Pytorch Pytork推断导致cpu内存泄漏

我使用pytorch模型推断，我得到了内存泄漏问题，我的代码如下：

import torch
import torch.nn as nn
from memory_profiler import profile


@profile(func=None, stream=open('./mem.log', 'w'))
def run(net, x):
    with x:
        net(x)


class ConvVerify(nn.Module):

    def init(self):
        for name, m in self.named_modules():
            # print(name, m)
            if isinstance(m, nn.Conv2d):
                nn.init.kaiming_normal_(m.weight, mode='fan_out')
                if m.bias is not None:
                    nn.init.constant_(m.bias, 0)
            elif isinstance(m, nn.BatchNorm2d):
                nn.init.constant_(m.running_mean, 0)
                nn.init.constant_(m.running_var, 1)
                if m.weight is not None:
                    nn.init.constant_(m.weight, 1)
                if m.bias is not None:
                    nn.init.constant_(m.bias, 0)

    def __init__(self):
        super(ConvVerify, self).__init__()

        stride = 1
        self.model = nn.Sequential(
            nn.Conv2d(288, 64, (2, 2), stride),
            nn.BatchNorm2d(64),
            nn.ReLU(),
        )
        self.init()

    def forward(self, x):
        return self.model(x)


def begin():
    conv_verify_inst = ConvVerify()
    x = torch.autograd.Variable(torch.rand(1, 288, 7, 7))
    for i in range(3000):
        run(conv_verify_inst, x)


if __name__ == "__main__":
    begin()

---

当运行某个迭代器时，内存将增加0.1M或0.2M。例如，基本内存是71.8mib，最后，内存增加到72mib

我投票结束这个问题，因为它应该是pytorch的GitHub上的错误报告，提供的代码在执行时会产生错误；你能检查一下你是否错过了什么吗。？

run

函数中带有x的

行似乎导致了错误，我也将在PyHub上报告此问题@Shai@Alka，您是对的，代码有错误。应该用x:net（x）

而不是“net（x）”退出