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# nemo_automodel.components.checkpoint

## Subpackages

* **[`nemo_automodel.components.checkpoint._backports`](/nemo-automodel/nemo_automodel/components/checkpoint/_backports)**

## Submodules

* **[`nemo_automodel.components.checkpoint._torch_backports`](/nemo-automodel/nemo_automodel/components/checkpoint/_torch_backports)**
* **[`nemo_automodel.components.checkpoint.addons`](/nemo-automodel/nemo_automodel/components/checkpoint/addons)**
* **[`nemo_automodel.components.checkpoint.checkpointing`](/nemo-automodel/nemo_automodel/components/checkpoint/checkpointing)**
* **[`nemo_automodel.components.checkpoint.config`](/nemo-automodel/nemo_automodel/components/checkpoint/config)**
* **[`nemo_automodel.components.checkpoint.conversion_mapping`](/nemo-automodel/nemo_automodel/components/checkpoint/conversion_mapping)**
* **[`nemo_automodel.components.checkpoint.lifecycle`](/nemo-automodel/nemo_automodel/components/checkpoint/lifecycle)**
* **[`nemo_automodel.components.checkpoint.state_dict_adapter`](/nemo-automodel/nemo_automodel/components/checkpoint/state_dict_adapter)**
* **[`nemo_automodel.components.checkpoint.stateful_wrappers`](/nemo-automodel/nemo_automodel/components/checkpoint/stateful_wrappers)**
* **[`nemo_automodel.components.checkpoint.utils`](/nemo-automodel/nemo_automodel/components/checkpoint/utils)**

## Package Contents

### Classes

| Name                                                                                      | Description                      |
| ----------------------------------------------------------------------------------------- | -------------------------------- |
| [`CheckpointingConfig`](#nemo_automodel-components-checkpoint-config-CheckpointingConfig) | Configuration for checkpointing. |

### API

```python
class nemo_automodel.components.checkpoint.config.CheckpointingConfig(
    enabled: bool = True,
    checkpoint_dir: str | pathlib.Path = 'checkpoints/',
    model_save_format: str = 'safetensors',
    model_cache_dir: str | pathlib.Path | None = None,
    model_repo_id: str | None = None,
    save_consolidated: bool | str | nemo_automodel.components.checkpoint.config.SaveConsolidatedMode = 'final',
    is_peft: bool = False,
    model_state_dict_keys: list[str] | None = None,
    is_async: bool = False,
    wait_for_staging: bool = False,
    cpu_offload: bool = False,
    load_metadata_with_gloo: bool = False,
    allow_legacy_pickle_restore: bool = False,
    dequantize_base_checkpoint: bool | None = None,
    original_model_root_dir: str | None = None,
    skip_task_head_prefixes_for_base_model: list[str] | None = None,
    single_rank_consolidation: bool = False,
    staging_dir: str | None = None,
    v4_compatible: bool = False,
    legacy_paramwrapper_layout: bool = False,
    diffusers_compatible: bool = False,
    best_metric_key: str = 'default',
    consolidation_timeout_minutes: int = 30,
    max_recent_checkpoints: int | None = None
)
```

Dataclass

Configuration for checkpointing.

Every field has a default so the recipe layer can construct this directly
from the YAML `checkpoint:` block merged with the model-derived
`model_repo_id` / `model_cache_dir` / `is_peft` values.  When
`model_cache_dir` is `None` it falls back to the HF hub cache.

**`allow_legacy_pickle_restore`** `bool = False`

---

**`best_metric_key`** `str = 'default'`

---

**`checkpoint_dir`** `str | Path = 'checkpoints/'`

---

**`consolidation_timeout_minutes`** `int = 30`

---

**`cpu_offload`** `bool = False`

---

**`dequantize_base_checkpoint`** `bool | None = None`

---

**`diffusers_compatible`** `bool = False`

---

**`enabled`** `bool = True`

---

**`is_async`** `bool = False`

---

**`is_peft`** `bool = False`

---

**`legacy_paramwrapper_layout`** `bool = False`

---

**`load_metadata_with_gloo`** `bool = False`

---

**`max_recent_checkpoints`** `int | None = None`

---

**`model_cache_dir`** `str | Path | None = None`

---

**`model_repo_id`** `str | None = None`

---

**`model_save_format`** `str = 'safetensors'`

---

**`model_state_dict_keys`** `list[str] | None = None`

---

**`original_model_root_dir`** `str | None = None`

---

**`save_consolidated`** `bool | str | SaveConsolidatedMode = 'final'`

---

**`single_rank_consolidation`** `bool = False`

---

**`skip_task_head_prefixes_for_base_model`** `list[str] | None = None`

---

**`staging_dir`** `str | None = None`

---

**`v4_compatible`** `bool = False`

---

**`wait_for_staging`** `bool = False`

---

```python
nemo_automodel.components.checkpoint.config.CheckpointingConfig.__post_init__()
```

Resolve the cache dir, enforce PEFT constraints, and coerce the save format/mode.

```python
nemo_automodel.components.checkpoint.config.CheckpointingConfig.build(
    dp_rank: int,
    tp_rank: int,
    pp_rank: int,
    moe_mesh: torch.distributed.device_mesh.DeviceMesh | None = None,
    process_group: torch.distributed.ProcessGroup | None = None,
    pp_group: torch.distributed.ProcessGroup | None = None
) -> nemo_automodel.components.checkpoint.checkpointing.Checkpointer
```

Build the `Checkpointer` engine for this config.

`Checkpointer` is imported lazily to avoid a circular import
(`checkpointing.py` imports `CheckpointingConfig` from this module)
and to keep the heavy DCP/safetensors deps out of module load.

**Parameters:**

**`dp_rank`** `int`

Data-parallel rank.

---

**`tp_rank`** `int`

Tensor-parallel rank.

---

**`pp_rank`** `int`

Pipeline-parallel rank.

---

**`moe_mesh`** `DeviceMesh | None` — default: None

Optional device mesh for MoE checkpointing.

---

**`process_group`** `ProcessGroup | None` — default: None

Process group used for distributed checkpoint collectives.

---

**`pp_group`** `ProcessGroup | None` — default: None

Optional pipeline-parallel process group. Threaded to the
PEFT save path so adapter weights are gathered across PP stages
(required for complete adapters when `pp_size > 1`).

---

**Returns:** `Checkpointer`

class:`Checkpointer`.