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Update python - #1465
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olivi-eh
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Looks like most of the issues look like this: Might need to manually bump |
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This PR contains the following updates:
==v1.0.1→==1.15.0==2.6.1→==2.7.1==2.1.3→==2.4.1==0.44.1→==0.50.2==5.5.0→==5.5.2==2024.8.30→==2024.12.14==3.4.0→==3.5.2==8.1.7→==8.5.0==2.11.0→==2.14.0==0.8.0→==0.8.2==8.15.0→==8.19.3==2.14.1→==2.16.0==0.2.13→==0.7.3==0.114.0→==0.143.1==0.115.0→==0.143.1==0.115.13→==0.143.1==2024.5.0→==2024.11.0==2024.9.0→==2024.12.0==1.16.0→==1.39.1==2.22.0→==2.42.0~=2.28.1→~=2.42.0~=2.34.0→~=2.62.0==2.27.0→==2.62.0==0.2.1→==0.6.1==3.27.0→==3.30.1==3.29.0→==3.46.1==2.5.1→==2.8.0==2.23.0→==2.32.0==1.11.1→==1.19.0==1.18.0→==1.26.0~=2.23.0→~=2.42.0==2.18.2→==2.19.0==1.8.0→==1.9.0==2.8.2→==2.11.0==1.2.1→==1.39.1==3.29.0→==3.46.1==1.65.0→==1.75.5==0.13.1→==0.14.5==1.62.3→==1.84.0==1.62.3→==1.84.0==0.24.7→==0.36.2==1.5.3→==1.6.0==0.4.6→==0.5.6==0.0.2→==0.0.8==0.8.1→==0.14.0==2.4.4→==2.5.4==26.2→==26.3==2.2.2→==2.3.3==v0.13.2→==0.21.2==0.3.2→==0.5.1==0.4.1→==0.5.4==1.25.0→==1.29.0==6.1.0→==6.1.1==2.9.9→==2.9.13==0.4.1→==0.4.2==0.4.1→==0.4.2==2.22→==2.23==2.11.7→==2.14.1==1.24.10→==1.28.2==2026.1.post1→==2026.5==1.11.1→==1.19.1==5.0.8→==5.3.1==2.33.0→==2.34.2==2.33.1→==2.34.2==4.9→==4.9.1>=0.6,<=0.6.4→>=0.17,<=0.17.0==1.5.1→==1.9.1==1.17.1→==1.18.1==1.16.0→==1.17.0==1.54.0→==1.66.0==2.17.0→==2.21.0==0.0.3→==0.0.5==3.6.0→==3.7.0==v0.11.4→==0.29.1==4.15.0→==4.16.0==2026.2→==2026.5==0.30.6→==0.54.0==0.34.0→==0.54.0==4.7.1→==4.23.1==1.23.0→==1.25.1Warning
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Release Notes
huggingface/accelerate (accelerate)
v1.15.0: : FSDP2 activation memory, dtensor improvementsCompare Source
v1.15.0: FSDP2 activation memory, dtensor improvements
FSDP2
A large batch of FSDP2 work this release: two fixes that cut activation memory at long sequence lengths, tied-embedding support on torch >= 2.13, and a round of checkpointing correctness and scale fixes.
Activation checkpointing was wrapping each child of the matched layer (
self_attn,mlp, the norms) instead of the layer itself, so every inter-child activation stayed saved for backward. It now wraps the layer.There's also a new FSDP2-only
activation_checkpointing_offload, which moves the remaining per-layer checkpoint inputs to pinned CPU memory. Gradients are exactly those of plain activation checkpointing:activation_checkpointing_offload: offload checkpointed layer inputs to pinned CPU memory by @qgallouedec in #4175FULL_STATE_DICTdropping every rank's adapter shard except rank 0 by @AmineDiro in #4206DTensor
Two fixes for DTensor-sharded models, which you hit with FSDP2, tensor parallelism, or any N-D parallelism setup: gradient clipping no longer fails on the
foreachop when plain tensors and DTensors are mixed, andprepare_modelleaves an already-sharded model where it is:Offloading & Quantization
An entire model can now be dispatched to disk, including tied weights — useful for tools like
llm-compressorthat compress large models on machines that can't hold them:Trackers
Custom trackers can be registered by name and then selected from
log_with=like any built-in one:Device support
Neuron gains a torch dynamo backend (so
--torch-compileworks with the Transformers Trainer) and MPS is now reported and handled properly byaccelerate envandfind_executable_batch_size.neuronbackend for torch dynamo by @michaelbenayoun in #4097accelerate envby @xquantize in #4158CLI
estimate-memoryfor timm>=1.0.29 by adding thehf-hub:prefix by @iamsharduld in #4213Minor fixes
New Contributors
Full Changelog: huggingface/accelerate@v1.14.0...v1.15.0
v1.14.0: : AMD ROCm support, FSDP2 hardeningCompare Source
FSDP2 Improvements
This release brings a large batch of FSDP2 fixes and quality-of-life improvements: correct dtype handling on load, sharding of embeddings/norms, QLoRA crash prevention, and a more robust auto-wrap policy.
AMD ROCm support
Accelerate now works end-to-end on AMD ROCm devices. Thanks @Abdennacer-Badaoui!
Neuron
Further Neuron improvements to reduce recompilation and cover missing device cases.
Quantization & Offloading
We improved offloading support for quantized models, including Torchao, int8, and tied-weight handling.
Data Loading
Minor fixes
Full Changelog: huggingface/accelerate@v1.13.0...v1.14.0
v1.13.0: : Neuron support, IPEX removal, and distributed training fixesCompare Source
AWS Neuron support
We now have support for AWS Neuron (Trainium/Inferentia) devices. Thanks @michaelbenayoun for adding this.
XPU Improvements
We've removed IPEX dependency and improved device-agnostic code for XPU.
#3912
FSDP2 Improvements
We've added a bunch of important fixes for FSDP2 users: upcasting only grad-requiring params, better tied embedding errors, DCP optimizer loading, bf16 optimizer step crash fix, and torch < 2.7.0 compatibility.