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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1400, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 977, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
0.jpg image | 1.jpg image | json dict | __key__ string | __url__ string |
|---|---|---|---|---|
{
"caption": "Add gray smoke billowing out of the chimney of the green steam locomotive."
} | i2i_000000 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/i2i.tar | ||
{
"caption": "Add a large white motorboat to the water in the foreground and a person walking down the pier, while slightly adjusting the camera perspective to focus on the new boat."
} | i2i_000001 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/i2i.tar | ||
Not supported with pagination yet | {
"caption": "Replace the black floor lamp in the background with the potted fiddle-leaf fig plant shown in Image 1. Ensure the plant is placed in the same position as the original lamp and that its lighting matches the rest of the video."
} | iv2v_000000 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/iv2v.tar | |
Not supported with pagination yet | {
"caption": "Replace the purple exercise mat on the floor with the thick blue textured exercise mat shown in Image 1."
} | iv2v_000001 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/iv2v.tar | |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "Replace the woman's top in Image 2 with the khaki short-sleeved T-shirt featuring a 'B' logo from Image 1, while keeping her sitting posture, the item in her hands, and the background unchanged."
} | r2i_000000 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/r2i.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "Replace the model's top in Image 2 with the light blue short-sleeved knit sweater featuring a dark blue graphic from Image 1. Please keep the model's pose, original skirt, and background unchanged."
} | r2i_000001 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/r2i.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "This is a photograph of an indoor stage event. The background is completely black, with lighting focused on the stage. On the left side of the stage, a woman with reddish-brown hair stands behind a blue podium, holding a microphone. She is wearing a dark, sleeveless top. Behind her, a large LED screen d... | t2i_000000 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/t2i.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "This is a daytime landscape photograph taken from a low angle near the surface of a body of water. The foreground is dominated by the dark green, rippling water, which reflects the sky and surrounding elements. In the midground, a long, narrow pedestrian bridge spans the water. The bridge is flanked by ... | t2i_000001 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/t2i.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "The video presents a continuous, slow forward tracking shot through a meticulously landscaped outdoor garden bathed in bright sunlight. In the immediate foreground, a dark stone fountain basin sits centered in a clear, shallow stream, ejecting a steady jet of water upward that creates ripples on the sur... | t2v_000000 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/t2v.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "In a warmly lit indoor setting, a German Shepherd dog is initially seated on a polished wooden floor beside a large window, bathed in the golden glow of sunlight streaming through the glass. The dog's coat displays rich black and tan markings, with its ears perked upright as it gazes intently outside. A... | t2v_000001 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/t2v.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "Transform the flat rectangular push-mop with grey head into an iron lantern pole wreathed in flame — a long, twisted, rope-like metal shaft that appears dark brown/black and slightly weathered, terminating in a small spherical cage of charred material that holds the fuel; the head is engulfed in bright,... | v2v_000000 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/v2v.tar |
Not supported with pagination yet | Not supported with pagination yet | {
"caption": "Transform the push-broom with stiff bristles into an angled flat mop with a low-profile, rectangular head made of light gray plastic and a long, slender matching gray handle. the head has a pale, slightly textured cleaning pad that shows darker smudges where it picks up dirt, while the plastic surfaces ... | v2v_000001 | hf://datasets/EasonXiao-888/JoyAI-Video-Edit_ToyData@d12402efb0b809e823dd1f8512c416c2a1c91e4f/v2v.tar |
JoyAI-Video-Edit Toy Data
A small example dataset for checking data loading and running training smoke tests with JoyAI-Video-Edit. It contains 12 samples across six tasks, with two samples per task. It is not a full training dataset or an evaluation benchmark.
GitHub repository: jd-opensource/JoyAI-Video-Edit.
Data Format
Samples are stored in WebDataset TAR archives. Each sample shares a filename prefix across its media files and a JSON record containing only a caption string:
{"caption": "The selected description or editing instruction."}
| Archive | Task | Media fields |
|---|---|---|
t2i.tar |
Text-to-image | jpg: target image |
i2i.tar |
Image editing | 0.jpg: source; 1.jpg: target |
r2i.tar |
Reference-guided image editing | 0.png: reference; 1.png: source; 2.png: target |
t2v.tar |
Text-to-video | mp4: target video |
v2v.tar |
Video editing | 0.mp4: source; 1.mp4: target |
iv2v.tar |
Reference-guided video editing | 0.jpg: reference; 0.mp4: source; 1.mp4: target |
Use caption as the only caption key for all tasks. The four training manifests group the archives as follows:
t2i.json:t2i.tar(2 samples).i2i.json:i2i.tarandr2i.tar(4 samples).t2v.json:t2v.tar(2 samples).v2v.json:v2v.tarandiv2v.tar(4 samples).
Local Training
Run these commands from the JoyAI-Video-Edit project directory:
hf download EasonXiao-888/JoyAI-Video-Edit_ToyData --repo-type dataset --local-dir data
python - <<'PY'
import json
from pathlib import Path
root = Path("data").resolve()
for name in ("t2i", "i2i", "t2v", "v2v"):
manifest_path = root / f"{name}.json"
manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
manifest["resolved_files"] = [
str(root / Path(shard).name) for shard in manifest["resolved_files"]
]
manifest_path.write_text(json.dumps(manifest, indent=2) + "\n", encoding="utf-8")
PY
The published manifests use portable filenames. The Python command converts them to local absolute paths for the training loader. Use the four JSON files as the training data manifests; all caption keys should be ["caption"] with sampling weights [1.0].
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