tensorflow memory_error ai_generated true

ResourceExhaustedError: allocator ran out of memory

ID: tensorflow/resource-exhausted

Also available as: JSON · Markdown
78%Fix Rate
83%Confidence
3Evidence
2023-01-01First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2 active — — —

Root Cause

System or GPU memory fully consumed.

generic

Workarounds

  1. 90% success Reduce batch size and use mixed precision training 
    tf.keras.mixed_precision.set_global_policy("mixed_float16")
  2. 85% success Use tf.data with prefetch and cache for efficient data loading

Dead Ends

Common approaches that don't work:

  1. Kill other processes blindly 80% fail

    May kill critical services

  2. Swap to disk as overflow 72% fail

    Extremely slow training