Datasets:

jeremycochoy
/

gift-pretrain-full-4096

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
item_id: string
start: timestamp[s]
freq: string
target: list<item: float>
  child 0, item: float
past_feat_dynamic_real: fixed_size_list<item: list<item: float>>[7]
  child 0, item: list<item: float>
      child 0, item: float
-- schema metadata --
huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 347
to
{'item_id': Value('string'), 'start': Value('timestamp[s]'), 'freq': Value('string'), 'target': List(Value('float32'))}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1779, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 609, in wrapped
                  for item in generator(*args, **kwargs):
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/arrow/arrow.py", line 74, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/arrow/arrow.py", line 54, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              item_id: string
              start: timestamp[s]
              freq: string
              target: list<item: float>
                child 0, item: float
              past_feat_dynamic_real: fixed_size_list<item: list<item: float>>[7]
                child 0, item: list<item: float>
                    child 0, item: float
              -- schema metadata --
              huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 347
              to
              {'item_id': Value('string'), 'start': Value('timestamp[s]'), 'freq': Value('string'), 'target': List(Value('float32'))}
              because column names don't match
              
              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 1342, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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item_id string	start timestamp[s]	freq string	target list
0	2015-01-01T00:00:00	5T	[61.93913650512695,59.23252487182617,61.99180221557617,62.480655670166016,62.490482330322266,62.5417(...TRUNCATED)
1	2015-01-01T00:00:00	5T	[64.2808837890625,65.08245086669922,65.30912017822266,65.191650390625,65.28766632080078,68.001235961(...TRUNCATED)
2	2015-01-01T00:00:00	5T	[62.077396392822266,64.80834197998047,64.80391693115234,67.20659637451172,67.32328796386719,66.41279(...TRUNCATED)
3	2015-01-01T00:00:00	5T	[60.78642272949219,65.85395050048828,64.26608276367188,63.988426208496094,64.70740509033203,62.72486(...TRUNCATED)
4	2015-01-01T00:00:00	5T	[63.12067413330078,59.20623016357422,62.239200592041016,65.80850982666016,65.70866394042969,63.67469(...TRUNCATED)
5	2015-01-01T00:00:00	5T	[64.44831848144531,62.4967155456543,63.816612243652344,64.75755310058594,65.35836791992188,63.123970(...TRUNCATED)
6	2015-01-01T00:00:00	5T	[63.41112518310547,65.99217987060547,60.19683074951172,62.01144790649414,65.09144592285156,62.115444(...TRUNCATED)
7	2015-01-01T00:00:00	5T	[64.7394790649414,64.71804809570312,65.44779205322266,66.33447265625,63.09504699707031,68.0616760253(...TRUNCATED)
8	2015-01-01T00:00:00	5T	[63.009918212890625,61.24407196044922,63.79776382446289,61.702735900878906,62.18679428100586,61.0574(...TRUNCATED)
9	2015-01-01T00:00:00	5T	[65.26490020751953,65.60872650146484,66.01715850830078,65.73542785644531,65.09737396240234,65.096916(...TRUNCATED)

End of preview.

gift-pretrain-full-4096

Full counterpart to jeremycochoy/gift-pretrain-small-4096: every series of every arrow file in Salesforce/GiftEvalPretrain, cropped into non-overlapping 4096-point windows and globally shuffled. The small companion sub-samples 10 series per sub-dataset; this one keeps everything.

6,376 source arrow files across 152 sub-datasets fully consumed
42,571,692 windows of length 4096 (float32)
4,274 parquet shards, ~619 GB total (zstd)

Layout

.
├── small_v1/                 ← gift-only training shards
│   ├── shard_NNNNN.parquet
│   └── manifest.json
├── eval/                     ← Salesforce/GiftEval mirror (bytes-as-is)
│   ├── m4_daily/
│   ├── ett1/
│   └── ...
└── README.md

(The directory is named small_v1/ purely to match the small companion's layout for tooling compatibility — it is not a small bundle.)

Schema (`small_v1/shard_*.parquet`)

Column	Type	Notes
`series`	`list<float32>[4096]`	Fixed-length non-overlapping window
`source_id`	`uint8`	Always `0` (gift) — bundle is single-source
`meta`	`string`	Original `item_id` from the source arrow file

Compression: zstd, row group size 10_000.

Sampling

For every arrow file in Salesforce/GiftEvalPretrain, every non-NaN target row contributes every non-overlapping 4096-point window. Series shorter than 4096 points yield zero windows and are silently skipped. Output is globally shuffled at row granularity via the two-pass bucket shuffle used for all training bundles in this family (stage 3 of scripts/training_data_prep/), so adjacent rows in shard_NNNNN.parquet are independent draws from the entire corpus.

NaN handling: GIFT pretrain contains a small fraction of partial or all-NaN target values; those rows pass through the pipeline unchanged. Consumers should forward-fill partials and skip all-NaN rows.

Reproducing

python -m training_data_prep.build_gift_only_bundle \
    --output-dir /path/to/out \
    --window-length 4096 \
    --all-files \
    --max-workers 48

The --all-files switch was added in jeremycochoy/rnd PR #305.

Downloads last month: 11,750

Total file size:

620 GB

gift-pretrain-full-4096

Layout

Schema (small_v1/shard_*.parquet)

Sampling

Reproducing

Schema (`small_v1/shard_*.parquet`)