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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: JSON parse error: The document is empty.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 342, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1391, in _parse
self.obj = DataFrame(
~~~~~~~~~^
ujson_loads(json, precise_float=self.precise_float), dtype=None
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/core/frame.py", line 782, in __init__
mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 503, in dict_to_mgr
return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 114, in arrays_to_mgr
index = _extract_index(arrays)
File "/usr/local/lib/python3.14/site-packages/pandas/core/internals/construction.py", line 677, in _extract_index
raise ValueError("All arrays must be of the same length")
ValueError: All arrays must be of the same length
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 345, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: The document is empty.
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 1379, 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 956, 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 1702, 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 1887, 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.
name string | year int64 | seed int64 | items int64 | items_per_site int64 | max_context int64 | context_lengths list | items_file string | embedding_root string | context_rule string | pixel_index string | array_layout dict | sites list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
validation | 2,025 | 20,260,926 | 50,000 | 5,000 | 12 | [
3,
5,
9,
12
] | val_config_items.npz | /maps/jl2692/forecast_benchmark/olmoearth_nano_s1_rtc_2024_2025_patch5 | 12 random distinct earlier 2025 scenes sorted oldest->newest; length-k context = last k of them (nested), so every k shares the same pixel and target date | row-major index into the site's embedding grid (row * width + col); pixel centre = affine(transform) * (col + .5, row + .5) in grid crs | {
"site": "index into 'sites'",
"pixel": "int32",
"target": "index into that site's 2025 'scenes'",
"context": "int16 [N, 12] indices into the same scene list, ascending"
} | [
{
"id": "biome_022_central_chile",
"group": "mediterranean",
"grid": {
"width": 200,
"height": 200,
"crs": "EPSG:32719",
"transform": [
50,
0,
305780,
0,
-50,
6235400
]
},
"scenes": [
{
"path": "biome_022... |
E²Forecast data
Benchmarks for Forecasting Earth Surface Change in Embedding Space. Code: https://github.com/ucam-eo/e2forecast. Checkpoints: https://huggingface.co/JingtaoLi/E2Forecast.
S1_Embed
OLMoEarth-nano (patch 5, 128-D) embeddings of every descending Sentinel-1 RTC acquisition in 2024–2025, at 100 sites (biome and urban), each a 200 × 200 grid.
embeddings/<site>/<year>/<timestamp>_..._128d.tif: one 128-band GeoTIFF per scene;embeddings/embedding_manifest.jsonlists every scene.config/split.json: training sites. Training uses 2024 only.config/{val,test}_config.json+*_items.npz: fixed 2025 evaluation items. Each item is a site, a pixel, a target scene and 12 earlier scenes; the test set has 50 sites × 20,000 items.
S2_Embed
PASTIS Sentinel-2 L2A patches embedded per date with Prithvi-EO-2.0-300M: a 1024-D token per 16 × 16 px, 8 × 8 tokens per patch.
embeddings_prithvi_eo_2_300M/S2_<ID_PATCH>.npy: float16, shape (T, 8, 8, 1024), dates in chronological order.benchmark_config/:config.json(context length 37), the patch split 1461 / 486 / 486, and the fixed{val,test}_samples.npz. Each sample is a patch, a token, a target date and 37 earlier dates; the paper reports the first 100,000 test samples.PASTIS/metadata.geojson: acquisition dates and patch footprints from PASTIS (Garnot & Landrieu, 2021).
INR
satclip_s2_100k/satclip_embeddings_location_{000493..000542}.tar: webdataset shards of the S2-100K images. Each sample holds .npy, the 256-D SatCLIP embedding, and .txt, "lon,lat,...".
The GSA data is not included.
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