![Categorical(probs).sample() generates RuntimeError: invalid argument 2: invalid multinomial distribution (encountering probability entry < 0) - reinforcement-learning - PyTorch Forums Categorical(probs).sample() generates RuntimeError: invalid argument 2: invalid multinomial distribution (encountering probability entry < 0) - reinforcement-learning - PyTorch Forums](https://discuss.pytorch.org/uploads/default/original/2X/5/5e252e48252d691098dcff57c77f81956d528497.png)
Categorical(probs).sample() generates RuntimeError: invalid argument 2: invalid multinomial distribution (encountering probability entry < 0) - reinforcement-learning - PyTorch Forums
torch.distributions.Categorical``` unintended ```log_prob``` gradient w.r.t ```probs``` · Issue #61727 · pytorch/pytorch · GitHub
Training Larger and Faster Recommender Systems with PyTorch Sparse Embeddings | by Bo Liu | NVIDIA Merlin | Medium
![Python: Is torch.multinomial functionally equivalent to torch.distributions. categorical.Categorical? Python: Is torch.multinomial functionally equivalent to torch.distributions. categorical.Categorical?](https://i.stack.imgur.com/PJQ2x.png)
Python: Is torch.multinomial functionally equivalent to torch.distributions. categorical.Categorical?
![class 'torch.distributions.categorical.Categorical'>中属性probs和logits的计算方式_ categorical.probs[sampled_action]-CSDN博客 class 'torch.distributions.categorical.Categorical'>中属性probs和logits的计算方式_ categorical.probs[sampled_action]-CSDN博客](https://img-blog.csdnimg.cn/2002f4159e78444b819710d2fc088178.png)