/sh3/ysuanbase/home/yeesuan9996/wangbei/software_lammps/lammps-install/src/Obj_mpi/../fft3d.cpp:113: undefined reference to `fftwf_execute_dft'

这个错误是在编译LAMMPS时出现的，指的是在链接时没有找到FFTW库。您需要确保已经正确安装了FFTW库，并且在编译LAMMPS时使用了正确的库路径和选项。

如果您已经安装了FFTW库，但是仍然出现这个错误，可能是因为LAMMPS编译时没有正确链接该库。您可以尝试在编译LAMMPS时手动添加FFTW库的路径和选项。例如，在Makefile文件中添加以下内容：

# Path to FFTW library
FFTW_PATH = /path/to/fftw

# FFTW library and include paths and options
LIB = -L$(FFTW_PATH)/lib -lfftw3f
INC = -I$(FFTW_PATH)/include

然后，在编译LAMMPS时，使用以下命令：

make yes-USER-FFT
make mpi

这应该会解决链接FFTW库的问题。

相关问题

如何解决Loading and preparing results... DONE (t=0.01s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* DONE (t=0.44s). Accumulating evaluation results... Traceback (most recent call last): File "tools/train.py", line 133, in <module> main() File "tools/train.py", line 129, in main runner.train() File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1721, in train model = self.train_loop.run() # type: ignore File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/mmengine/runner/loops.py", line 102, in run self.runner.val_loop.run() File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/mmengine/runner/loops.py", line 366, in run metrics = self.evaluator.evaluate(len(self.dataloader.dataset)) File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/mmengine/evaluator/evaluator.py", line 79, in evaluate _results = metric.evaluate(size) File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/mmengine/evaluator/metric.py", line 133, in evaluate _metrics = self.compute_metrics(results) # type: ignore File "/home/wangbei/mmdetection(coco)/mmdet/evaluation/metrics/coco_metric.py", line 512, in compute_metrics coco_eval.accumulate() File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/pycocotools-2.0-py3.8-linux-x86_64.egg/pycocotools/cocoeval.py", line 378, in accumulate tp_sum = np.cumsum(tps, axis=1).astype(dtype=np.float) File "/home/wangbei/anaconda3/envs/Object_mmdetection/lib/python3.8/site-packages/numpy/__init__.py", line 305, in __getattr__ raise AttributeError(__former_attrs__[attr]) AttributeError: module 'numpy' has no attribute 'float'. `np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 29887 closing signal SIGTERM ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 29886) of binary: /home/wangbei/anaconda3/envs/Object_mmdetection/bin/python

这个错误看起来像是在使用numpy时出现了问题。根据错误信息，似乎是在`pycocotools/cocoeval.py`文件中的`np.float`出现了问题。这是因为在NumPy 1.20中，`np.float`被弃用了。为了解决这个问题，你需要将代码中的`np.float`替换为`float`或`np.float64`。

你可以在`pycocotools/cocoeval.py`文件中找到`tp_sum = np.cumsum(tps, axis=1).astype(dtype=np.float)`这一行代码，将其中的`np.float`替换为`float`或`np.float64`。如果你不确定应该使用哪个，请根据NumPy版本查看官方文档或参考错误信息中提供的链接。

在修改代码后，重新运行程序，应该就可以解决这个问题了。

torch.distributed.elastic.multiprocessing.errors.ChildFailedError: /home/wangbei/yolov5-7.0/train.py FAILED

这个错误是由于 torch.distributed.elastic.multiprocessing 模块中的一个子进程失败导致的。可能有多种原因导致子进程失败，例如内存不足、文件读写错误、网络连接问题等等。你需要根据具体的错误信息来确定原因，并尝试解决问题。可以检查日志文件或者在发生错误时打印出错误信息来帮助你定位问题。