pytorch二分类loss

A python-based machine learning framework, providing tensors, dynamic neural networks and strong GPU acceleration.

Bitnami Secure Image for pytorch

The PyTorch on ROCm Docker images

Bitnami Helm chart for PyTorch

Build, ship and run secure software with Chainguard's low-to-zero CVE container images.

This docker repo is used for hosting pytorch-nightly-build docker images.

Containers for running PyTorch workloads on Intel® Architecture.

Unified PyTorch base container optimized for training with ROCm

PyTorch二分类时BCELoss，CrossEntropyLoss，Sigmoid等的选择和使用 这里就总结一下使用PyTorch做二分类时的几种情况： 总体上来讲，有三种实现形式： 最后分类层降至一维，使用sigmoid输出一个0-1之间的分数，使用torch.nn.BCELoss作为loss