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https://api.github.com/repos/huggingface/datasets/issues/5872 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5872/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5872/comments | https://api.github.com/repos/huggingface/datasets/issues/5872/events | https://github.com/huggingface/datasets/pull/5872 | 1,713,174,662 | PR_kwDODunzps5QrQ5o | 5,872 | Fix infer module for uppercase extensions | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-17T05:56:45 | 2023-05-17T14:26:59 | 2023-05-17T14:19:18 | MEMBER | null | false | {
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} | Fix the `infer_module_for_data_files` and `infer_module_for_data_files_in_archives` functions when passed a data file name with uppercase extension, e.g. `filename.TXT`.
Before, `None` module was returned. | {
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https://api.github.com/repos/huggingface/datasets/issues/5868 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5868/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5868/comments | https://api.github.com/repos/huggingface/datasets/issues/5868/events | https://github.com/huggingface/datasets/issues/5868 | 1,711,173,098 | I_kwDODunzps5l_m3q | 5,868 | Is it possible to change a cached file and 're-cache' it instead of re-generating? | {
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"Arrow files/primitives (tables and arrays) are immutable, so re-generating them is the only option, I'm afraid.",
"> \r\n\r\nGot it, thanks for your reply"
] | 2023-05-16T03:45:42 | 2023-05-17T11:21:36 | 2023-05-17T11:21:36 | NONE | null | null | null | ### Feature request
Hi,
I have a huge cached file using `map`(over 500GB), and I want to change an attribution of each element, is there possible to do it using some method instead of re-generating, because `map` takes over 24 hours
### Motivation
For large datasets, I think it is very important because we always face the problem which is changing something in the original cache without re-generating it.
### Your contribution
For now, I can't help, sorry. | {
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https://api.github.com/repos/huggingface/datasets/issues/5861 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5861/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5861/comments | https://api.github.com/repos/huggingface/datasets/issues/5861/events | https://github.com/huggingface/datasets/pull/5861 | 1,709,807,340 | PR_kwDODunzps5Qf55q | 5,861 | Better error message when combining dataset dicts instead of datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/5860 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5860/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5860/comments | https://api.github.com/repos/huggingface/datasets/issues/5860/events | https://github.com/huggingface/datasets/pull/5860 | 1,709,727,460 | PR_kwDODunzps5QfojD | 5,860 | Minor tqdm optim | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-15T09:49:37 | 2023-05-17T18:46:46 | 2023-05-17T18:39:35 | MEMBER | null | false | {
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} | Don't create a tqdm progress bar when `disable_tqdm` is passed to `map_nested`.
On my side it sped up some iterable datasets by ~30% when `map_nested` is used extensively to recursively tensorize python dicts. | {
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https://api.github.com/repos/huggingface/datasets/issues/5853 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5853/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5853/comments | https://api.github.com/repos/huggingface/datasets/issues/5853/events | https://github.com/huggingface/datasets/pull/5853 | 1,708,092,786 | PR_kwDODunzps5QaZLP | 5,853 | [docs] Redirects, migrated from nginx | {
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"@mishig25 note that it's not exactly the same behavior as in nginx as here it interacts a bit with the `version` and the `language`\r\n\r\nShould be close enough, though.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow=... | 2023-05-12T19:19:27 | 2023-05-15T10:37:19 | 2023-05-15T10:30:14 | MEMBER | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/5848 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5848/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5848/comments | https://api.github.com/repos/huggingface/datasets/issues/5848/events | https://github.com/huggingface/datasets/pull/5848 | 1,707,506,734 | PR_kwDODunzps5QYa1B | 5,848 | Add `accelerate` as metric's test dependency to fix CI error | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-12T12:01:01 | 2023-05-12T13:48:47 | 2023-05-12T13:39:06 | CONTRIBUTOR | null | false | {
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} | The `frugalscore` metric uses Transformers' Trainer, which requires `accelerate` (as of recently).
Fixes the following [CI error](https://github.com/huggingface/datasets/actions/runs/4950900048/jobs/8855148703?pr=5845). | {
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https://api.github.com/repos/huggingface/datasets/issues/5851 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5851/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5851/comments | https://api.github.com/repos/huggingface/datasets/issues/5851/events | https://github.com/huggingface/datasets/issues/5851 | 1,707,907,048 | I_kwDODunzps5lzJfo | 5,851 | Error message not clear in interleaving datasets | {
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standard env
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [X] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)
### Reproduction
I'm trying to interleave 'sciq', 'wiki' and the 'pile-enron' dataset. I think the error I made was that I loaded the train split of one, but for the other but the error is not too helpful-
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[/home/suryahari/Vornoi/save_model_ops.py](https://vscode-remote+ssh-002dremote-002bthomsonlab-002d2-002ejamesgornet-002ecom.vscode-resource.vscode-cdn.net/home/suryahari/Vornoi/save_model_ops.py) in line 3
[41](file:///home/suryahari/Vornoi/save_model_ops.py?line=40) # %%
----> [43](file:///home/suryahari/Vornoi/save_model_ops.py?line=42) dataset = interleave_datasets(datasets, stopping_strategy="all_exhausted")
File [~/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py:124](https://vscode-remote+ssh-002dremote-002bthomsonlab-002d2-002ejamesgornet-002ecom.vscode-resource.vscode-cdn.net/home/suryahari/~/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py:124), in interleave_datasets(datasets, probabilities, seed, info, split, stopping_strategy)
[122](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=121) for dataset in datasets[1:]:
[123](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=122) if (map_style and not isinstance(dataset, Dataset)) or (iterable and not isinstance(dataset, IterableDataset)):
--> [124](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=123) raise ValueError(
[125](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=124) f"Unable to interleave a {type(datasets[0])} with a {type(dataset)}. Expected a list of Dataset objects or a list of IterableDataset objects."
[126](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=125) )
[127](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=126) if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
[128](file:///home/suryahari/miniconda3/envs/vornoi/lib/python3.10/site-packages/datasets/combine.py?line=127) raise ValueError(f"{stopping_strategy} is not supported. Please enter a valid stopping_strategy.")
ValueError: Unable to interleave a with a . Expected a list of Dataset objects or a list of IterableDataset objects.
```
### Expected behavior
the error message should hopefully be more clear | {
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https://api.github.com/repos/huggingface/datasets/issues/5845 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5845/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5845/comments | https://api.github.com/repos/huggingface/datasets/issues/5845/events | https://github.com/huggingface/datasets/pull/5845 | 1,706,253,251 | PR_kwDODunzps5QUMjS | 5,845 | Add `date_format` param to the CSV reader | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-05-11T17:29:57 | 2023-05-15T07:39:13 | 2023-05-12T15:14:48 | CONTRIBUTOR | null | false | {
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"merged_at": "2023-05-12T15:14:48"
} | Adds the `date_format` param introduced in Pandas 2.0 to the CSV reader and improves its type hints. | {
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https://api.github.com/repos/huggingface/datasets/issues/5841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5841/comments | https://api.github.com/repos/huggingface/datasets/issues/5841/events | https://github.com/huggingface/datasets/issues/5841 | 1,705,286,639 | I_kwDODunzps5lpJvv | 5,841 | Abusurdly slow on iteration | {
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"Hi ! You can try to use the [Image](https://huggingface.co/docs/datasets/v2.12.0/en/package_reference/main_classes#datasets.Image) type which [decodes images on-the-fly](https://huggingface.co/docs/datasets/v2.12.0/en/about_dataset_features#image-feature) into pytorch tensors :)\r\n\r\n```python\r\nds = Dataset.fr... | 2023-05-11T08:04:09 | 2023-05-15T15:38:13 | 2023-05-15T15:38:13 | NONE | null | null | null | ### Describe the bug
I am attempting to iterate through an image dataset, but I am encountering a significant slowdown in the iteration speed. In order to investigate this issue, I conducted the following experiment:
```python
a=torch.randn(100,224)
a=torch.stack([a] * 10000)
a.shape
# %%
ds=Dataset.from_dict({"tensor":a})
for i in tqdm(ds.with_format("numpy")):
pass
for i in tqdm(ds.with_format("torch")):
pass
```
I noticed that the dataset in numpy format performs significantly faster than the one in torch format. My hypothesis is that the dataset undergoes a transformation process of torch->python->numpy(torch) in the background, which might be causing the slowdown. Is there any way to expedite the process by bypassing such transformations?
Furthermore, if I increase the size of a to an image shape, like:
```python
a=torch.randn(3,224,224)
```
the iteration speed becomes absurdly slow, around 100 iterations per second, whereas the speed with numpy format is approximately 250 iterations per second. This level of speed would be unacceptable for large image datasets, as it could take several hours just to iterate through a single epoch.
### Steps to reproduce the bug
```python
a=torch.randn(100,224)
a=torch.stack([a] * 10000)
a.shape
# %%
ds=Dataset.from_dict({"tensor":a})
for i in tqdm(ds.with_format("numpy")):
pass
for i in tqdm(ds.with_format("torch")):
pass
```
### Expected behavior
iteration faster
### Environment info
- `datasets` version: 2.11.0
- Platform: Linux-5.4.0-148-generic-x86_64-with-glibc2.10
- Python version: 3.8.16
- Huggingface_hub version: 0.13.4
- PyArrow version: 11.0.0
- Pandas version: 2.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5840/comments | https://api.github.com/repos/huggingface/datasets/issues/5840/events | https://github.com/huggingface/datasets/issues/5840 | 1,705,212,085 | I_kwDODunzps5lo3i1 | 5,840 | load model error. | {
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"Please report this in the `transformers` repo, as it's not related to `datasets`"
] | 2023-05-11T07:12:38 | 2023-05-12T13:44:07 | 2023-05-12T13:44:06 | NONE | null | null | null | ### Describe the bug
I had trained one model use deepspeed, when I load the final load I get the follow error:
OSError: Can't load tokenizer for '/XXX/DeepSpeedExamples/applications/DeepSpeed-Chat/output/step3-models/1.3b/actor'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure '/home/fm001/hzl/Project/DeepSpeedExamples/applications/DeepSpeed-Chat/output/step3-models/1.3b/actor' is the correct path to a directory containing all relevant files for a BloomTokenizerFast tokenizer.
my load code is : python chat.py --path /XXX/DeepSpeedExamples/applications/DeepSpeed-Chat/output/step3-models/1.3b/actor/
### Steps to reproduce the bug
γγγ
### Expected behavior
γγγ
### Environment info
γγγ | {
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