torch.compile

In this paper I investigate the effect of random seed selection on the accuracy when using popular deep learning architectures for computer vision.

设置CPU生成随机数的种子，方便下次复现实验结果。 语法. torch.manual_seed(seed) → torch._C.Generator. 参数. seed (int) – CPU生成随机 ...

PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration; Deep neural networks built ... Pytorch · CONTRIBUTING.md · Release Notes · Issues

These are the basic building blocks for graphs: torch.nn Containers, Global Hooks, For Module, Convolution Layers, Pooling layers, Padding Layers, Non-linear ... Torch.nn.functional · Torch.nn.attention · Linear · Conv2d

Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable ... PyTorch 2.x · Previous PyTorch Versions · Welcome to PyTorch Tutorials · Ten

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PyTorch is an optimized tensor library for deep learning using GPUs and CPUs. Features described in this documentation are classified by release status. Torch · Torch.nn · torch.Tensor · Torch.cuda

torch.manual_seed. torch.manual_seed(seed)[source][source]. Sets the seed for generating random numbers on all devices. Returns a torch.Generator object.

You are here because you want to use torch.compile to make your PyTorch model run faster. torch.compile is a complex and relatively new piece of software.