feat: add prompt only image generation datasets

docs/user_manual/configure.rst

@@ -269,9 +269,9 @@ Underneath you can find the list of all the available datasets.
      - ``text_generation_collate``
      - ``text: str``
    * - Image Generation
-     - `LAION256 <https://huggingface.co/datasets/nannullna/laion_subset>`_, `OpenImage <https://huggingface.co/datasets/data-is-better-together/open-image-preferences-v1>`_, `COCO <https://huggingface.co/datasets/phiyodr/coco2017>`_
-     - ``image_generation_collate``
-     - ``image: PIL.Image.Image``, ``text: str``
+     - `LAION256 <https://huggingface.co/datasets/nannullna/laion_subset>`_, `OpenImage <https://huggingface.co/datasets/data-is-better-together/open-image-preferences-v1>`_, `COCO <https://huggingface.co/datasets/phiyodr/coco2017>`_, `DrawBench <https://huggingface.co/datasets/sayakpaul/drawbench>`_, `PartiPrompts <https://huggingface.co/datasets/nateraw/parti-prompts>`_, `GenAIBench <https://huggingface.co/datasets/BaiqiL/GenAI-Bench>`_
+     - ``image_generation_collate``, ``prompt_collate``
+     - ``text: str``, ``image: Optional[PIL.Image.Image]``
    * - Image Classification
      - `ImageNet <https://huggingface.co/datasets/zh-plus/tiny-imagenet>`_, `MNIST <https://huggingface.co/datasets/ylecun/mnist>`_, `CIFAR10 <https://huggingface.co/datasets/uoft-cs/cifar10>`_
      - ``image_classification_collate``

src/pruna/data/__init__.py

@@ -24,6 +24,11 @@
     setup_imagenet_dataset,
     setup_mnist_dataset,
 )
+from pruna.data.datasets.prompt import (
+    setup_drawbench_dataset,
+    setup_genai_bench_dataset,
+    setup_parti_prompts_dataset,
+)
 from pruna.data.datasets.question_answering import setup_polyglot_dataset
 from pruna.data.datasets.text_generation import (
     setup_c4_dataset,
@@ -56,4 +61,7 @@
     "Polyglot": (setup_polyglot_dataset, "question_answering_collate", {}),
     "OpenImage": (setup_open_image_dataset, "image_generation_collate", {"img_size": 1024}),
     "CIFAR10": (setup_cifar10_dataset, "image_classification_collate", {"img_size": 32}),
+    "DrawBench": (setup_drawbench_dataset, "prompt_collate", {}),
+    "PartiPrompts": (setup_parti_prompts_dataset, "prompt_collate", {}),
+    "GenAIBench": (setup_genai_bench_dataset, "prompt_collate", {}),
 }

src/pruna/data/collate.py

@@ -92,6 +92,25 @@ def image_generation_collate(data: Any, img_size: int, output_format: str = "int
     return texts, images_tensor
 
 
+def prompt_collate(data: Any) -> Tuple[List[str], None]:
+    """
+    Custom collation function for prompt datasets.
+
+    Expects a ``text`` column containing the clear-text prompt in the dataset.
+
+    Parameters
+    ----------
+    data : Any
+        The data to collate.
+
+    Returns
+    -------
+    Tuple[List[str], None]
+        The collated data.
+    """
+    return [item["text"] for item in data], None
+
+
 def audio_collate(data: Any) -> Tuple[List[str], List[str]]:
     """
     Custom collation function for audio datasets.
@@ -226,4 +245,5 @@ def question_answering_collate(
     "image_classification_collate": image_classification_collate,
     "text_generation_collate": text_generation_collate,
     "question_answering_collate": question_answering_collate,
+    "prompt_collate": prompt_collate,
 }

src/pruna/data/datasets/prompt.py

@@ -0,0 +1,85 @@
+# Copyright 2025 - Pruna AI GmbH. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Tuple
+
+from datasets import Dataset, load_dataset
+
+from pruna.logging.logger import pruna_logger
+
+
+def setup_drawbench_dataset(seed: int) -> Tuple[Dataset, Dataset, Dataset]:
+    """
+    Setup the DrawBench dataset.
+
+    License: Apache 2.0
+
+    Parameters
+    ----------
+    seed : int
+        The seed to use.
+
+    Returns
+    -------
+    Tuple[Dataset, Dataset, Dataset]
+        The DrawBench dataset.
+    """
+    ds = load_dataset("sayakpaul/drawbench", trust_remote_code=True)["train"]
+    ds = ds.rename_column("Prompts", "text")
+    pruna_logger.info("DrawBench is a test-only dataset. Do not use it for training or validation.")
+    return ds.select([0]), ds.select([0]), ds
+
+
+def setup_parti_prompts_dataset(seed: int) -> Tuple[Dataset, Dataset, Dataset]:
+    """
+    Setup the Parti Prompts dataset.
+
+    License: Apache 2.0
+
+    Parameters
+    ----------
+    seed : int
+        The seed to use.
+
+    Returns
+    -------
+    Tuple[Dataset, Dataset, Dataset]
+        The Parti Prompts dataset.
+    """
+    ds = load_dataset("nateraw/parti-prompts")["train"]
+    ds = ds.rename_column("Prompt", "text")
+    pruna_logger.info("PartiPrompts is a test-only dataset. Do not use it for training or validation.")
+    return ds.select([0]), ds.select([0]), ds
+
+
+def setup_genai_bench_dataset(seed: int) -> Tuple[Dataset, Dataset, Dataset]:
+    """
+    Setup the GenAI Bench dataset.
+
+    License: Apache 2.0
+
+    Parameters
+    ----------
+    seed : int
+        The seed to use.
+
+    Returns
+    -------
+    Tuple[Dataset, Dataset, Dataset]
+        The GenAI Bench dataset.
+    """
+    ds = load_dataset("BaiqiL/GenAI-Bench")["train"]
+    ds = ds.rename_column("Prompt", "text")
+    pruna_logger.info("GenAI-Bench is a test-only dataset. Do not use it for training or validation.")
+    return ds.select([0]), ds.select([0]), ds

tests/data/test_datamodule.py

@@ -36,6 +36,9 @@ def iterate_dataloaders(datamodule: PrunaDataModule) -> None:
         pytest.param("OpenAssistant", dict(tokenizer=bert_tokenizer), marks=pytest.mark.slow),
         pytest.param("C4", dict(tokenizer=bert_tokenizer), marks=pytest.mark.slow),
         pytest.param("Polyglot", dict(tokenizer=bert_tokenizer), marks=pytest.mark.slow),
+        pytest.param("DrawBench", dict(), marks=pytest.mark.slow),
+        pytest.param("PartiPrompts", dict(), marks=pytest.mark.slow),
+        pytest.param("GenAIBench", dict(), marks=pytest.mark.slow),
     ],
 )
 def test_dm_from_string(dataset_name: str, collate_fn_args: dict[str, Any]) -> None: