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# nemo_automodel.components.models.d1.records

Published D1 text prompts with explicit question and option identities.

## Module Contents

### Classes

| Name                                                                          | Description                                            |
| ----------------------------------------------------------------------------- | ------------------------------------------------------ |
| [`D1TextExample`](#nemo_automodel-components-models-d1-records-D1TextExample) | One decision in the publisher's internal option order. |

### Functions

| Name                                                                                | Description                                                               |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------- |
| [`encode_d1_record`](#nemo_automodel-components-models-d1-records-encode_d1_record) | Encode unchanged SOC records using reviewed pinned publisher prompt code. |

### API

```python
class nemo_automodel.components.models.d1.records.D1TextExample(
    record_id: str,
    input_ids: tuple[int, ...],
    question_id: str,
    option_ids: tuple[str, ...],
    marker_positions: tuple[int, ...],
    alias_token_ids: tuple[tuple[int, ...], ...],
    head_question_type: int,
    temperature: float
)
```

Dataclass

One decision in the publisher's internal option order.

Marker positions and alias groups are mutually exclusive model readouts.
Temperature applies to Omni text logits before training and evaluation.
Recipes align labels and rewards separately using the question and option IDs.

**`alias_token_ids`** `tuple[tuple[int, ...], ...]`

---

**`head_question_type`** `int`

---

**`input_ids`** `tuple[int, ...]`

---

**`marker_positions`** `tuple[int, ...]`

---

**`option_ids`** `tuple[str, ...]`

---

**`question_id`** `str`

---

**`record_id`** `str`

---

**`temperature`** `float`

---

```python
nemo_automodel.components.models.d1.records.encode_d1_record(
    record: dict[str, typing.Any],
    tokenizer: typing.Any,
    prompt: types.ModuleType,
    omni: bool,
    max_length: int,
    temperatures: dict[str, float] | None = None
) -> list[nemo_automodel.components.models.d1.records.D1TextExample]
```

Encode unchanged SOC records using reviewed pinned publisher prompt code.

**Parameters:**

**`record`** `dict[str, Any]`

Validated state/questions record. Supervision is not consumed.

---

**`tokenizer`** `Any`

Tokenizer from the same immutable release as the prompt code.

---

**`prompt`** `ModuleType`

Imported publisher prompt module, pinned by the recipe.

---

**`omni`** `bool`

Select the marker encoder instead of the causal token-alias prompt.

---

**`max_length`** `int`

Context limit; causal inputs are rejected rather than truncated.

---

**`temperatures`** `dict[str, float] | None` — default: None

Released Omni text calibration, unchanged across stages.

---

**Returns:** `list[D1TextExample]`

Encoded questions with their model-output option identities. The caller