pytorch type_error ai_generated true

RuntimeError: Expected dtype float16 for half precision but got float32

ID: pytorch/amp-gradscaler-dtype

Also available as: JSON · Markdown · 中文
78%Fix Rate
82%Confidence
1Evidence
2023-07-10First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
torch>=2.0.0 active — — —
CUDA>=11.8 active — — —

Root Cause

A tensor with incorrect dtype (float32 instead of float16) was passed to an operation that expects half-precision input, such as within torch.cuda.amp.autocast with GradScaler.

generic

中文

将类型不正确的张量（float32 而非 float16）传递给了期望半精度输入的操作，例如在 torch.cuda.amp.autocast 和 GradScaler 中使用时。

Official Documentation

https://pytorch.org/docs/stable/amp.html

Workarounds

  1. 85% success Explicitly cast inputs to half precision before the operation, or ensure the model uses half precision layers correctly with GradScaler. 
    Explicitly cast inputs to half precision before the operation, or ensure the model uses half precision layers correctly with GradScaler.
  2. 75% success Check for custom operations that do not support autocast and manually cast inputs to float16. 
    Check for custom operations that do not support autocast and manually cast inputs to float16.

中文步骤

  1. Explicitly cast inputs to half precision before the operation, or ensure the model uses half precision layers correctly with GradScaler.
  2. Check for custom operations that do not support autocast and manually cast inputs to float16.

Dead Ends

Common approaches that don't work:

  1. 60% fail

    Disabling autocast entirely removes the error but defeats the purpose of mixed precision training.

  2. 70% fail

    Manually converting all tensors to float16 can cause numerical instability and does not fix the root cause of incorrect dtype propagation.