cell is empty...")
        if isinstance(obj, klass):
            find_obj = True
            rs = gc.get_referrers(obj)
            print("---------------------------referrers of %s" % klass.__name__)
            for ob in rs:
                print(type(ob), ob.__name__ if type(ob) is type else repr(ob)[:140])
                rs1 = gc.get_referrers(ob)
                for ob1 in rs1:
                    print('    ', type(ob1), ob1.__name__ if type(ob1) is type else repr(ob1)[:140])
            print("---------------------------")
    if not find_obj:
        print("Nothing refrences %s" % klass.__name__) 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def print_muppy_sumary():
    # http://pythonhosted.org/Pympler/index.html
    try:
        from pympler import muppy, summary
    except ImportError:
        print("WARNING: pympler not installed")
        return
    # from pympler.classtracker import ClassTracker
    # from pympler.classtracker_stats import HtmlStats
    global all_objects, obj_summary, class_tracker
    if all_objects is None:
        all_objects = muppy.get_objects()
        obj_summary = summary.summarize(all_objects)
        summary.print_(obj_summary)

        # class_tracker = ClassTracker()
        # class_tracker.track_class(FICSPlayer, trace=1)
        # class_tracker.track_class(ICGameModel, resolution_level=2, trace=1)
    else:
        obj_summary2 = summary.summarize(muppy.get_objects())
        diff = summary.get_diff(obj_summary, obj_summary2)
        summary.print_(diff, limit=200)

        # class_tracker.create_snapshot('usage')
        # HtmlStats(tracker=class_tracker).create_html('profile.html') 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def get_instances(cls):
    return [x for x in gc.get_objects() if isinstance(x, cls)] 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def count(typename):
    """Count objects tracked by the garbage collector with a given class name.

    Example:

        >>> count('dict')
        42
        >>> count('MyClass')
        3

    Note that the GC does not track simple objects like int or str.
    """
    return sum(1 for o in gc.get_objects() if type(o).__name__ == typename) 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def typestats():
    """Count the number of instances for each type tracked by the GC.

    Note that the GC does not track simple objects like int or str.

    Note that classes with the same name but defined in different modules
    will be lumped together.
    """
    stats = {}
    for o in gc.get_objects():
        stats.setdefault(type(o).__name__, 0)
        stats[type(o).__name__] += 1
    return stats 

# 需要導入模塊: import gc [as 別名]
# 或者: from gc import get_objects [as 別名]
def by_type(typename):
    """Return objects tracked by the garbage collector with a given class name.

    Example:

        >>> by_type('MyClass')
        [<mymodule.MyClass object at 0x...>]

    Note that the GC does not track simple objects like int or str.
    """
    return [o for o in gc.get_objects() if type(o).__name__ == typename]