return forward_call(*input, **kwargs) File "/home/sdy/hw/pop2/CNN/CNNmodel.py", line 33, in forward x = self.conv2(x) File "/home/sdy/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/home/sdy/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/container.py", line 141, in forward input = module(input) File "/home/sdy/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/home/sdy/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 446, in forward return self._conv_forward(input, self.weight, self.bias) File "/home/sdy/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 443, in _conv_forward self.padding, self.dilation, self.groups) RuntimeError: [enforce fail at CPUAllocator.cpp:68] . DefaultCPUAllocator: can't allocate memory: you tried to allocate 21469593600 bytes. Error code 12 (Cannot allocate memory)
时间: 2023-08-11 09:08:53 浏览: 330
这个错误是由于无法分配足够的内存导致的。你尝试分配的内存大小为 21469593600 字节,但系统无法满足这个请求。
解决这个问题的方法之一是减少模型或输入数据的大小,以减少内存需求。你可以尝试使用更小的模型或缩小输入数据的尺寸。
另外,你也可以检查系统上的可用内存情况。可能是因为系统内存不足,无法满足所需的内存分配请求。在这种情况下,你可以尝试释放一些不必要的内存或重启系统来释放内存。
如果你正在使用 GPU,还可以尝试增加 GPU 的显存限制。可以使用 `torch.cuda.set_per_process_memory_fraction()` 函数来设置每个进程使用的 GPU 显存比例,以确保不会超出可用显存。
总之,你需要减少内存需求或增加可用内存来解决这个问题。
相关问题
Traceback (most recent call last): File "train.py", line 354, in <module> fit_one_epoch(model_train, model, yolo_loss, loss_history, optimizer, epoch, epoch_step, epoch_step_val, gen, gen_val, UnFreeze_Epoch, Cuda, save_period, save_dir) File "/hy-tmp/yolov5-pytorch-bilibili/yolov5-pytorch-bilibili/utils/utils_fit.py", line 34, in fit_one_epoch outputs = model_train(images) File "/usr/local/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/usr/local/miniconda3/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 169, in forward return self.module(*inputs[0], **kwargs[0]) File "/usr/local/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/hy-tmp/yolov5-pytorch-bilibili/yolov5-pytorch-bilibili/nets/yolo.py", line 102, in forward self.h3 = self.bottlenecklstm3(P3, self.h3, self.c3) # lstm File "/usr/local/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/hy-tmp/yolov5-pytorch-bilibili/yolov5-pytorch-bilibili/nets/bottleneck_lstm.py", line 141, in forward new_h, new_c = self.cell(inputs, h, c) File "/usr/local/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/hy-tmp/yolov5-pytorch-bilibili/yolov5-pytorch-bilibili/nets/bottleneck_lstm.py", line 68, in forward y = torch.cat((x, h),1) RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument tensors in method wrapper_cat)
这个错误通常是由于将位于不同设备(如GPU和CPU)上的张量传递给需要所有张量都在同一设备上的函数或方法,例如`torch.cat()`方法。要解决这个问题,需要将所有张量都移动到同一设备上,或者使用支持跨设备的函数(如`torch.nn.DataParallel()`)来处理它们。可以使用`tensor.to(device)`方法将张量移动到指定设备上,其中`device`可以是字符串(如`"cuda:0"`)或`torch.device()`对象。在这个特定的错误中,很可能是将GPU上的张量与CPU上的张量拼接在一起,因此需要将所有张量移动到同一设备上。可以使用`tensor.to(device)`方法将张量移动到指定设备上,其中`device`可以是字符串(如`"cuda:0"`)或`torch.device()`对象。
Traceback (most recent call last): File "/home/a/pycharmproject/clothes_try_on_copy/11/PF-AFN-main/PF-AFN_train/train_PBAFN_stage1.py", line 134, in <module> loss_vgg = criterionVGG(x_all[num], cur_person_clothes.cuda()) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/pycharmproject/clothes_try_on_copy/11/PF-AFN-main/PF-AFN_train/models/networks.py", line 164, in forward x_vgg, y_vgg = self.vgg(x), self.vgg(y) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/pycharmproject/clothes_try_on_copy/11/PF-AFN-main/PF-AFN_train/models/networks.py", line 150, in forward h_relu5 = self.slice5(h_relu4) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/container.py", line 119, in forward input = module(input) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/modules/pooling.py", line 162, in forward return F.max_pool2d(input, self.kernel_size, self.stride, File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/_jit_internal.py", line 365, in fn return if_false(*args, **kwargs) File "/home/a/.conda/envs/clothes_try_on_copy1/lib/python3.8/site-packages/torch/nn/functional.py", line 659, in _max_pool2d return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode) RuntimeError: Given input size: (512x2x1). Calculated output size: (512x1x0). Output size is too small 进程已结束,退出代码1
根据你提供的错误信息,这是一个运行时错误(RuntimeError)。错误信息中指出了问题出现的位置和错误类型。
根据错误信息可以看出,在执行 `forward` 方法时,发生了一个尺寸(size)计算错误。具体来说,输入的尺寸是 `(512x2x1)`,但计算得到的输出尺寸是 `(512x1x0)`。错误信息还指出输出尺寸过小(Output size is too small),导致计算无法进行。
这种错误通常与网络模型的结构和输入数据的尺寸不匹配有关。可能是在网络模型的某一层或操作中,尺寸计算出现了错误。可能的原因包括输入数据的维度不正确、网络模型定义中的错误或者数据预处理过程中的问题。
要解决这个问题,你可以检查以下几个方面:
1. 确保输入数据的维度和尺寸与模型定义相匹配。
2. 检查网络模型定义中各层或操作的输入输出尺寸是否正确。
3. 检查数据预处理过程中是否存在错误,例如可能需要进行维度变换或缩放操作。
如果你需要更详细的帮助,请提供相关的代码片段或更多上下文信息,我将尽力帮助你找到解决方案。
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