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# nemo_automodel.components.checkpoint.config

Public config surface for the checkpoint component.

`CheckpointingConfig` holds the typed parameters that drive checkpointing
behaviour and exposes `.build()` to construct the :class:`Checkpointer`
engine (defined in `checkpointing.py`).  Every field has a sensible default
so the recipe layer can construct it directly from the YAML `checkpoint:`
block plus the model-derived `model_repo_id` / `model_cache_dir` /
`is_peft` arguments — there is no separate builder/adapter.

## Module Contents

### Classes

| Name                                                                                        | Description                                             |
| ------------------------------------------------------------------------------------------- | ------------------------------------------------------- |
| [`CheckpointingConfig`](#nemo_automodel-components-checkpoint-config-CheckpointingConfig)   | Configuration for checkpointing.                        |
| [`SaveConsolidatedMode`](#nemo_automodel-components-checkpoint-config-SaveConsolidatedMode) | Controls when consolidated HF safetensors are exported. |

### Functions

| Name                                                                                                        | Description                                                              |
| ----------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| [`_is_geq_torch_2_9`](#nemo_automodel-components-checkpoint-config-_is_geq_torch_2_9)                       | Check if the current torch version is greater than or equal to 2.9.0.    |
| [`_is_leq_torch_2_7_1`](#nemo_automodel-components-checkpoint-config-_is_leq_torch_2_7_1)                   | Check if the current torch version is less than or equal to 2.7.1.       |
| [`_normalize_save_consolidated`](#nemo_automodel-components-checkpoint-config-_normalize_save_consolidated) | Normalize legacy bools and string aliases to a consolidated export mode. |

### Data

[`_TORCH_2_7_1`](#nemo_automodel-components-checkpoint-config-_TORCH_2_7_1)

[`_TORCH_2_9`](#nemo_automodel-components-checkpoint-config-_TORCH_2_9)

[`__all__`](#nemo_automodel-components-checkpoint-config-__all__)

### 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,
    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,
    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`

---

**`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 :class:`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`.

```python
class nemo_automodel.components.checkpoint.config.SaveConsolidatedMode
```

**Bases:** `enum.Enum`

Controls when consolidated HF safetensors are exported.

**`EVERY`** `= 'every'`

---

**`FALSE`** `= 'false'`

---

**`FINAL`** `= 'final'`

---

```python
nemo_automodel.components.checkpoint.config._is_geq_torch_2_9() -> bool
```

Check if the current torch version is greater than or equal to 2.9.0.

```python
nemo_automodel.components.checkpoint.config._is_leq_torch_2_7_1() -> bool
```

Check if the current torch version is less than or equal to 2.7.1.

```python
nemo_automodel.components.checkpoint.config._normalize_save_consolidated(
    value: bool | str | nemo_automodel.components.checkpoint.config.SaveConsolidatedMode
) -> nemo_automodel.components.checkpoint.config.SaveConsolidatedMode
```

Normalize legacy bools and string aliases to a consolidated export mode.

```python
nemo_automodel.components.checkpoint.config._TORCH_2_7_1 = (2, 7, 1)
```

```python
nemo_automodel.components.checkpoint.config._TORCH_2_9 = (2, 9)
```

```python
nemo_automodel.components.checkpoint.config.__all__ = ['CheckpointingConfig', 'SaveConsolidatedMode']
```