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https://github.com/huggingface/datasets/issues/5597
in-place dataset update
We won't support in-place modifications since `datasets` is based on the Apache Arrow format which doesn't support in-place modifications. In your case the old dataset is garbage collected pretty quickly so you won't have memory issues. Note that datasets loaded from disk (memory mapped) are not loaded in memory,...
### Motivation For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this. ```python from datasets import Dataset ds = Datas...
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in-place dataset update ### Motivation For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this. ```python from datasets im...
https://github.com/huggingface/datasets/issues/5597
in-place dataset update
Thank you for your detailed reply. > In your case the old dataset is garbage collected pretty quickly so you won't have memory issues. I understand this, but it still copies the old dataset to create the new one, is this correct? So maybe it is not memory-consuming, but time-consuming?
### Motivation For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this. ```python from datasets import Dataset ds = Datas...
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in-place dataset update ### Motivation For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this. ```python from datasets im...
https://github.com/huggingface/datasets/issues/5597
in-place dataset update
Indeed, and because of that it is more efficient to add multiple rows at once instead of one by one, using `concatenate_datasets` for example.
### Motivation For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this. ```python from datasets import Dataset ds = Datas...
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in-place dataset update ### Motivation For the circumstance that I creat an empty `Dataset` and keep appending new rows into it, I found that it leads to creating a new dataset at each call. It looks quite memory-consuming. I just wonder if there is any more efficient way to do this. ```python from datasets im...
https://github.com/huggingface/datasets/issues/5596
[TypeError: Couldn't cast array of type] Can only load a subset of the dataset
Apparently some JSON objects have a `"labels"` field. Since this field is not present in every object, you must specify all the fields types in the README.md EDIT: actually specifying the feature types doesn’t solve the issue, it raises an error because “labels” is missing in the data
### Describe the bug I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error: ``` casted_values = _c(array.values, feature[0]) File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 1839, in wr...
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[TypeError: Couldn't cast array of type] Can only load a subset of the dataset ### Describe the bug I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error: ``` casted_values = _c(array.values, feature[0]) ...
https://github.com/huggingface/datasets/issues/5596
[TypeError: Couldn't cast array of type] Can only load a subset of the dataset
We've updated the dataset to remove the extra `labels` field from some files, closing this issue. Thanks!
### Describe the bug I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error: ``` casted_values = _c(array.values, feature[0]) File "/opt/conda/lib/python3.7/site-packages/datasets/table.py", line 1839, in wr...
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[TypeError: Couldn't cast array of type] Can only load a subset of the dataset ### Describe the bug I'm trying to load this [dataset](https://huggingface.co/datasets/bigcode-data/the-stack-gh-issues) which consists of jsonl files and I get the following error: ``` casted_values = _c(array.values, feature[0]) ...
https://github.com/huggingface/datasets/issues/5594
Error while downloading the xtreme udpos dataset
Hi! I cannot reproduce this error on my machine. The raised error could mean that one of the downloaded files is corrupted. To verify this is not the case, you can run `load_dataset` as follows: ```python train_dataset = load_dataset('xtreme', 'udpos.English', split="train", cache_dir=args.cache_dir, download_mode...
### Describe the bug Hi, I am facing an error while downloading the xtreme udpos dataset using load_dataset. I have datasets 2.10.1 installed ```Downloading and preparing dataset xtreme/udpos.Arabic to /compute/tir-1-18/skhanuja/multilingual_ft/cache/data/xtreme/udpos.Arabic/1.0.0/29f5d57a48779f37ccb75cb8708d1...
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Error while downloading the xtreme udpos dataset ### Describe the bug Hi, I am facing an error while downloading the xtreme udpos dataset using load_dataset. I have datasets 2.10.1 installed ```Downloading and preparing dataset xtreme/udpos.Arabic to /compute/tir-1-18/skhanuja/multilingual_ft/cache/data/xtre...
https://github.com/huggingface/datasets/issues/5586
.sort() is broken when used after .filter(), only in 2.10.0
Thanks for reporting and thanks @mariosasko for fixing ! We just did a patch release `2.10.1` with the fix
### Describe the bug Hi, thank you for your support! It seems like the addition of multiple key sort (#5502) in 2.10.0 broke the `.sort()` method. After filtering a dataset with `.filter()`, the `.sort()` seems to refer to the query_table index of the previous unfiltered dataset, resulting in an IndexError. ...
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.sort() is broken when used after .filter(), only in 2.10.0 ### Describe the bug Hi, thank you for your support! It seems like the addition of multiple key sort (#5502) in 2.10.0 broke the `.sort()` method. After filtering a dataset with `.filter()`, the `.sort()` seems to refer to the query_table index of t...
https://github.com/huggingface/datasets/issues/5585
Cache is not transportable
Hi ! No the cache is not transportable in general. It will work on a shared filesystem if you use the same python environment, but not across machines/os/environments. In particular, reloading cached datasets does work, but reloading cached processed datasets (e.g. from `map`) may not work. This is because some hash...
### Describe the bug I would like to share cache between two machines (a Windows host machine and a WSL instance). I run most my code in WSL. I have just run out of space in the virtual drive. Rather than expand the drive size, I plan to move to cache to the host Windows machine, thereby sharing the downloads. I...
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Cache is not transportable ### Describe the bug I would like to share cache between two machines (a Windows host machine and a WSL instance). I run most my code in WSL. I have just run out of space in the virtual drive. Rather than expand the drive size, I plan to move to cache to the host Windows machine, thereb...
https://github.com/huggingface/datasets/issues/5584
Unable to load coyo700M dataset
Hi @manuaero Thank you for your interest in the COYO dataset. Our dataset provides the img-url and alt-text in the form of a parquet, so to utilize the coyo dataset you will need to download it directly. We provide a [guide](https://github.com/kakaobrain/coyo-dataset/blob/main/download/README.md) to download,...
### Describe the bug Seeing this error when downloading https://huggingface.co/datasets/kakaobrain/coyo-700m: ```ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.``` Full stack trace ```Downloading and preparing dataset parquet/kakaobrain--coy...
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Unable to load coyo700M dataset ### Describe the bug Seeing this error when downloading https://huggingface.co/datasets/kakaobrain/coyo-700m: ```ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.``` Full stack trace ```Downloading and prepari...
https://github.com/huggingface/datasets/issues/5577
Cannot load `the_pile_openwebtext2`
Hi! I've merged a PR to use `int32` instead of `int8` for `reddit_scores`, so it should work now.
### Describe the bug I met the same bug mentioned in #3053 which is never fixed. Because several `reddit_scores` are larger than `int8` even `int16`. https://huggingface.co/datasets/the_pile_openwebtext2/blob/main/the_pile_openwebtext2.py#L62 ### Steps to reproduce the bug ```python3 from datasets import load...
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Cannot load `the_pile_openwebtext2` ### Describe the bug I met the same bug mentioned in #3053 which is never fixed. Because several `reddit_scores` are larger than `int8` even `int16`. https://huggingface.co/datasets/the_pile_openwebtext2/blob/main/the_pile_openwebtext2.py#L62 ### Steps to reproduce the bug ...
https://github.com/huggingface/datasets/issues/5575
Metadata for each column
Hi! Indeed it would be useful to support this. PyArrow natively supports schema-level and column-level, so implementing this should be straightforward. The API I have in mind would work as follows: ```python col_feature = Value("string", metadata="Some column-level metadata") features = Features({"col": col_featur...
### Feature request Being able to put some metadata for each column as a string or any other type. ### Motivation I will bring the motivation by an example, lets say we are experimenting with embedding produced by some image encoder network, and we want to iterate through a couple of preprocessing and see which on...
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Metadata for each column ### Feature request Being able to put some metadata for each column as a string or any other type. ### Motivation I will bring the motivation by an example, lets say we are experimenting with embedding produced by some image encoder network, and we want to iterate through a couple of pre...
https://github.com/huggingface/datasets/issues/5574
c4 dataset streaming fails with `FileNotFoundError`
Also encountering this issue for every dataset I try to stream! Installed datasets from main: ``` - `datasets` version: 2.10.1.dev0 - Platform: macOS-13.1-arm64-arm-64bit - Python version: 3.9.13 - PyArrow version: 10.0.1 - Pandas version: 1.5.2 ``` Repro: ```python from datasets import load_dataset spig...
### Describe the bug Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`. ### Steps to reproduce the bug ```python from datasets import load_dataset dataset = load_dataset("c4", "en", split="train", ...
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c4 dataset streaming fails with `FileNotFoundError` ### Describe the bug Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`. ### Steps to reproduce the bug ```python from datasets import load_dataset...
https://github.com/huggingface/datasets/issues/5574
c4 dataset streaming fails with `FileNotFoundError`
This problem now appears again, this time with an underlying HTTP 502 status code: ``` aiohttp.client_exceptions.ClientResponseError: 502, message='Bad Gateway', url=URL('https://huggingface.co/datasets/allenai/c4/resolve/1ddc917116b730e1859edef32896ec5c16be51d0/en/c4-validation.00002-of-00008.json.gz') ```
### Describe the bug Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`. ### Steps to reproduce the bug ```python from datasets import load_dataset dataset = load_dataset("c4", "en", split="train", ...
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c4 dataset streaming fails with `FileNotFoundError` ### Describe the bug Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`. ### Steps to reproduce the bug ```python from datasets import load_dataset...
https://github.com/huggingface/datasets/issues/5574
c4 dataset streaming fails with `FileNotFoundError`
Re-executing a minute later, the underlying cause is an HTTP 403 status code, as reported yesterday: ``` aiohttp.client_exceptions.ClientResponseError: 403, message='Forbidden', url=URL('https://cdn-lfs.huggingface.co/datasets/allenai/c4/4bf6b248b0f910dcde2cdf2118d6369d8208c8f9515ec29ab73e531f380b18e2?response-cont...
### Describe the bug Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`. ### Steps to reproduce the bug ```python from datasets import load_dataset dataset = load_dataset("c4", "en", split="train", ...
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c4 dataset streaming fails with `FileNotFoundError` ### Describe the bug Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`. ### Steps to reproduce the bug ```python from datasets import load_dataset...
https://github.com/huggingface/datasets/issues/5571
load_dataset fails for JSON in windows
Hi! You need to pass an input json file explicitly as `data_files` to `load_dataset` to avoid this error: ```python ds = load_dataset("json", data_files=args.input_json) ```
### Describe the bug Steps: 1. Created a dataset in a Linux VM and created a small sample using dataset.to_json() method. 2. Downloaded the JSON file to my local Windows machine for working and saved in say - r"C:\Users\name\file.json" 3. I am reading the file in my local PyCharm - the location of python file is di...
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load_dataset fails for JSON in windows ### Describe the bug Steps: 1. Created a dataset in a Linux VM and created a small sample using dataset.to_json() method. 2. Downloaded the JSON file to my local Windows machine for working and saved in say - r"C:\Users\name\file.json" 3. I am reading the file in my local Py...
https://github.com/huggingface/datasets/issues/5570
load_dataset gives FileNotFoundError on imagenet-1k if license is not accepted on the hub
Hi, thanks for the feedback! Would it help to add a tip or note saying the dataset is gated and you need to accept the license before downloading it?
### Describe the bug When calling ```load_dataset('imagenet-1k')``` FileNotFoundError is raised, if not logged in and if logged in with huggingface-cli but not having accepted the licence on the hub. There is no error once accepting. ### Steps to reproduce the bug ``` from datasets import load_dataset imagenet =...
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load_dataset gives FileNotFoundError on imagenet-1k if license is not accepted on the hub ### Describe the bug When calling ```load_dataset('imagenet-1k')``` FileNotFoundError is raised, if not logged in and if logged in with huggingface-cli but not having accepted the licence on the hub. There is no error once acce...
https://github.com/huggingface/datasets/issues/5568
dataset.to_iterable_dataset() loses useful info like dataset features
Hi ! Oh good catch. I think the features should be passed to `IterableDataset.from_generator()` in `to_iterable_dataset()` indeed. Setting this as a good first issue if someone would like to contribute, otherwise we can take care of it :)
### Describe the bug Hello, I like the new `to_iterable_dataset` feature but I noticed something that seems to be missing. When using `to_iterable_dataset` to transform your map style dataset into iterable dataset, you lose valuable metadata like the features. These metadata are useful if you want to interleav...
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dataset.to_iterable_dataset() loses useful info like dataset features ### Describe the bug Hello, I like the new `to_iterable_dataset` feature but I noticed something that seems to be missing. When using `to_iterable_dataset` to transform your map style dataset into iterable dataset, you lose valuable metadata l...
https://github.com/huggingface/datasets/issues/5568
dataset.to_iterable_dataset() loses useful info like dataset features
seems like the feature parameter is missing from `return IterableDataset.from_generator(Dataset._iter_shards, gen_kwargs={"shards": shards})` hence it defaults to None.
### Describe the bug Hello, I like the new `to_iterable_dataset` feature but I noticed something that seems to be missing. When using `to_iterable_dataset` to transform your map style dataset into iterable dataset, you lose valuable metadata like the features. These metadata are useful if you want to interleav...
17
dataset.to_iterable_dataset() loses useful info like dataset features ### Describe the bug Hello, I like the new `to_iterable_dataset` feature but I noticed something that seems to be missing. When using `to_iterable_dataset` to transform your map style dataset into iterable dataset, you lose valuable metadata l...
https://github.com/huggingface/datasets/issues/5555
`.shuffle` throwing error `ValueError: Protocol not known: parent`
Hi ! The indices mapping is written in the same cachedirectory as your dataset. Can you run this to show your current cache directory ? ```python print(train_dataset.cache_files) ```
### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle() File /opt/conda/envs/pytorch/lib/python3.9/site-packages/dataset...
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`.shuffle` throwing error `ValueError: Protocol not known: parent` ### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle(...
https://github.com/huggingface/datasets/issues/5555
`.shuffle` throwing error `ValueError: Protocol not known: parent`
``` [{'filename': '.../train/dataset.arrow'}, {'filename': '.../train/dataset.arrow'}] ``` These are the actual paths where `.hf` files are stored.
### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle() File /opt/conda/envs/pytorch/lib/python3.9/site-packages/dataset...
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`.shuffle` throwing error `ValueError: Protocol not known: parent` ### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle(...
https://github.com/huggingface/datasets/issues/5555
`.shuffle` throwing error `ValueError: Protocol not known: parent`
I'm not aware of any `.hf` file ? What are you referring to ? Also the error says "Protocol unknown: parent". Is there a chance you may have ended up with a path that contains this string `parent://` ?
### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle() File /opt/conda/envs/pytorch/lib/python3.9/site-packages/dataset...
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`.shuffle` throwing error `ValueError: Protocol not known: parent` ### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle(...
https://github.com/huggingface/datasets/issues/5555
`.shuffle` throwing error `ValueError: Protocol not known: parent`
I figured out why the issue was occuring but don't know the long-term fix. The dataset I was trying to shuffle was loaded from a saved file which had `::` delimiter in filename. When I try with the exact same file without `::` in filename, it works as expected. Quick fix is to not use colons in filename. But if this ...
### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle() File /opt/conda/envs/pytorch/lib/python3.9/site-packages/dataset...
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`.shuffle` throwing error `ValueError: Protocol not known: parent` ### Describe the bug ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [16], line 1 ----> 1 train_dataset = train_dataset.shuffle(...
https://github.com/huggingface/datasets/issues/5546
Downloaded datasets do not cache at $HF_HOME
Hi ! Can you make sure you set `HF_HOME` before importing `datasets` ? Then you can print ```python print(datasets.config.HF_CACHE_HOME) print(datasets.config.HF_DATASETS_CACHE) ```
### Describe the bug In the huggingface course (https://huggingface.co/course/chapter3/2?fw=pt) it said that if we set HF_HOME, downloaded datasets would be cached at specified address but it does not. downloaded models from checkpoint names are downloaded and cached at HF_HOME but this is not the case for datasets, t...
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Downloaded datasets do not cache at $HF_HOME ### Describe the bug In the huggingface course (https://huggingface.co/course/chapter3/2?fw=pt) it said that if we set HF_HOME, downloaded datasets would be cached at specified address but it does not. downloaded models from checkpoint names are downloaded and cached at H...
https://github.com/huggingface/datasets/issues/5543
the pile datasets url seems to change back
Thanks for reporting, @wjfwzzc. I am transferring this issue to the corresponding dataset on the Hub: https://huggingface.co/datasets/bookcorpusopen/discussions/1
### Describe the bug in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again. ### Steps to reproduce the bug ```python3 from datasets import load_dataset dataset = load_dataset("bookcorpusopen") ``` shows ```python3 ...
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the pile datasets url seems to change back ### Describe the bug in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again. ### Steps to reproduce the bug ```python3 from datasets import load_dataset dataset = load_datase...
https://github.com/huggingface/datasets/issues/5543
the pile datasets url seems to change back
Thank you. All fixes are done: - [x] https://huggingface.co/datasets/bookcorpusopen/discussions/2 - [x] https://huggingface.co/datasets/the_pile/discussions/1 - [x] https://huggingface.co/datasets/the_pile_books3/discussions/1 - [x] https://huggingface.co/datasets/the_pile_openwebtext2/discussions/2 - [x] https://...
### Describe the bug in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again. ### Steps to reproduce the bug ```python3 from datasets import load_dataset dataset = load_dataset("bookcorpusopen") ``` shows ```python3 ...
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the pile datasets url seems to change back ### Describe the bug in #3627, the host url of the pile dataset became `https://mystic.the-eye.eu`. Now the new url is broken, but `https://the-eye.eu` seems to work again. ### Steps to reproduce the bug ```python3 from datasets import load_dataset dataset = load_datase...
https://github.com/huggingface/datasets/issues/5541
Flattening indices in selected datasets is extremely inefficient
Running the script above on the branch https://github.com/huggingface/datasets/pull/5542 results in the expected behaviour: ``` Num chunks for original ds: 1 Original ds save/load save_to_disk -- RAM memory used: 0.671875 MB -- Total time: 0.255265 s load_from_disk -- RAM memory used: 42.796875 MB -- Total time: 0...
### Describe the bug If we perform a `select` (or `shuffle`, `train_test_split`, etc.) operation on a dataset , we end up with a dataset with an `indices_table`. Currently, flattening such dataset consumes a lot of memory and the resulting flat dataset contains ChunkedArrays with as many chunks as there are rows. Thi...
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Flattening indices in selected datasets is extremely inefficient ### Describe the bug If we perform a `select` (or `shuffle`, `train_test_split`, etc.) operation on a dataset , we end up with a dataset with an `indices_table`. Currently, flattening such dataset consumes a lot of memory and the resulting flat datase...
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