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https://api.github.com/repos/huggingface/datasets/issues/6322 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6322/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6322/comments | https://api.github.com/repos/huggingface/datasets/issues/6322/events | https://github.com/huggingface/datasets/pull/6322 | 1,952,947,461 | PR_kwDODunzps5dT5vG | 6,322 | Fix regex `get_data_files` formatting for base paths | {
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} | With this pr https://github.com/huggingface/datasets/pull/6309, it is formatting the entire base path into regex, which results in the undesired formatting error `doesn't match the pattern` because of the line in `glob_pattern_to_regex`: `.replace("//", "/")`:
- Input: `hf://datasets/...`
- Output: `hf:/datasets/...`
This fix will only convert the `split_pattern` to regex and keep the `base_path` unchanged.
cc @albertvillanova hopefully this still works with your implementation | {
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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... | 2023-10-19T16:24:35 | 2023-10-19T17:18:00 | 2023-10-19T17:07:35 | CONTRIBUTOR | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/6320 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6320/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6320/comments | https://api.github.com/repos/huggingface/datasets/issues/6320/events | https://github.com/huggingface/datasets/issues/6320 | 1,952,618,316 | I_kwDODunzps50YpdM | 6,320 | Dataset slice splits can't load training and validation at the same time | {
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"The expression \"train+test\" concatenates the splits.\r\n\r\nThe individual splits as separate datasets can be obtained as follows:\r\n```python\r\ntrain_ds, test_ds = load_dataset(\"<dataset_name>\", split=[\"train\", \"test\"])\r\ntrain_10pct_ds, test_10pct_ds = load_dataset(\"<dataset_name>\", split=[\"train[:... | 2023-10-19T16:09:22 | 2023-10-19T18:36:18 | null | NONE | null | null | null | ### Describe the bug
According to the [documentation](https://huggingface.co/docs/datasets/v2.14.5/loading#slice-splits) is should be possible to run the following command:
`train_test_ds = datasets.load_dataset("bookcorpus", split="train+test")`
to load the train and test sets from the dataset.
However executing the equivalent code:
`speech_commands_v1 = load_dataset("superb", "ks", split="train+test")`
only yields the following output:
> Dataset({
> features: ['file', 'audio', 'label'],
> num_rows: 54175
> })
Where loading the dataset without the split argument yields:
> DatasetDict({
> train: Dataset({
> features: ['file', 'audio', 'label'],
> num_rows: 51094
> })
> validation: Dataset({
> features: ['file', 'audio', 'label'],
> num_rows: 6798
> })
> test: Dataset({
> features: ['file', 'audio', 'label'],
> num_rows: 3081
> })
> })
Thus, the API seems to be broken in this regard.
This is a bit annoying since I want to be able to use the split argument with `split="train[:10%]+test[:10%]"` to have smaller dataset to work with when validating my model is working correctly.
### Steps to reproduce the bug
`speech_commands_v1 = load_dataset("superb", "ks", split="train+test")`
### Expected behavior
> DatasetDict({
> train: Dataset({
> features: ['file', 'audio', 'label'],
> num_rows: 51094
> })
> test: Dataset({
> features: ['file', 'audio', 'label'],
> num_rows: 3081
> })
> })
### Environment info
```
import datasets
print(datasets.__version__)
```
> 2.14.5
```
import sys
print(sys.version)
```
> 3.9.17 (main, Jul 5 2023, 20:41:20)
> [GCC 11.2.0] | {
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https://api.github.com/repos/huggingface/datasets/issues/6319 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6319/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6319/comments | https://api.github.com/repos/huggingface/datasets/issues/6319/events | https://github.com/huggingface/datasets/issues/6319 | 1,952,101,717 | I_kwDODunzps50WrVV | 6,319 | Datasets.map is severely broken | {
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"Hi! Instead of processing a single example at a time, you should use the batched `map` for the best performance (with `num_proc=1`) - the fast tokenizers can process a batch's samples in parallel in that scenario.\r\n\r\nE.g., the following code in Colab takes an hour to complete:\r\n```python\r\n# !pip install da... | 2023-10-19T12:19:33 | 2023-10-19T22:02:23 | null | NONE | null | null | null | ### Describe the bug
Regardless of how many cores I used, I have 16 or 32 threads, map slows down to a crawl at around 80% done, lingers maybe until 97% extremely slowly and NEVER finishes the job. It just hangs.
After watching this for 27 hours I control-C out of it. Until the end one process appears to be doing something, but it never ends.
I saw some comments about fast tokenizers using Rust and all and tried different variations. NOTHING works.
### Steps to reproduce the bug
Running it without breaking the dataset into parts results in the same behavior. The loop was an attempt to see if this was a RAM issue.
for idx in range(100):
dataset = load_dataset("togethercomputer/RedPajama-Data-1T-Sample", cache_dir=cache_dir, split=f'train[{idx}%:{idx+1}%]')
dataset = dataset.map(partial(tokenize_fn, tokenizer), batched=False, num_proc=1, remove_columns=["text", "meta"])
dataset.save_to_disk(training_args.cache_dir + f"/training_data_{idx}")
### Expected behavior
I expect map to run at more or less the same speed it starts with and FINISH its processing.
### Environment info
Python 3.8, same with 3.10 makes no difference.
Ubuntu 20.04, | {
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https://api.github.com/repos/huggingface/datasets/issues/6318 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6318/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6318/comments | https://api.github.com/repos/huggingface/datasets/issues/6318/events | https://github.com/huggingface/datasets/pull/6318 | 1,952,100,706 | PR_kwDODunzps5dRC9V | 6,318 | Deterministic set hash | {
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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... | 2023-10-19T12:19:13 | 2023-10-19T16:27:20 | 2023-10-19T16:16:31 | MEMBER | null | false | {
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} | Sort the items in a set according to their `datasets.fingerprint.Hasher.hash` hash to get a deterministic hash of sets.
This is useful to get deterministic hashes of tokenizers that use a trie based on python sets.
reported in https://github.com/huggingface/datasets/issues/3847 | {
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https://api.github.com/repos/huggingface/datasets/issues/6317 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6317/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6317/comments | https://api.github.com/repos/huggingface/datasets/issues/6317/events | https://github.com/huggingface/datasets/issues/6317 | 1,951,965,668 | I_kwDODunzps50WKHk | 6,317 | sentiment140 dataset unavailable | {
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"Thanks for reporting. We are investigating the issue.",
"We have opened an issue in the corresponding Hub dataset: https://huggingface.co/datasets/sentiment140/discussions/3\r\n\r\nLet's continue the discussion there."
] | 2023-10-19T11:25:21 | 2023-10-19T13:04:56 | 2023-10-19T13:04:56 | NONE | null | null | null | ### Describe the bug
loading the dataset using load_dataset("sentiment140") returns the following error
ConnectionError: Couldn't reach http://cs.stanford.edu/people/alecmgo/trainingandtestdata.zip (error 403)
### Steps to reproduce the bug
Run the following code (version should not matter).
```
from datasets import load_dataset
data = load_dataset("sentiment140")
```
### Expected behavior
The dataset should be loaded just like any other.
The main issue is that it is no longer hosted by stanford. It is still available from a [Google Drive Link](https://docs.google.com/file/d/0B04GJPshIjmPRnZManQwWEdTZjg/edit).
### Environment info
- `datasets` version: 2.14.5
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.10.8
- Huggingface_hub version: 0.17.3
- PyArrow version: 13.0.0
- Pandas version: 2.1.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6316 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6316/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6316/comments | https://api.github.com/repos/huggingface/datasets/issues/6316/events | https://github.com/huggingface/datasets/pull/6316 | 1,951,819,869 | PR_kwDODunzps5dQGpg | 6,316 | Fix loading Hub datasets with CSV metadata file | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-19T10:21:34 | 2023-10-19T16:38:48 | null | MEMBER | null | false | {
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} | Currently, the reading of the metadata file infers the file extension (.jsonl or .csv) from the passed filename. However, downloaded files from the Hub don't have file extension. For example:
- the original file: `hf://datasets/__DUMMY_TRANSFORMERS_USER__/test-dataset-5916a4-16977085077831/metadata.jsonl`
- corresponds to the downloaded path: `/tmp/pytest-of-username/pytest-46/cache/datasets/downloads/9f5374dbb470f711f6b89d66a5eec1f19cc96324b26bcbebe29138bda6cb20e6`, which does not have extension
In the case where the metadata file does not have an extension, the reader assumes it is a JSONL file, thus the reported error when trying to read a CSV file as a JSONL one: `ArrowInvalid: JSON parse error: Invalid value. in row 0`
This behavior was introduced by:
- #4837
This PR extracts the metadata file extension from the original filename (instead of the downloaded one) and passes it as a parameter to the read_metadata function.
Fix #6315. | {
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https://api.github.com/repos/huggingface/datasets/issues/6315 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6315/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6315/comments | https://api.github.com/repos/huggingface/datasets/issues/6315/events | https://github.com/huggingface/datasets/issues/6315 | 1,951,800,819 | I_kwDODunzps50Vh3z | 6,315 | Hub datasets with CSV metadata raise ArrowInvalid: JSON parse error: Invalid value. in row 0 | {
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"followers_... | null | [] | 2023-10-19T10:11:29 | 2023-10-19T10:11:29 | null | MEMBER | null | null | null | When trying to load a Hub dataset that contains a CSV metadata file, it raises an `ArrowInvalid` error:
```
E pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0
pyarrow/error.pxi:100: ArrowInvalid
```
See: https://huggingface.co/datasets/lukarape/public_small_papers/discussions/1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6314 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6314/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6314/comments | https://api.github.com/repos/huggingface/datasets/issues/6314/events | https://github.com/huggingface/datasets/pull/6314 | 1,951,684,763 | PR_kwDODunzps5dPo25 | 6,314 | Support creating new branch in push_to_hub | {
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https://api.github.com/repos/huggingface/datasets/issues/6313 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6313/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6313/comments | https://api.github.com/repos/huggingface/datasets/issues/6313/events | https://github.com/huggingface/datasets/pull/6313 | 1,951,527,712 | PR_kwDODunzps5dPGmL | 6,313 | Fix commit message formatting in multi-commit uploads | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6313). All of your documentation changes will be reflected on that endpoint."
] | 2023-10-19T07:53:56 | 2023-10-19T17:34:34 | null | CONTRIBUTOR | null | false | {
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} | Currently, the commit message keeps on adding:
- `Upload dataset (part 00000-of-00002)`
- `Upload dataset (part 00000-of-00002) (part 00001-of-00002)`
Introduced in https://github.com/huggingface/datasets/pull/6269
This PR fixes this issue to have
- `Upload dataset (part 00000-of-00002)`
- `Upload dataset (part 00001-of-00002)` | {
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https://api.github.com/repos/huggingface/datasets/issues/6312 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6312/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6312/comments | https://api.github.com/repos/huggingface/datasets/issues/6312/events | https://github.com/huggingface/datasets/pull/6312 | 1,950,128,416 | PR_kwDODunzps5dKWDF | 6,312 | docs: resolving namespace conflict, refactored variable | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-18T16:10:59 | 2023-10-19T16:31:59 | 2023-10-19T16:23:07 | CONTRIBUTOR | null | false | {
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} | In docs of about_arrow.md, in the below example code
The variable name 'time' was being used in a way that could potentially lead to a namespace conflict with Python's built-in 'time' module. It is not a good convention and can lead to unintended variable shadowing for any user re-using the example code.
To ensure code clarity, and prevent potential naming conflicts renamed the variable 'time' to 'elapsed_time' in the example code. | {
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https://api.github.com/repos/huggingface/datasets/issues/6311 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6311/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6311/comments | https://api.github.com/repos/huggingface/datasets/issues/6311/events | https://github.com/huggingface/datasets/issues/6311 | 1,949,304,993 | I_kwDODunzps50MAih | 6,311 | cast_column to Sequence with length=4 occur exception raise in datasets/table.py:2146 | {
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"Thanks for reporting! We've spotted the bugs with the `array.values` handling and are fixing them in https://github.com/huggingface/datasets/pull/6283 (should be part of the next release)."
] | 2023-10-18T09:38:05 | 2023-10-18T17:28:36 | null | NONE | null | null | null | ### Describe the bug
i load a dataset from local csv file which has 187383612 examples, then use `map` to generate new columns for test.
here is my code :
```
import os
from datasets import load_dataset
from datasets.features import Sequence, Value
def add_new_path(example):
example["ais_bbox"] = [100,100,200,200]
example["ais_image_path"] = os.path.join("images", example["image_path"]) if example["image_path"] else ""
return example
ais_dataset = load_dataset("/data/ryan.gao/ais_dataset_cache/raw/1749/")
hf_ds = ais_dataset.map(add_new_path, batched=False, num_proc=32)
ds = hf_ds.cast_column("ais_bbox", Sequence(Value("int32"), length=4))
```
and the `cast_column` raise an exception
```
Casting the dataset: 3%|███▉
...
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2110, in cast_column
return self.cast(features)
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2055, in cast
dataset = dataset.map(
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 592, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 557, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3097, in map
for rank, done, content in Dataset._map_single(**dataset_kwargs):
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3474, in _map_single
batch = apply_function_on_filtered_inputs(
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3353, in apply_function_on_filtered_inputs
processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 2329, in table_cast
return cast_table_to_schema(table, schema)
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 2288, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 2288, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 1831, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 1831, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 2145, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
TypeError: Couldn't cast array of type
list<item: int64>
to
Sequence(feature=Value(dtype='int32', id=None), length=4, id=None)
```
i check the source code and make debug info:
in datasets/table.py:2092
```
2091 if feature.length > -1:
2092 if feature.length * len(array) == len(array.values):
2093 return pa.FixedSizeListArray.from_arrays(_c(array.values, feature.feature), feature.length)
2094 print(len(array))
2095 print(len(array.values))
```
my feature.length is 4. but feature.length * len(array) == len(array.values) is false.
print(len(array)) is 262
print(len(array.values)) is 4000
then I use "for item in array" to print each item then get 262 * [100,100,200,200]
and use "for item in array.values" to print each item and get 4000 int32 which are 1000 * [100,100,200,200]
i'm wondering the `chunk` in each `array.chunks`, the "chunk.values" may get all the chunks's value rather than single chunk? but i check the pyarrow's doc seems chunk.values is chunk's value not all.
### Steps to reproduce the bug
code provided above.
### Expected behavior
feature.length * len(array) == len(array.values) should be true. and there should not has Exception.
### Environment info
python3.9
x86_64
datasets: 2.14.4
pyarrow: 13.0.0 or 10.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6310 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6310/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6310/comments | https://api.github.com/repos/huggingface/datasets/issues/6310/events | https://github.com/huggingface/datasets/pull/6310 | 1,947,457,988 | PR_kwDODunzps5dBPnY | 6,310 | Add return_file_name in load_dataset | {
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} | Proposition to fix #5806.
Added an optional parameter `return_file_name` in the dataset builder config. When set to `True`, the function will include the file name corresponding to the sample in the returned output.
There is a difference between arrow-based and folder-based datasets to return the file name:
- for arrow-based: a column is concatenated after the table is cast.
- for folder-based: `dataset.info.features` has the entry `file_name` and the original file name is passed to the `sample_metadata` dictionary.
The difference in behavior might be a concern, also I do not know whether the `file_name` should return the original file path or the downloaded one for folder-based datasets.
I added some tests for the datasets that already had a test file. | {
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https://api.github.com/repos/huggingface/datasets/issues/6309 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6309/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6309/comments | https://api.github.com/repos/huggingface/datasets/issues/6309/events | https://github.com/huggingface/datasets/pull/6309 | 1,946,916,969 | PR_kwDODunzps5c_YcX | 6,309 | Fix get_data_patterns for directories with the word data twice | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-17T09:00:39 | 2023-10-18T14:01:52 | 2023-10-18T13:50:35 | MEMBER | null | false | {
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} | Before the fix, `get_data_patterns` inferred wrongly the split name for paths with the word "data" twice:
- For the URL path: `hf://datasets/piuba-bigdata/articles_and_comments@f328d536425ae8fcac5d098c8408f437bffdd357/data/train-00001-of-00009.parquet` (note the org name `piuba-bigdata/` ending with `data/`)
- The inferred split name was: `articles_and_comments@f328d536425ae8fcac5d098c8408f437bffdd357/data/train` instead of `train`
This PR fixes this issue by passing the `base_path` (`hf://datasets/piuba-bigdata/articles_and_comments@f328d536425ae8fcac5d098c8408f437bffdd357`) to `_get_data_files_patterns` and prepending it to the regex split pattern (`data/{split}-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*\\..*`).
Fix #6305.
Fix https://huggingface.co/datasets/piuba-bigdata/articles_and_comments/discussions/1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6308 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6308/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6308/comments | https://api.github.com/repos/huggingface/datasets/issues/6308/events | https://github.com/huggingface/datasets/issues/6308 | 1,946,810,625 | I_kwDODunzps50CfkB | 6,308 | module 'resource' has no attribute 'error' | {
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"This (Windows) issue was fixed in `fsspec` in https://github.com/fsspec/filesystem_spec/pull/1275. So, to avoid the error, update the `fsspec` installation with `pip install -U fsspec`.",
"> This (Windows) issue was fixed in `fsspec` in [fsspec/filesystem_spec#1275](https://github.com/fsspec/filesystem_spec/pul... | 2023-10-17T08:08:54 | 2023-10-18T12:48:37 | null | NONE | null | null | null | ### Describe the bug
just run import:
`from datasets import load_dataset`
and then:
```
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\__init__.py", line 22, in <module>
from .arrow_dataset import Dataset
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\arrow_dataset.py", line 66, in <module>
from .arrow_reader import ArrowReader
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\arrow_reader.py", line 30, in <module>
from .download.download_config import DownloadConfig
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\download\__init__.py", line 10, in <module>
from .streaming_download_manager import StreamingDownloadManager
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\download\streaming_download_manager.py", line 21, in <module>
from ..filesystems import COMPRESSION_FILESYSTEMS
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\datasets\filesystems\__init__.py", line 8, in <module>
import fsspec.asyn
File "C:\ProgramData\anaconda3\envs\py310\lib\site-packages\fsspec\asyn.py", line 157, in <module>
ResourceEror = resource.error
AttributeError: module 'resource' has no attribute 'error'
Process finished with exit code 1
```
and the error codes are:
```
try:
import resource
except ImportError:
resource = None
ResourceError = OSError
else:
ResourceEror = resource.error
```
1. miss spelling : "ResourceEror " should be "ResourceErorr"
2. module 'resource' has no attribute 'error'
### Steps to reproduce the bug
only one step:
`from datasets import load_dataset`
### Expected behavior
slove error: module 'resource' has no attribute 'error'
### Environment info
python=3.10
datasets==2.14.5
| {
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https://api.github.com/repos/huggingface/datasets/issues/6307 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6307/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6307/comments | https://api.github.com/repos/huggingface/datasets/issues/6307/events | https://github.com/huggingface/datasets/pull/6307 | 1,946,414,808 | PR_kwDODunzps5c9s0j | 6,307 | Fix typo in code example in docs | {
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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... | 2023-10-17T02:28:50 | 2023-10-17T12:59:26 | 2023-10-17T06:36:19 | CONTRIBUTOR | null | false | {
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"merged_at": "2023-10-17T06:36:18"
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