Daniel Basher 是Gradient 播客的主持人。他致力于深入探讨人工智能和机器学习领域的前沿话题,邀请来自学术界和工业界的专家分享他们的研究成果和实践经验。Daniel 以其独特的采访风格和深入的问题著称,帮助听众更好地理解复杂的技术概念和其实际应用。作为一名技术爱好者和优秀的沟通者,他在播客中创造了一个引人入胜的...
and can modestly improve performance. However, it changes certain behaviors. For example: 1. When the user tries to access a gradient and perform manual ops on it, a None attribute or a Tensor full of 0s will behave differently. 2. If the user ...
record_shapes=False) as prof: with record_function(" Non-Compilied Causal Attention"): for _ in range(25): model(x) print(prof.key_averages().table(sort_by="cuda_time_total"
本文详细介绍了基于扩散模型构建的文本到视频生成系统,展示了在MSRV-TT和Shutterstock视频标注数据集上训练的模型输出结果。以下是模型在不同提示词下的生成示例。 首先展示一些模型生成效果展示 提示词:"A person holding a camera"(训练10K步...
df = compare_traces_output.sort_values(by="diff_counts", ascending=False).head(10) TraceDiff.visualize_counts_diff(df) ../_images/counts_diff.png 类似地,可以计算出持续时间变化最大的前十个操作符如下: 代码语言:javascript 代码运行次数:0 运行 复制 df = compare_traces_output.sort_values(by...
数据加载 在PyTorch中，数据加载可通过自定义的数据集对象。数据集对象被抽象为Dataset类，实现自定义的...
Fully Sharded Data Parallel (FSDP) 实现了 Optimizer + Gradient + Horizontal Model Sharding。 2.3 Optimizer State Sharding (OSS) 因为OSS是ZeroRedundancyOptimizer的源头,所以我们先看看其思路。OSS实现了与优化器内存相关的优化。像Adam这样的优化器通常需要保持动量、方差。即便可以使用FP16精度的参数和梯度进行训...
Sharded Data Parallel (SDP) 负责 Optimizer + Gradient State Sharding。 Fully Sharded Data Parallel (FSDP) 实现了 Optimizer + Gradient + Horizontal Model Sharding。 2.3 Optimizer State Sharding (OSS) 因为OSS是ZeroRedundancyOptimizer的源头,所以我们先看看其思路。OSS实现了与优化器内存相关的优化。像Adam这...
PyTorch now supports autoloading for out-of-tree device extensions, streamlining integration by eliminating the need for manual imports. This feature, enabled through the torch.backends entrypoint, simplifies usage by ensuring seamless extension loading, while allowing users to disable it via an environme...
(i.e, it started overfitting). This is because as a neural network gets deeper, the gradients from the loss function start to shrink to zero and thus the weights are not updated. This problem is known as the vanishing gradient problem. ResNet essentially solved this problem by using skip ...