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pytorch-fsdp2

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License: Apache-2.0

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SKILL.mdcore · 10,827 bytes
references/pytorch_dcp_async_recipe.mddoc · 808 bytes
references/pytorch_dcp_overview.mddoc · 1,022 bytes
references/pytorch_dcp_recipe.mddoc · 1,043 bytes
references/pytorch_ddp_notes.mddoc · 461 bytes
references/pytorch_device_mesh_tutorial.mddoc · 1,222 bytes
references/pytorch_examples_fsdp2.mddoc · 742 bytes
references/pytorch_fsdp1_api.mddoc · 396 bytes
references/pytorch_fsdp2_tutorial.mddoc · 2,495 bytes
references/pytorch_fully_shard_api.mddoc · 2,884 bytes
references/pytorch_tp_tutorial.mddoc · 994 bytes
references/ray_train_fsdp2_example.mddoc · 592 bytes
references/torchtitan_fsdp_notes.mddoc · 666 bytes

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<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT -->
---
name: pytorch-fsdp2
description: PyTorch FSDP2 fully sharded data parallelism. Use when training large models with per-parameter sharding and composable parallelism.
tags: [pytorch-fsdp2, distributed-training, scaling]
---

# Skill: Use PyTorch FSDP2 (`fully_shard`) correctly in a training script

This skill teaches a coding agent how to **add PyTorch FSDP2** to a training loop with correct initialization, sharding, mixed precision/offload configuration, and checkpointing.

> FSDP2 in PyTorch is exposed primarily via `torch.distributed.fsdp.fully_shard` and the `FSDPModule` methods it adds in-place to modules. See: `references/pytorch_fully_shard_api.md`, `references/pytorch_fsdp2_tutorial.md`.

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