我有一个在循环中实例化的对象，这会导致内存积累。
for l in range(10):
grido = RasterModelGrid((3000, 3000), 10)
# Tracking memory
snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('traceback')
# pick the biggest memory block
stat = top_stats[0]
print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
for line in stat.traceback.format():
print(line)
del grido
# Tracking memory
snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('traceback')
# pick the biggest memory block
stat = top_stats[0]
print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
for line in stat.traceback.format():
print(line)
，调试输出为:
2 memory blocks: 281156.3 KiB
File "/home/aargenti/eclipse-workspace/landlab/test_memory_leak.py", line 13
grido = RasterModelGrid((3000, 3000), 10)
File "/home/aargenti/eclipse-workspace/landlab/landlab/grid/raster.py", line 238
DualUniformRectilinearGraph.__init__(
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/dual_structured_quad.py", line 187
UniformRectilinearGraph.__init__(self, shape, spacing=spacing, origin=origin)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 654
StructuredQuadGraphExtras.__init__(self, node_y_and_x, sort=sort)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 518
links=StructuredQuadLayoutCython.nodes_at_link(self.shape),
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 88
nodes_at_link = np.empty((n_links, 2), dtype=int)
2 memory blocks: 281156.3 KiB
File "/home/aargenti/eclipse-workspace/landlab/test_memory_leak.py", line 13
grido = RasterModelGrid((3000, 3000), 10)
File "/home/aargenti/eclipse-workspace/landlab/landlab/grid/raster.py", line 238
DualUniformRectilinearGraph.__init__(
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/dual_structured_quad.py", line 187
UniformRectilinearGraph.__init__(self, shape, spacing=spacing, origin=origin)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 654
StructuredQuadGraphExtras.__init__(self, node_y_and_x, sort=sort)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 518
links=StructuredQuadLayoutCython.nodes_at_link(self.shape),
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 88
nodes_at_link = np.empty((n_links, 2), dtype=int)
4 memory blocks: 562312.7 KiB
File "/home/aargenti/eclipse-workspace/landlab/test_memory_leak.py", line 13
grido = RasterModelGrid((3000, 3000), 10)
File "/home/aargenti/eclipse-workspace/landlab/landlab/grid/raster.py", line 238
DualUniformRectilinearGraph.__init__(
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/dual_structured_quad.py", line 187
UniformRectilinearGraph.__init__(self, shape, spacing=spacing, origin=origin)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 654
StructuredQuadGraphExtras.__init__(self, node_y_and_x, sort=sort)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 518
links=StructuredQuadLayoutCython.nodes_at_link(self.shape),
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 88
nodes_at_link = np.empty((n_links, 2), dtype=int)
4 memory blocks: 562312.7 KiB
File "/home/aargenti/eclipse-workspace/landlab/test_memory_leak.py", line 13
grido = RasterModelGrid((3000, 3000), 10)
File "/home/aargenti/eclipse-workspace/landlab/landlab/grid/raster.py", line 238
DualUniformRectilinearGraph.__init__(
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/dual_structured_quad.py", line 187
UniformRectilinearGraph.__init__(self, shape, spacing=spacing, origin=origin)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 654
StructuredQuadGraphExtras.__init__(self, node_y_and_x, sort=sort)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 518
links=StructuredQuadLayoutCython.nodes_at_link(self.shape),
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 88
nodes_at_link = np.empty((n_links, 2), dtype=int)
但是当我直接用
实例化父类时grido = DualUniformRectilinearGraph((3000, 3000), 10)
代替:
grido = RasterModelGrid((3000, 3000), 10)
我没有这个内存问题:
2 memory blocks: 281156.3 KiB
File "/home/aargenti/eclipse-workspace/landlab/test_memory_leak.py", line 16
grido = DualUniformRectilinearGraph((3000, 3000), 10)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/dual_structured_quad.py", line 187
UniformRectilinearGraph.__init__(self, shape, spacing=spacing, origin=origin)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 654
StructuredQuadGraphExtras.__init__(self, node_y_and_x, sort=sort)
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 518
links=StructuredQuadLayoutCython.nodes_at_link(self.shape),
File "/home/aargenti/eclipse-workspace/landlab/landlab/graph/structured_quad/structured_quad.py", line 88
nodes_at_link = np.empty((n_links, 2), dtype=int)
571 memory blocks: 74.2 KiB
File "/home/aargenti/eclipse-workspace/landlab/test_memory_leak.py", line 20
top_stats = snapshot.statistics('traceback')
File "/home/aargenti/anaconda3/envs/landlab/lib/python3.10/tracemalloc.py", line 533
grouped = self._group_by(key_type, cumulative)
File "/home/aargenti/anaconda3/envs/landlab/lib/python3.10/tracemalloc.py", line 498
traceback = Traceback(frames)
File "/home/aargenti/anaconda3/envs/landlab/lib/python3.10/tracemalloc.py", line 193
self._frames = tuple(reversed(frames))
初始化用下面的代码进行:
class RasterModelGrid(
DiagonalsMixIn, DualUniformRectilinearGraph, ModelGrid, RasterModelGridPlotter
):
def __init__(
self,
shape,
xy_spacing=1.0,
xy_of_lower_left=(0.0, 0.0),
xy_of_reference=(0.0, 0.0),
xy_axis_name=("x", "y"),
xy_axis_units="-",
bc=None,
):
shape = tuple(shape)
xy_spacing = np.asfarray(np.broadcast_to(xy_spacing, 2))
self._xy_of_lower_left = tuple(np.asfarray(xy_of_lower_left))
if shape[0] <= 0 or shape[1] <= 0:
raise ValueError("number of rows and columns must be positive")
DualUniformRectilinearGraph.__init__(
self, shape, spacing=xy_spacing[::-1], origin=self.xy_of_lower_left[::-1]
)
ModelGrid.__init__(
self,
xy_axis_name=xy_axis_name,
xy_axis_units=xy_axis_units,
xy_of_reference=xy_of_reference,
)
self._node_status = np.full(
self.number_of_nodes, NodeStatus.CORE, dtype=np.uint8
)
self._node_status[self.perimeter_nodes] = NodeStatus.FIXED_VALUE
if bc is None:
bc = {"right": "open", "top": "open", "left": "open", "bottom": "open"}
if "closed" in bc.values():
self.set_closed_boundaries_at_grid_edges(*grid_edge_is_closed_from_dict(bc))
self.looped_node_properties = {}
# List of looped neighbor cells (all 8 neighbors) for
# given *cell ids* can be created if requested by the user.
self._looped_cell_neighbor_list = None
# List of second ring looped neighbor cells (all 16 neighbors) for
# given *cell ids* can be created if requested by the user.
self._looped_second_ring_cell_neighbor_list_created = False
为什么在实例化子对象时存在这种内存积累?我知道这不是一个最小的工作代码，但这不是我的代码，我不熟悉它。如果您不知道哪里出了问题，您会建议我测试什么来查看问题的来源?
考虑到你在Ubuntu上运行，我建议使用chap。
在您的特定情况下，假设您看到内存积累，但不一定是崩溃，您应该为您的进程收集一个活动核心，如下所示:
echo 0x37 > /proc/pid-of-your-process/coredump_filter
gcore pid-of-your-process
chap core-file-just-created
当您到达chap提示符时，尝试:
describe used %ContainerPythonObject /redirectSuffix containers
将创建一个名为core-file-name.containers的文件。您可以在该文件中搜索RasterModelGrid你可能会发现其中的很多，而且很可能每一个都涉及到某种循环。给定python分配的地址，您可以通过在chap提示符中执行以下操作来理解它是如何锚定的:
describe allocation address-you-just-found
/extend %ContainerPythonObject<-
/extend %PyDictKeysObject<-
/extend %PyDictValuesArray<-
/extend %PythonListItems<-
/skipUnfavoredReferences true
/commentExtensions true
/redirectSuffix RasterModelGridExplanation
如果您仔细查看结果文件，这应该允许您理解为什么特定的RasterModelGridExplanation
仍然在内存中，或者仍然可访问，或者只是在一个循环中，还没有被垃圾收集。