torch.cuda.manual_seed_all(seed)

This function sets the seed for all available GPUs in the system. The seed is used to initialize the random number generator for CUDA computations.

All random number generators in PyTorch are deterministic by default, so setting the seed ensures that the same sequence of random numbers is generated every time the code is run. This is useful for reproducibility and debugging purposes.

The input parameter `seed` is an integer value that is used to initialize the random number generator. It can be any integer value, but it is recommended to use a fixed value for reproducibility purposes.

相关问题

seed = 1234 np.random.seed(seed) torch.manual_seed(seed) torch.cuda.manual_seed(seed) torch.cuda.manual_seed_all(seed)

These lines of code set the random seed for three different libraries: numpy, PyTorch (CPU), and PyTorch (GPU). Setting the random seed ensures that the sequence of random numbers generated by these libraries is reproducible. This is useful when running experiments or training models, as it ensures that the results can be replicated.

The specific value used for the seed (1234 in this case) is arbitrary and could be any integer.

用中文回答seed = 1234 np.random.seed(seed) torch.manual_seed(seed) torch.cuda.manual_seed(seed) torch.cuda.manual_seed_all(seed)

这段代码是设置随机数种子，可以保证每次运行代码生成的随机数都是相同的。其中，seed = 1234 是设置随机数种子的值；np.random.seed(seed) 是设置numpy库的随机数种子；torch.manual_seed(seed) 是设置pytorch的CPU随机数种子；torch.cuda.manual_seed(seed) 是设置pytorch的单个GPU随机数种子；torch.cuda.manual_seed_all(seed) 是设置pytorch的所有GPU随机数种子。