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https://api.github.com/repos/huggingface/datasets/issues/2923 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2923/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2923/comments | https://api.github.com/repos/huggingface/datasets/issues/2923/events | https://github.com/huggingface/datasets/issues/2923 | 997,351,590 | I_kwDODunzps47cmCm | 2,923 | Loading an autonlp dataset raises in normal mode but not in streaming mode | {
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"Closing since autonlp dataset are now supported"
] | 1,631,727,878,000 | 1,649,758,180,000 | 1,649,758,179,000 | CONTRIBUTOR | null | ## Describe the bug
The same dataset (from autonlp) raises an error in normal mode, but does not raise in streaming mode
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("severo/autonlp-data-sentiment_detection-3c8bcd36", split="train", streaming=False)
## raises an error
load_dataset("severo/autonlp-data-sentiment_detection-3c8bcd36", split="train", streaming=True)
## does not raise an error
```
## Expected results
Both calls should raise the same error
## Actual results
Call with streaming=False:
```
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 5825.42it/s]
Using custom data configuration autonlp-data-sentiment_detection-3c8bcd36-fe30267462d1d42b
Downloading and preparing dataset json/autonlp-data-sentiment_detection-3c8bcd36 to /home/slesage/.cache/huggingface/datasets/json/autonlp-data-sentiment_detection-3c8bcd36-fe30267462d1d42b/0.0.0/d75ead8d5cfcbe67495df0f89bd262f0023257fbbbd94a730313295f3d756d50...
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:00<00:00, 15923.71it/s]
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:00<00:00, 3346.88it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 726, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 1187, in _prepare_split
writer.write_table(table)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/arrow_writer.py", line 418, in write_table
pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/arrow_writer.py", line 418, in <listcomp>
pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
File "pyarrow/table.pxi", line 1249, in pyarrow.lib.Table.__getitem__
File "pyarrow/table.pxi", line 1825, in pyarrow.lib.Table.column
File "pyarrow/table.pxi", line 1800, in pyarrow.lib.Table._ensure_integer_index
KeyError: 'Field "splits" does not exist in table schema'
```
Call with `streaming=False`:
```
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 6000.43it/s]
Using custom data configuration autonlp-data-sentiment_detection-3c8bcd36-fe30267462d1d42b
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:00<00:00, 46916.15it/s]
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 5/5 [00:00<00:00, 148734.18it/s]
```
## Environment info
- `datasets` version: 1.12.1.dev0
- Platform: Linux-5.11.0-1017-aws-x86_64-with-glibc2.29
- Python version: 3.8.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/2922 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2922/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2922/comments | https://api.github.com/repos/huggingface/datasets/issues/2922/events | https://github.com/huggingface/datasets/pull/2922 | 997,332,662 | PR_kwDODunzps4ry6-s | 2,922 | Fix conversion of multidim arrays in list to arrow | {
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} | [] | closed | false | null | [] | null | [] | 1,631,726,496,000 | 1,631,726,572,000 | 1,631,726,505,000 | MEMBER | null | Arrow only supports 1-dim arrays. Previously we were converting all the numpy arrays to python list before instantiating arrow arrays to workaround this limitation.
However in #2361 we started to keep numpy arrays in order to keep their dtypes.
It works when we pass any multi-dim numpy array (the conversion to arrow has been added on our side), but not for lists of multi-dim numpy arrays.
In this PR I added two strategies:
- one that takes a list of multi-dim numpy arrays on returns an arrow array in an optimized way (more common case)
- one that takes a list of possibly very nested data (lists, dicts, tuples) containing multi-dim arrays. This one is less optimized since it converts all the multi-dim numpy arrays into lists of 1-d arrays for compatibility with arrow. This strategy is simpler that just trying to create the arrow array from a possibly very nested data structure, but in the future we can improve it if needed.
Fix https://github.com/huggingface/datasets/issues/2921 | {
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https://api.github.com/repos/huggingface/datasets/issues/2921 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2921/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2921/comments | https://api.github.com/repos/huggingface/datasets/issues/2921/events | https://github.com/huggingface/datasets/issues/2921 | 997,325,424 | I_kwDODunzps47cfpw | 2,921 | Using a list of multi-dim numpy arrays raises an error "can only convert 1-dimensional array values" | {
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} | [] | closed | false | null | [] | null | [] | 1,631,725,931,000 | 1,631,726,505,000 | 1,631,726,505,000 | MEMBER | null | This error has been introduced in https://github.com/huggingface/datasets/pull/2361
To reproduce:
```python
import numpy as np
from datasets import Dataset
d = Dataset.from_dict({"a": [np.zeros((2, 2))]})
```
raises
```python
Traceback (most recent call last):
File "playground/ttest.py", line 5, in <module>
d = Dataset.from_dict({"a": [np.zeros((2, 2))]}).with_format("torch")
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_dataset.py", line 458, in from_dict
pa_table = InMemoryTable.from_pydict(mapping=mapping)
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 365, in from_pydict
return cls(pa.Table.from_pydict(*args, **kwargs))
File "pyarrow/table.pxi", line 1639, in pyarrow.lib.Table.from_pydict
File "pyarrow/array.pxi", line 332, in pyarrow.lib.asarray
File "pyarrow/array.pxi", line 223, in pyarrow.lib.array
File "pyarrow/array.pxi", line 110, in pyarrow.lib._handle_arrow_array_protocol
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_writer.py", line 107, in __arrow_array__
out = pa.array(self.data, type=type)
File "pyarrow/array.pxi", line 306, in pyarrow.lib.array
File "pyarrow/array.pxi", line 39, in pyarrow.lib._sequence_to_array
File "pyarrow/error.pxi", line 143, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 99, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Can only convert 1-dimensional array values | {
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Fix #2919 | {
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"doing a patch release now :)"
] | 1,631,714,710,000 | 1,631,726,509,000 | 1,631,726,303,000 | MEMBER | null | When accessing examples from a dataset formatted for pytorch, some progress bars appear when accessing examples:
```python
In [1]: import datasets as ds
In [2]: d = ds.Dataset.from_dict({"a": [0, 1, 2]}).with_format("torch")
In [3]: d[0]
100%|ββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 3172.70it/s]
Out[3]: {'a': tensor(0)}
```
This is because the pytorch formatter calls `map_nested` that uses progress bars
cc @sgugger | {
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https://api.github.com/repos/huggingface/datasets/issues/2918 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2918/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2918/comments | https://api.github.com/repos/huggingface/datasets/issues/2918/events | https://github.com/huggingface/datasets/issues/2918 | 997,063,347 | I_kwDODunzps47bfqz | 2,918 | `Can not decode content-encoding: gzip` when loading `scitldr` dataset with streaming | {
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"Hi @SBrandeis, thanks for reporting! ^^\r\n\r\nI think this is an issue with `fsspec`: https://github.com/intake/filesystem_spec/issues/389\r\n\r\nI will ask them if they are planning to fix it...",
"Code to reproduce the bug: `ClientPayloadError: 400, message='Can not decode content-encoding: gzip'`\r\n```python\r\nIn [1]: import fsspec\r\n\r\nIn [2]: import json\r\n\r\nIn [3]: with fsspec.open('https://raw.githubusercontent.com/allenai/scitldr/master/SciTLDR-Data/SciTLDR-FullText/test.jsonl', encoding=\"utf-8\") as f:\r\n ...: for row in f:\r\n ...: data = json.loads(row)\r\n ...:\r\n---------------------------------------------------------------------------\r\nClientPayloadError Traceback (most recent call last)\r\n```",
"Thanks for investigating @albertvillanova ! π€ "
] | 1,631,711,167,000 | 1,638,346,500,000 | 1,638,346,500,000 | CONTRIBUTOR | null | ## Describe the bug
Trying to load the `"FullText"` config of the `"scitldr"` dataset with `streaming=True` raises an error from `aiohttp`:
```python
ClientPayloadError: 400, message='Can not decode content-encoding: gzip'
```
cc @lhoestq
## Steps to reproduce the bug
```python
from datasets import load_dataset
iter_dset = iter(
load_dataset("scitldr", name="FullText", split="test", streaming=True)
)
next(iter_dset)
```
## Expected results
Returns the first sample of the dataset
## Actual results
Calling `__next__` crashes with the following Traceback:
```python
----> 1 next(dset_iter)
~\miniconda3\envs\datasets\lib\site-packages\datasets\iterable_dataset.py in __iter__(self)
339
340 def __iter__(self):
--> 341 for key, example in self._iter():
342 if self.features:
343 # we encode the example for ClassLabel feature types for example
~\miniconda3\envs\datasets\lib\site-packages\datasets\iterable_dataset.py in _iter(self)
336 else:
337 ex_iterable = self._ex_iterable
--> 338 yield from ex_iterable
339
340 def __iter__(self):
~\miniconda3\envs\datasets\lib\site-packages\datasets\iterable_dataset.py in __iter__(self)
76
77 def __iter__(self):
---> 78 for key, example in self.generate_examples_fn(**self.kwargs):
79 yield key, example
80
~\.cache\huggingface\modules\datasets_modules\datasets\scitldr\72d6e2195786c57e1d343066fb2cc4f93ea39c5e381e53e6ae7c44bbfd1f05ef\scitldr.py in _generate_examples(self, filepath, split)
162
163 with open(filepath, encoding="utf-8") as f:
--> 164 for id_, row in enumerate(f):
165 data = json.loads(row)
166 if self.config.name == "AIC":
~\miniconda3\envs\datasets\lib\site-packages\fsspec\implementations\http.py in read(self, length)
496 else:
497 length = min(self.size - self.loc, length)
--> 498 return super().read(length)
499
500 async def async_fetch_all(self):
~\miniconda3\envs\datasets\lib\site-packages\fsspec\spec.py in read(self, length)
1481 # don't even bother calling fetch
1482 return b""
-> 1483 out = self.cache._fetch(self.loc, self.loc + length)
1484 self.loc += len(out)
1485 return out
~\miniconda3\envs\datasets\lib\site-packages\fsspec\caching.py in _fetch(self, start, end)
378 elif start < self.start:
379 if self.end - end > self.blocksize:
--> 380 self.cache = self.fetcher(start, bend)
381 self.start = start
382 else:
~\miniconda3\envs\datasets\lib\site-packages\fsspec\asyn.py in wrapper(*args, **kwargs)
86 def wrapper(*args, **kwargs):
87 self = obj or args[0]
---> 88 return sync(self.loop, func, *args, **kwargs)
89
90 return wrapper
~\miniconda3\envs\datasets\lib\site-packages\fsspec\asyn.py in sync(loop, func, timeout, *args, **kwargs)
67 raise FSTimeoutError
68 if isinstance(result[0], BaseException):
---> 69 raise result[0]
70 return result[0]
71
~\miniconda3\envs\datasets\lib\site-packages\fsspec\asyn.py in _runner(event, coro, result, timeout)
23 coro = asyncio.wait_for(coro, timeout=timeout)
24 try:
---> 25 result[0] = await coro
26 except Exception as ex:
27 result[0] = ex
~\miniconda3\envs\datasets\lib\site-packages\fsspec\implementations\http.py in async_fetch_range(self, start, end)
538 if r.status == 206:
539 # partial content, as expected
--> 540 out = await r.read()
541 elif "Content-Length" in r.headers:
542 cl = int(r.headers["Content-Length"])
~\miniconda3\envs\datasets\lib\site-packages\aiohttp\client_reqrep.py in read(self)
1030 if self._body is None:
1031 try:
-> 1032 self._body = await self.content.read()
1033 for trace in self._traces:
1034 await trace.send_response_chunk_received(
~\miniconda3\envs\datasets\lib\site-packages\aiohttp\streams.py in read(self, n)
342 async def read(self, n: int = -1) -> bytes:
343 if self._exception is not None:
--> 344 raise self._exception
345
346 # migration problem; with DataQueue you have to catch
ClientPayloadError: 400, message='Can not decode content-encoding: gzip'
```
## Environment info
- `datasets` version: 1.12.0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.5
- PyArrow version: 2.0.0
- aiohttp version: 3.7.4.post0
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https://api.github.com/repos/huggingface/datasets/issues/2917 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2917/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2917/comments | https://api.github.com/repos/huggingface/datasets/issues/2917/events | https://github.com/huggingface/datasets/issues/2917 | 997,041,658 | I_kwDODunzps47baX6 | 2,917 | windows download abnormal | {
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"Hi ! Is there some kind of proxy that is configured in your browser that gives you access to internet ? If it's the case it could explain why it doesn't work in the code, since the proxy wouldn't be used",
"It is indeed an agency problem, thank you very, very much",
"Let me know if you have other questions :)\r\n\r\nClosing this issue now"
] | 1,631,709,935,000 | 1,631,812,668,000 | 1,631,812,668,000 | NONE | null | ## Describe the bug
The script clearly exists (accessible from the browser), but the script download fails on windows. Then I tried it again and it can be downloaded normally on linux. why??
## Steps to reproduce the bug
```python3.7 + windows
![image](https://user-images.githubusercontent.com/52347799/133436174-4303f847-55d5-434f-a749-08da3bb9b654.png)
# Sample code to reproduce the bug
```
## Expected results
It can be downloaded normally.
## Actual results
it cann't
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:1.11.0
- Platform:windows
- Python version:3.7
- PyArrow version:
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https://api.github.com/repos/huggingface/datasets/issues/2916 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2916/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2916/comments | https://api.github.com/repos/huggingface/datasets/issues/2916/events | https://github.com/huggingface/datasets/pull/2916 | 997,003,661 | PR_kwDODunzps4rx5ua | 2,916 | Add OpenAI's pass@k code evaluation metric | {
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"> The implementation makes heavy use of multiprocessing which this PR does not touch. Is this conflicting with multiprocessing natively integrated in datasets?\r\n\r\nIt should work normally, but feel free to test it.\r\nThere is some documentation about using metrics in a distributed setup that uses multiprocessing [here](https://huggingface.co/docs/datasets/loading.html?highlight=rank#distributed-setup)\r\nYou can test to spawn several processes where each process would load the metric. Then in each process you add some references/predictions to the metric. Finally you call compute() in each process and on process 0 it should return the result on all the references/predictions\r\n\r\nLet me know if you have questions or if I can help",
"Is there a good way to debug the Windows tests? I suspect it is an issue with `multiprocessing`, but I can't see the error messages.",
"Indeed it has an issue on windows.\r\nIn your example it's supposed to output\r\n```python\r\n{'pass@1': 0.5, 'pass@2': 1.0}\r\n```\r\nbut it gets\r\n```python\r\n{'pass@1': 0.0, 'pass@2': 0.0}\r\n```\r\n\r\nI'm not on my windows machine today so I can't take a look at it. I can dive into it early next week if you want",
"> I'm not on my windows machine today so I can't take a look at it. I can dive into it early next week if you want\r\n\r\nThat would be great - unfortunately I have no access to a windows machine at the moment. I am quite sure it is an issue with in exectue.py because of multiprocessing.\r\n"
] | 1,631,707,543,000 | 1,636,726,791,000 | 1,636,726,790,000 | MEMBER | null | This PR introduces the `code_eval` metric which implements [OpenAI's code evaluation harness](https://github.com/openai/human-eval) introduced in the [Codex paper](https://arxiv.org/abs/2107.03374). It is heavily based on the original implementation and just adapts the interface to follow the `predictions`/`references` convention.
The addition of this metric should enable the evaluation against the code evaluation datasets added in #2897 and #2893.
A few open questions:
- The implementation makes heavy use of multiprocessing which this PR does not touch. Is this conflicting with multiprocessing natively integrated in `datasets`?
- This metric executes generated Python code and as such it poses dangers of executing malicious code. OpenAI addresses this issue by 1) commenting the `exec` call in the code so the user has to actively uncomment it and read the warning and 2) suggests using a sandbox environment (gVisor container). Should we add a similar safeguard? E.g. a prompt that needs to be answered when initialising the metric? Or at least a warning message?
- Naming: the implementation sticks to the `predictions`/`references` naming, however, the references are not reference solutions but unittest to test the solution. While reference solutions are also available they are not used. Should the naming be adapted? | {
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https://api.github.com/repos/huggingface/datasets/issues/2915 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2915/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2915/comments | https://api.github.com/repos/huggingface/datasets/issues/2915/events | https://github.com/huggingface/datasets/pull/2915 | 996,870,071 | PR_kwDODunzps4rxfWb | 2,915 | Fix fsspec AbstractFileSystem access | {
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https://api.github.com/repos/huggingface/datasets/issues/2914 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2914/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2914/comments | https://api.github.com/repos/huggingface/datasets/issues/2914/events | https://github.com/huggingface/datasets/issues/2914 | 996,770,168 | I_kwDODunzps47aYF4 | 2,914 | Having a dependency defining fsspec entrypoint raises an AttributeError when importing datasets | {
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"Closed by #2915."
] | 1,631,692,446,000 | 1,631,724,557,000 | 1,631,724,556,000 | CONTRIBUTOR | null | ## Describe the bug
In one of my project, I defined a custom fsspec filesystem with an entrypoint.
My guess is that by doing so, a variable named `spec` is created in the module `fsspec` (created by entering a for loop as there are entrypoints defined, see the loop in question [here](https://github.com/intake/filesystem_spec/blob/0589358d8a029ed6b60d031018f52be2eb721291/fsspec/__init__.py#L55)).
So that `fsspec.spec`, that was previously referring to the `spec` submodule, is now referring to that `spec` variable.
This make the import of datasets failing as it is using that `fsspec.spec`.
## Steps to reproduce the bug
I could reproduce the bug with a dummy poetry project.
Here is the pyproject.toml:
```toml
[tool.poetry]
name = "debug-datasets"
version = "0.1.0"
description = ""
authors = ["Pierre Godard"]
[tool.poetry.dependencies]
python = "^3.8"
datasets = "^1.11.0"
[tool.poetry.dev-dependencies]
[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"
[tool.poetry.plugins."fsspec.specs"]
"file2" = "fsspec.implementations.local.LocalFileSystem"
```
The only other file being a `debug_datasets/__init__.py` empty file.
The overall structure of the project is as follows:
```
.
βββ pyproject.toml
βββ debug_datasets
βββ __init__.py
```
Then, within the project folder run:
```
poetry install
poetry run python
```
And in the python interpreter, try to import `datasets`:
```
import datasets
```
## Expected results
The import should run successfully.
## Actual results
Here is the trace of the error I get:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/godarpi/.cache/pypoetry/virtualenvs/debug-datasets-JuFzTKL--py3.8/lib/python3.8/site-packages/datasets/__init__.py", line 33, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/home/godarpi/.cache/pypoetry/virtualenvs/debug-datasets-JuFzTKL--py3.8/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 48, in <module>
from .filesystems import extract_path_from_uri, is_remote_filesystem
File "/home/godarpi/.cache/pypoetry/virtualenvs/debug-datasets-JuFzTKL--py3.8/lib/python3.8/site-packages/datasets/filesystems/__init__.py", line 30, in <module>
def is_remote_filesystem(fs: fsspec.spec.AbstractFileSystem) -> bool:
AttributeError: 'EntryPoint' object has no attribute 'AbstractFileSystem'
```
## Suggested fix
`datasets/filesystems/__init__.py`, line 30, replace:
```
def is_remote_filesystem(fs: fsspec.spec.AbstractFileSystem) -> bool:
```
by:
```
def is_remote_filesystem(fs: fsspec.AbstractFileSystem) -> bool:
```
I will come up with a PR soon if this effectively solves the issue.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: WSL2 (Ubuntu 20.04.1 LTS)
- Python version: 3.8.5
- PyArrow version: 5.0.0
- `fsspec` version: 2021.8.1
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https://api.github.com/repos/huggingface/datasets/issues/2913 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2913/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2913/comments | https://api.github.com/repos/huggingface/datasets/issues/2913/events | https://github.com/huggingface/datasets/issues/2913 | 996,436,368 | I_kwDODunzps47ZGmQ | 2,913 | timit_asr dataset only includes one text phrase | {
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"Hi @margotwagner, \r\nThis bug was fixed in #1995. Upgrading the datasets should work (min v1.8.0 ideally)",
"Hi @margotwagner,\r\n\r\nYes, as @bhavitvyamalik has commented, this bug was fixed in `datasets` version 1.5.0. You need to update it, as your current version is 1.4.1:\r\n> Environment info\r\n> - `datasets` version: 1.4.1"
] | 1,631,653,567,000 | 1,631,693,119,000 | 1,631,693,118,000 | NONE | null | ## Describe the bug
The dataset 'timit_asr' only includes one text phrase. It only includes the transcription "Would such an act of refusal be useful?" multiple times rather than different phrases.
## Steps to reproduce the bug
Note: I am following the tutorial https://huggingface.co/blog/fine-tune-wav2vec2-english
1. Install the dataset and other packages
```python
!pip install datasets>=1.5.0
!pip install transformers==4.4.0
!pip install soundfile
!pip install jiwer
```
2. Load the dataset
```python
from datasets import load_dataset, load_metric
timit = load_dataset("timit_asr")
```
3. Remove columns that we don't want
```python
timit = timit.remove_columns(["phonetic_detail", "word_detail", "dialect_region", "id", "sentence_type", "speaker_id"])
```
4. Write a short function to display some random samples of the dataset.
```python
from datasets import ClassLabel
import random
import pandas as pd
from IPython.display import display, HTML
def show_random_elements(dataset, num_examples=10):
assert num_examples <= len(dataset), "Can't pick more elements than there are in the dataset."
picks = []
for _ in range(num_examples):
pick = random.randint(0, len(dataset)-1)
while pick in picks:
pick = random.randint(0, len(dataset)-1)
picks.append(pick)
df = pd.DataFrame(dataset[picks])
display(HTML(df.to_html()))
show_random_elements(timit["train"].remove_columns(["file"]))
```
## Expected results
10 random different transcription phrases.
## Actual results
10 of the same transcription phrase "Would such an act of refusal be useful?"
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.4.1
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.5
- PyArrow version: not listed
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https://api.github.com/repos/huggingface/datasets/issues/2912 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2912/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2912/comments | https://api.github.com/repos/huggingface/datasets/issues/2912/events | https://github.com/huggingface/datasets/pull/2912 | 996,256,005 | PR_kwDODunzps4rvhgp | 2,912 | Update link to Blog in docs footer | {
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https://api.github.com/repos/huggingface/datasets/issues/2911 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2911/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2911/comments | https://api.github.com/repos/huggingface/datasets/issues/2911/events | https://github.com/huggingface/datasets/pull/2911 | 996,202,598 | PR_kwDODunzps4rvW7Y | 2,911 | Fix exception chaining | {
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https://api.github.com/repos/huggingface/datasets/issues/2910 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2910/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2910/comments | https://api.github.com/repos/huggingface/datasets/issues/2910/events | https://github.com/huggingface/datasets/pull/2910 | 996,149,632 | PR_kwDODunzps4rvL9N | 2,910 | feat: πΈ pass additional arguments to get private configs + info | {
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] | 1,631,633,059,000 | 1,631,722,749,000 | 1,631,722,746,000 | CONTRIBUTOR | null | `use_auth_token` can now be passed to the functions to get the configs
or infos of private datasets on the hub | {
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} | [] | closed | false | null | [] | null | [] | 1,631,625,035,000 | 1,634,124,469,000 | 1,634,124,469,000 | CONTRIBUTOR | null | I can't run the tests for dummy data, facing this error
`ImportError while loading conftest '/home/zaid/tmp/fix_anli_splits/datasets/tests/conftest.py'.
tests/conftest.py:10: in <module>
from datasets import config
E ImportError: cannot import name 'config' from 'datasets' (unknown location)` | {
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https://api.github.com/repos/huggingface/datasets/issues/2908 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2908/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2908/comments | https://api.github.com/repos/huggingface/datasets/issues/2908/events | https://github.com/huggingface/datasets/pull/2908 | 995,970,612 | PR_kwDODunzps4rumwW | 2,908 | Update Zenodo metadata with creator names and affiliation | {
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https://api.github.com/repos/huggingface/datasets/issues/2907 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2907/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2907/comments | https://api.github.com/repos/huggingface/datasets/issues/2907/events | https://github.com/huggingface/datasets/pull/2907 | 995,968,152 | PR_kwDODunzps4rumOy | 2,907 | add story_cloze dataset | {
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"Will create a new one, this one seems to be missed up. "
] | 1,631,623,013,000 | 1,633,729,302,000 | 1,633,729,301,000 | CONTRIBUTOR | null | @lhoestq I have spent some time but I still I can't succeed in correctly testing the dummy_data. | {
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https://api.github.com/repos/huggingface/datasets/issues/2906 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2906/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2906/comments | https://api.github.com/repos/huggingface/datasets/issues/2906/events | https://github.com/huggingface/datasets/pull/2906 | 995,962,905 | PR_kwDODunzps4rulH- | 2,906 | feat: πΈ add a function to get a dataset config's split names | {
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"> Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos)\r\n\r\nYes totally :) This tutorial should indeed mention this, given how fundamental it is"
] | 1,631,622,682,000 | 1,633,341,338,000 | 1,633,341,337,000 | CONTRIBUTOR | null | Also: pass additional arguments (use_auth_token) to get private configs + info of private datasets on the hub
Questions:
- [x] I'm not sure how the versions work: I changed 1.12.1.dev0 to 1.12.1.dev1, was it correct?
-> no: reverted
- [x] Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos)
-> yes: added | {
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https://api.github.com/repos/huggingface/datasets/issues/2905 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2905/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2905/comments | https://api.github.com/repos/huggingface/datasets/issues/2905/events | https://github.com/huggingface/datasets/pull/2905 | 995,843,964 | PR_kwDODunzps4ruL5X | 2,905 | Update BibTeX entry | {
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https://api.github.com/repos/huggingface/datasets/issues/2904 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2904/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2904/comments | https://api.github.com/repos/huggingface/datasets/issues/2904/events | https://github.com/huggingface/datasets/issues/2904 | 995,814,222 | I_kwDODunzps47WutO | 2,904 | FORCE_REDOWNLOAD does not work | {
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"Hi ! Thanks for reporting. The error seems to happen only if you use compressed files.\r\n\r\nThe second dataset is prepared in another dataset cache directory than the first - which is normal, since the source file is different. However, it doesn't uncompress the new data file because it finds the old uncompressed data in the extraction cache directory.\r\n\r\nIf we fix the extraction cache mechanism to uncompress a local file if it changed then it should fix the issue.\r\nCurrently the extraction cache mechanism only takes into account the path of the compressed file, which is an issue.",
"Facing the same issue, is there any way to overtake this issue until it will be fixed? ",
"You can clear your extraction cache in the meantime (by default at `~/.cache/huggingface/datasets/downloads/extracted`)"
] | 1,631,612,726,000 | 1,633,513,039,000 | null | NONE | null | ## Describe the bug
With GenerateMode.FORCE_REDOWNLOAD, the documentation says
+------------------------------------+-----------+---------+
| | Downloads | Dataset |
+====================================+===========+=========+
| `REUSE_DATASET_IF_EXISTS` (default)| Reuse | Reuse |
+------------------------------------+-----------+---------+
| `REUSE_CACHE_IF_EXISTS` | Reuse | Fresh |
+------------------------------------+-----------+---------+
| `FORCE_REDOWNLOAD` | Fresh | Fresh |
+------------------------------------+-----------+---------+
However, the old dataset is loaded even when FORCE_REDOWNLOAD is chosen.
## Steps to reproduce the bug
```python
import pandas as pd
from datasets import load_dataset, GenerateMode
pd.DataFrame(range(5), columns=['numbers']).to_csv('/tmp/test.tsv.gz', index=False)
ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD)
print(ee)
pd.DataFrame(range(10), columns=['numerals']).to_csv('/tmp/test.tsv.gz', index=False)
ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD)
print(ee)
```
## Expected results
Dataset({
features: ['numbers'],
num_rows: 5
})
Dataset({
features: ['numerals'],
num_rows: 10
})
## Actual results
Dataset({
features: ['numbers'],
num_rows: 5
})
Dataset({
features: ['numbers'],
num_rows: 5
})
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-4.14.181-108.257.amzn1.x86_64-x86_64-with-glibc2.10
- Python version: 3.7.10
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2903 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2903/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2903/comments | https://api.github.com/repos/huggingface/datasets/issues/2903/events | https://github.com/huggingface/datasets/pull/2903 | 995,715,191 | PR_kwDODunzps4rtxxV | 2,903 | Fix xpathopen to accept positional arguments | {
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"thanks!"
] | 1,631,606,570,000 | 1,631,609,481,000 | 1,631,608,847,000 | MEMBER | null | Fix `xpathopen()` so that it also accepts positional arguments.
Fix #2901. | {
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https://api.github.com/repos/huggingface/datasets/issues/2902 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2902/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2902/comments | https://api.github.com/repos/huggingface/datasets/issues/2902/events | https://github.com/huggingface/datasets/issues/2902 | 995,254,216 | MDU6SXNzdWU5OTUyNTQyMTY= | 2,902 | Add WIT Dataset | {
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"@hassiahk is working on it #2810 ",
"WikiMedia is now hosting the pixel values directly which should make it a lot easier!\r\nThe files can be found here:\r\nhttps://techblog.wikimedia.org/2021/09/09/the-wikipedia-image-caption-matching-challenge-and-a-huge-release-of-image-data-for-research/\r\nhttps://analytics.wikimedia.org/published/datasets/one-off/caption_competition/training/image_pixels/",
"> @hassiahk is working on it #2810\r\n\r\nThank you @bhavitvyamalik! Added this issue so we could track progress π . Just linked the PR as well for visibility. ",
"Hey folks, we are now hosting the merged pixel values + embeddings + metadata ourselves. I gave it a try - [nateraw/wit](https://huggingface.co/datasets/nateraw/wit)\r\n\r\n**β οΈ - Make sure you add `streaming=True` unless you're prepared to download 400GB of data!**\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset('nateraw/wit', streaming=True)\r\nexample = next(iter(ds))\r\n```\r\n\r\n```python\r\n>>> example = next(iter(ds['train']))\r\n>>> example.keys()\r\ndict_keys(['b64_bytes', 'original_width', 'image_url', 'wit_features', 'original_height', 'metadata_url', 'mime_type', 'caption_attribution_description', 'embedding'])\r\n>>> example['wit_features'].keys()\r\ndict_keys(['hierarchical_section_title', 'language', 'attribution_passes_lang_id', 'context_section_description', 'is_main_image', 'page_title', 'caption_title_and_reference_description', 'caption_alt_text_description', 'caption_reference_description', 'page_url', 'context_page_description', 'section_title', 'page_changed_recently'])\r\n```",
"Hi! `datasets` now hosts two versions of the WIT dataset:\r\n* [`google/wit`](https://huggingface.co/datasets/google/wit): Google's version with the image URLs\r\n* [`wikimedia/wit_base`](https://huggingface.co/datasets/wikimedia/wit_base): Wikimedia's version with the images + ResNet embeddings, but with less data than Google's version"
] | 1,631,561,929,000 | 1,654,104,520,000 | 1,654,104,520,000 | CONTRIBUTOR | null | ## Adding a Dataset
- **Name:** *WIT*
- **Description:** *Wikipedia-based Image Text Dataset*
- **Paper:** *[WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
](https://arxiv.org/abs/2103.01913)*
- **Data:** *https://github.com/google-research-datasets/wit*
- **Motivation:** (excerpt from their Github README.md)
> - The largest multimodal dataset (publicly available at the time of this writing) by the number of image-text examples.
> - A massively multilingual dataset (first of its kind) with coverage for over 100+ languages.
> - A collection of diverse set of concepts and real world entities.
> - Brings forth challenging real-world test sets.
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/2901 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2901/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2901/comments | https://api.github.com/repos/huggingface/datasets/issues/2901/events | https://github.com/huggingface/datasets/issues/2901 | 995,232,844 | MDU6SXNzdWU5OTUyMzI4NDQ= | 2,901 | Incompatibility with pytest | {
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"Sorry, my bad... When implementing `xpathopen`, I just considered the use case in the COUNTER dataset... I'm fixing it!"
] | 1,631,560,337,000 | 1,631,608,847,000 | 1,631,608,847,000 | CONTRIBUTOR | null | ## Describe the bug
pytest complains about xpathopen / path.open("w")
## Steps to reproduce the bug
Create a test file, `test.py`:
```python
import datasets as ds
def load_dataset():
ds.load_dataset("counter", split="train", streaming=True)
```
And launch it with pytest:
```bash
python -m pytest test.py
```
## Expected results
It should give something like:
```
collected 1 item
test.py . [100%]
======= 1 passed in 3.15s =======
```
## Actual results
```
============================================================================================================================= test session starts ==============================================================================================================================
platform linux -- Python 3.8.11, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /home/slesage/hf/datasets-preview-backend, configfile: pyproject.toml
plugins: anyio-3.3.1
collected 1 item
tests/queries/test_rows.py . [100%]Traceback (most recent call last):
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pytest/__main__.py", line 5, in <module>
raise SystemExit(pytest.console_main())
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/config/__init__.py", line 185, in console_main
code = main()
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/config/__init__.py", line 162, in main
ret: Union[ExitCode, int] = config.hook.pytest_cmdline_main(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_hooks.py", line 265, in __call__
return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_manager.py", line 80, in _hookexec
return self._inner_hookexec(hook_name, methods, kwargs, firstresult)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 60, in _multicall
return outcome.get_result()
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_result.py", line 60, in get_result
raise ex[1].with_traceback(ex[2])
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 39, in _multicall
res = hook_impl.function(*args)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/main.py", line 316, in pytest_cmdline_main
return wrap_session(config, _main)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/main.py", line 304, in wrap_session
config.hook.pytest_sessionfinish(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_hooks.py", line 265, in __call__
return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_manager.py", line 80, in _hookexec
return self._inner_hookexec(hook_name, methods, kwargs, firstresult)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 55, in _multicall
gen.send(outcome)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/terminal.py", line 803, in pytest_sessionfinish
outcome.get_result()
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_result.py", line 60, in get_result
raise ex[1].with_traceback(ex[2])
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 39, in _multicall
res = hook_impl.function(*args)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/cacheprovider.py", line 428, in pytest_sessionfinish
config.cache.set("cache/nodeids", sorted(self.cached_nodeids))
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/cacheprovider.py", line 188, in set
f = path.open("w")
TypeError: xpathopen() takes 1 positional argument but 2 were given
```
## Environment info
- `datasets` version: 1.12.0
- Platform: Linux-5.11.0-1017-aws-x86_64-with-glibc2.29
- Python version: 3.8.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/2900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2900/comments | https://api.github.com/repos/huggingface/datasets/issues/2900/events | https://github.com/huggingface/datasets/pull/2900 | 994,922,580 | MDExOlB1bGxSZXF1ZXN0NzMyNzczNDkw | 2,900 | Fix null sequence encoding | {
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Fix https://github.com/huggingface/datasets/issues/2892 | {
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https://api.github.com/repos/huggingface/datasets/issues/2899 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2899/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2899/comments | https://api.github.com/repos/huggingface/datasets/issues/2899/events | https://github.com/huggingface/datasets/issues/2899 | 994,082,432 | MDU6SXNzdWU5OTQwODI0MzI= | 2,899 | Dataset | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/2898 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2898/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2898/comments | https://api.github.com/repos/huggingface/datasets/issues/2898/events | https://github.com/huggingface/datasets/issues/2898 | 994,032,814 | MDU6SXNzdWU5OTQwMzI4MTQ= | 2,898 | Hug emoji | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/2897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2897/comments | https://api.github.com/repos/huggingface/datasets/issues/2897/events | https://github.com/huggingface/datasets/pull/2897 | 993,798,386 | MDExOlB1bGxSZXF1ZXN0NzMxOTA0ODk4 | 2,897 | Add OpenAI's HumanEval dataset | {
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"I just fixed the class name, and added `[More Information Needed]` in empty sections in case people want to complete the dataset card :)"
] | 1,631,353,067,000 | 1,631,804,531,000 | 1,631,804,531,000 | MEMBER | null | This PR adds OpenAI's [HumanEval](https://github.com/openai/human-eval) dataset. The dataset consists of 164 handcrafted programming problems with solutions and unittests to verify solution. This dataset is useful to evaluate code generation models. | {
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https://api.github.com/repos/huggingface/datasets/issues/2896 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2896/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2896/comments | https://api.github.com/repos/huggingface/datasets/issues/2896/events | https://github.com/huggingface/datasets/pull/2896 | 993,613,113 | MDExOlB1bGxSZXF1ZXN0NzMxNzcwMTE3 | 2,896 | add multi-proc in `to_csv` | {
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"I think you can just add a test `test_dataset_to_csv_multiproc` in `tests/io/test_csv.py` and we'll be good",
"Hi @lhoestq, \r\nI've added `test_dataset_to_csv` apart from `test_dataset_to_csv_multiproc` as no test was there to check generated CSV file when `num_proc=1`. Please let me know if anything is also required! "
] | 1,631,309,709,000 | 1,635,400,053,000 | 1,635,264,042,000 | CONTRIBUTOR | null | This PR extends the multi-proc method used in #2747 for`to_json` to `to_csv` as well.
Results on my machine post benchmarking on `ascent_kb` dataset (giving ~45% improvement when compared to num_proc = 1):
```
Time taken on 1 num_proc, 10000 batch_size 674.2055702209473
Time taken on 4 num_proc, 10000 batch_size 425.6553490161896
Time taken on 1 num_proc, 50000 batch_size 623.5897650718689
Time taken on 4 num_proc, 50000 batch_size 380.0402421951294
Time taken on 4 num_proc, 100000 batch_size 361.7168130874634
```
This is a WIP as writing tests is pending for this PR.
I'm also exploring [this](https://arrow.apache.org/docs/python/csv.html#incremental-writing) approach for which I'm using `pyarrow-5.0.0`.
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https://api.github.com/repos/huggingface/datasets/issues/2895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2895/comments | https://api.github.com/repos/huggingface/datasets/issues/2895/events | https://github.com/huggingface/datasets/pull/2895 | 993,462,274 | MDExOlB1bGxSZXF1ZXN0NzMxNjQ0NTY2 | 2,895 | Use pyarrow.Table.replace_schema_metadata instead of pyarrow.Table.cast | {
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``update_metadata_with_features`` uses ``Table.cast`` which slows down ``load_from_disk`` (and possibly other methods that use it) for very large datasets. Since ``update_metadata_with_features`` is only updating the schema metadata, it makes more sense to use ``pyarrow.Table.replace_schema_metadata`` which is much faster. This PR adds a ``replace_schema_metadata`` method to all table classes, and modifies ``update_metadata_with_features`` to use it instead of ``cast``. | {
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Related to #2866.
CC: @severo. | {
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https://api.github.com/repos/huggingface/datasets/issues/2893 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2893/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2893/comments | https://api.github.com/repos/huggingface/datasets/issues/2893/events | https://github.com/huggingface/datasets/pull/2893 | 993,342,781 | MDExOlB1bGxSZXF1ZXN0NzMxNTQ0NDQz | 2,893 | add mbpp dataset | {
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"I think it's fine to have the original schema"
] | 1,631,287,650,000 | 1,631,784,942,000 | 1,631,784,942,000 | MEMBER | null | This PR adds the mbpp dataset introduced by Google [here](https://github.com/google-research/google-research/tree/master/mbpp) as mentioned in #2816.
The dataset contain two versions: a full and a sanitized one. They have a slightly different schema and it is current state the loading preserves the original schema. An open question is whether to harmonize the two schemas when loading the dataset or to preserve the original one. Since not all fields are overlapping the schema will not be exactly the same. | {
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"This has been fixed by https://github.com/huggingface/datasets/pull/2900\r\nWe're doing a new release 1.12 today to make the fix available :)"
] | 1,631,283,103,000 | 1,631,542,693,000 | 1,631,542,662,000 | MEMBER | null | There is an error when encoding a dataset with None objects with a Sequence feature
To reproduce:
```python
from datasets import Dataset, Features, Value, Sequence
data = {"a": [[0], None]}
features = Features({"a": Sequence(Value("int32"))})
dataset = Dataset.from_dict(data, features=features)
```
raises
```python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-24-40add67f8751> in <module>
2 data = {"a": [[0], None]}
3 features = Features({"a": Sequence(Value("int32"))})
----> 4 dataset = Dataset.from_dict(data, features=features)
[...]
~/datasets/features.py in encode_nested_example(schema, obj)
888 if isinstance(obj, str): # don't interpret a string as a list
889 raise ValueError("Got a string but expected a list instead: '{}'".format(obj))
--> 890 return [encode_nested_example(schema.feature, o) for o in obj]
891 # Object with special encoding:
892 # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks
TypeError: 'NoneType' object is not iterable
```
Instead, if should run without error, as if the `features` were not passed | {
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"@lhoestq, thanks for your review.\r\n\r\nI added test for `to_pylist`, I didn't do that for `to_numpy` because this method shouldn't be called for dynamic dimension ArrayXD - this method will try to make a single numpy array for the whole column which cannot be done for dynamic arrays.\r\n\r\nI dig into `to_pandas()` functionality and I found it quite difficult to implement. `PandasArrayExtensionArray` takes single np.array as an argument. It might be a bit of changes to make it work with the list of arrays. Do you mind if we exclude this work from this PR. I added an error message for the case if somebody tries to use dynamic arrays with `to_pandas`",
"@lhoestq, I just fixed all the tests. Let me know if there is anything else to add.",
"@lhoestq, any chance you had some time to check out this PR?\r\n",
"Hi ! Sorry for the delay\r\n\r\nIt looks good to me ! I think the only thing missing is the support for passing a list of numpy arrays to `map` when the first dimension is dynamic.\r\n\r\nCurrently it raises an error:\r\n```python\r\nfrom datasets import *\r\nimport numpy as np\r\n\r\nfeatures= Features({\"a\": Array3D(shape=(None, 5, 2), dtype=\"int32\")})\r\nd = Dataset.from_dict({\"a\": [np.zeros((5,5,2)), np.zeros((2,5,2))]}, features=features)\r\nd = d.map(lambda a: {\"a\": np.concatenate([a]*2)}, input_columns=\"a\")\r\nprint(d[0])\r\n```\r\nraises\r\n```python\r\nTraceback (most recent call last):\r\n File \"playground/ttest.py\", line 6, in <module>\r\n d = d.map(lambda x: {\"a\": np.concatenate([x]*2)}, input_columns=\"a\")\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_dataset.py\", line 1932, in map\r\n return self._map_single(\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_dataset.py\", line 426, in wrapper\r\n out: Union[\"Dataset\", \"DatasetDict\"] = func(self, *args, **kwargs)\r\n File \"/home/truent/hf/datasets/src/datasets/fingerprint.py\", line 406, in wrapper\r\n out = func(self, *args, **kwargs)\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_dataset.py\", line 2317, in _map_single\r\n writer.finalize()\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_writer.py\", line 443, in finalize\r\n self.write_examples_on_file()\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_writer.py\", line 312, in write_examples_on_file\r\n pa_array = pa.array(typed_sequence)\r\n File \"pyarrow/array.pxi\", line 222, in pyarrow.lib.array\r\n File \"pyarrow/array.pxi\", line 110, in pyarrow.lib._handle_arrow_array_protocol\r\n File \"/home/truent/hf/datasets/src/datasets/arrow_writer.py\", line 108, in __arrow_array__\r\n storage = pa.array(self.data, type.storage_dtype)\r\n File \"pyarrow/array.pxi\", line 305, in pyarrow.lib.array\r\n File \"pyarrow/array.pxi\", line 39, in pyarrow.lib._sequence_to_array\r\n File \"pyarrow/error.pxi\", line 122, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 84, in pyarrow.lib.check_status\r\npyarrow.lib.ArrowInvalid: Can only convert 1-dimensional array values\r\n```\r\n\r\nI think the issue is that here we don't cover the case where self.data is a list of numpy arrays:\r\n\r\nhttps://github.com/huggingface/datasets/blob/55fd140a63b8f03a0e72985647e498f1fc799d3f/src/datasets/arrow_writer.py#L104-L109\r\n\r\nWe should remove the `isinstance(self.data[0], np.ndarray)` part and add these lines to cover this case:\r\n\r\nhttps://github.com/huggingface/datasets/blob/55fd140a63b8f03a0e72985647e498f1fc799d3f/src/datasets/arrow_writer.py#L112-L113",
"@lhoestq, thanks, good catch!\r\nAre you able to run this check with fixed dimension ArrayXD?\r\nfor below example\r\n```\r\nimport numpy as np\r\nfrom datasets import *\r\n\r\nfeatures = Features({\"a\": Array3D(shape=(2, 5, 2), dtype=\"int32\")})\r\nd = Dataset.from_dict({\"a\": [np.zeros((2, 5, 2)), np.zeros((2, 5, 2))]}, features=features)\r\nd = d.map(lambda a: {\"a\": np.array(a) + 1}, input_columns=\"a\")\r\nprint(d[0])\r\n```\r\n\r\nI am getting:\r\n```\r\n File \"/home/ib/datasets/src/datasets/arrow_writer.py\", line 116, in __arrow_array__\r\n if trying_type and out[0].as_py() != self.data[0]:\r\nValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()\r\n```",
"Nevertheless, I tried to fix that. Let me know if that works.",
"@lhoestq, just resolved the conflicts. Let me know if there is anything left to do with this PR",
"Hi, thanks a lot for your comments.\r\nAgree, happy to contribute to this topic in future PRs",
"Hi @rpowalski, thanks for adding this feature! \r\n\r\nI wanted to check if you are still interested in documenting this, otherwise I'd be happy to help with it :)"
] | 1,631,274,772,000 | 1,637,681,593,000 | 1,635,500,237,000 | CONTRIBUTOR | null | Add support for dynamic first dimension for ArrayXD features. See issue [#887](https://github.com/huggingface/datasets/issues/887).
Following changes allow for `to_pylist` method of `ArrayExtensionArray` to return a list of numpy arrays where fist dimension can vary.
@lhoestq Could you suggest how you want to extend test suit. For now I added only very limited testing. | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/2888 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2888/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2888/comments | https://api.github.com/repos/huggingface/datasets/issues/2888/events | https://github.com/huggingface/datasets/issues/2888 | 992,676,535 | MDU6SXNzdWU5OTI2NzY1MzU= | 2,888 | v1.11.1 release date | {
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"Hi ! Probably 1.12 on monday :)\r\n",
"@albertvillanova i think this issue is still valid and should not be closed till `>1.11.0` is published :)"
] | 1,631,224,395,000 | 1,631,477,915,000 | 1,631,463,339,000 | NONE | null | Hello, i need to use latest features in one of my packages but there have been no new datasets release since 2 months ago.
When do you plan to publush v1.11.1 release? | {
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https://api.github.com/repos/huggingface/datasets/issues/2887 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2887/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2887/comments | https://api.github.com/repos/huggingface/datasets/issues/2887/events | https://github.com/huggingface/datasets/pull/2887 | 992,576,305 | MDExOlB1bGxSZXF1ZXN0NzMwODg4MTU3 | 2,887 | #2837 Use cache folder for lockfile | {
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"The CI fail about the meteor metric is unrelated to this PR "
] | 1,631,217,356,000 | 1,633,456,702,000 | 1,633,456,702,000 | CONTRIBUTOR | null | Fixes #2837
Use a cache folder directory to store the FileLock.
The issue was that the lock file was in a readonly folder.
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https://api.github.com/repos/huggingface/datasets/issues/2886 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2886/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2886/comments | https://api.github.com/repos/huggingface/datasets/issues/2886/events | https://github.com/huggingface/datasets/issues/2886 | 992,534,632 | MDU6SXNzdWU5OTI1MzQ2MzI= | 2,886 | Hj | {
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https://api.github.com/repos/huggingface/datasets/issues/2885 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2885/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2885/comments | https://api.github.com/repos/huggingface/datasets/issues/2885/events | https://github.com/huggingface/datasets/issues/2885 | 992,160,544 | MDU6SXNzdWU5OTIxNjA1NDQ= | 2,885 | Adding an Elastic Search index to a Dataset | {
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"Hi, is this bug deterministic in your poetry env ? I mean, does it always stop at 90% or is it random ?\r\n\r\nAlso, can you try using another version of Elasticsearch ? Maybe there's an issue with the one of you poetry env",
"I face similar issue with oscar dataset on remote ealsticsearch instance. It was mainly due to timeout of batch indexing requests and I solve these by adding large request_timeout param in `search.py`\r\n\r\n```\r\n for ok, action in es.helpers.streaming_bulk(\r\n client=self.es_client,\r\n index=index_name,\r\n actions=passage_generator(),\r\n request_timeout=3600,\r\n )\r\n ```",
"Hi @MotzWanted - are there any errors in the Elasticsearch cluster logs? Since it works in your local environment and the cluster versions are different between your poetry env and your local env, it is possible that it is some difference in the cluster - either settings or the cluster being under a different load etc that has this effect, so it would be useful to see if any errors are thrown in the cluster's logs when you try to ingest. \r\nWhich elasticsearch client method is the function `add_elasticsearch_index` from your code using under the hood? Is it `helpers.bulk` or is the indexing performed using something else? You can try adding a timeout to the indexing method to see if this helps. Also, you mention that it stops at around 90% - do you know if the timeout/hanging happens always when a particular document is being indexed or does it happen randomly at around 90% completeness but on different documents?"
] | 1,631,190,099,000 | 1,634,756,231,000 | null | NONE | null | ## Describe the bug
When trying to index documents from the squad dataset, the connection to ElasticSearch seems to break:
Reusing dataset squad (/Users/andreasmotz/.cache/huggingface/datasets/squad/plain_text/1.0.0/d6ec3ceb99ca480ce37cdd35555d6cb2511d223b9150cce08a837ef62ffea453)
90%|βββββββββββββββββββββββββββββββββββββββββββββ | 9501/10570 [00:01<00:00, 6335.61docs/s]
No error is thrown, but the indexing breaks ~90%.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from datasets import load_dataset
from elasticsearch import Elasticsearch
es = Elasticsearch()
squad = load_dataset('squad', split='validation')
index_name = "corpus"
es_config = {
"settings": {
"number_of_shards": 1,
"analysis": {"analyzer": {"stop_standard": {"type": "standard", " stopwords": "_english_"}}},
},
"mappings": {
"properties": {
"idx" : {"type" : "keyword"},
"title" : {"type" : "keyword"},
"text": {
"type": "text",
"analyzer": "standard",
"similarity": "BM25"
},
}
},
}
class IndexBuilder:
"""
Elastic search indexing of a corpus
"""
def __init__(
self,
*args,
#corpus : None,
dataset : squad,
index_name = str,
query = str,
config = dict,
**kwargs,
):
#instantiate HuggingFace dataset
self.dataset = dataset
#instantiate ElasticSearch config
self.config = config
self.es = Elasticsearch()
self.index_name = index_name
self.query = query
def elastic_index(self):
print(self.es.info)
self.es.indices.delete(index=self.index_name, ignore=[400, 404])
search_index = self.dataset.add_elasticsearch_index(column='context', host='localhost', port='9200', es_index_name=self.index_name, es_index_config=self.config)
return search_index
def exact_match_method(self, index):
scores, retrieved_examples = index.get_nearest_examples('context', query=self.query, k=1)
return scores, retrieved_examples
if __name__ == "__main__":
print(type(squad))
Index = IndexBuilder(dataset=squad, index_name='corpus_index', query='Where was Chopin born?', config=es_config)
search_index = Index.elastic_index()
scores, examples = Index.exact_match_method(search_index)
print(scores, examples)
for name in squad.column_names:
print(type(squad[name]))
```
## Environment info
We run the code in Poetry. This might be the issue, since the script runs successfully in our local environment.
Poetry:
- Python version: 3.8
- PyArrow: 4.0.1
- Elasticsearch: 7.13.4
- datasets: 1.10.2
Local:
- Python version: 3.8
- PyArrow: 3.0.0
- Elasticsearch: 7.7.1
- datasets: 1.7.0
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https://api.github.com/repos/huggingface/datasets/issues/2884 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2884/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2884/comments | https://api.github.com/repos/huggingface/datasets/issues/2884/events | https://github.com/huggingface/datasets/pull/2884 | 992,135,698 | MDExOlB1bGxSZXF1ZXN0NzMwNTA4MTE1 | 2,884 | Add IC, SI, ER tasks to SUPERB | {
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"Sorry for the late PR, uploading 10+GB files to the hub through a VPN was an adventure :sweat_smile: ",
"Thank you so much for adding these subsets @anton-l! \r\n\r\n> These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingface.co/datasets/anton-l/superb_source_data_dumps/tree/main\r\nAre we allowed to make these datasets public or would that violate the terms of their use?",
"@lewtun These ones all have non-permissive licences, so the mirrored data I linked is open only to the HF org for now. But we could try contacting the authors to ask if they'd like to host these with us. \nFor example VoxCeleb1 now has direct links (the ones in the script) that don't require form submission and passwords, but they ban IPs after each download for some reason :(",
"> @lewtun These ones all have non-permissive licences, so the mirrored data I linked is open only to the HF org for now. But we could try contacting the authors to ask if they'd like to host these with us.\r\n> For example VoxCeleb1 now has direct links (the ones in the script) that don't require form submission and passwords, but they ban IPs after each download for some reason :(\r\n\r\nI think there would be a lot of value added if the authors would be willing to host their data on the HF Hub! As an end-user of `datasets`, I've found I'm more likely to explore a dataset if I'm able to quickly pull the subsets without needing a manual download. Perhaps we can tell them that the Hub offers several advantages like versioning and interactive exploration (with `datasets-viewer`)?"
] | 1,631,188,563,000 | 1,632,129,478,000 | 1,632,128,449,000 | MEMBER | null | This PR adds 3 additional classification tasks to SUPERB
#### Intent Classification
Dataset URL seems to be down at the moment :( See the note below.
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/fluent_commands/dataset.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#ic-intent-classification---fluent-speech-commands
#### Speaker Identification
Manual download script:
```
mkdir VoxCeleb1
cd VoxCeleb1
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad
cat vox1_dev* > vox1_dev_wav.zip
unzip vox1_dev_wav.zip
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip
unzip vox1_test_wav.zip
# download the official SUPERB train-dev-test split
wget https://raw.githubusercontent.com/s3prl/s3prl/master/s3prl/downstream/voxceleb1/veri_test_class.txt
```
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/voxceleb1/dataset.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sid-speaker-identification
#### Intent Classification
Manual download requires going through a slow application process, see the note below.
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/emotion/IEMOCAP_preprocess.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#er-emotion-recognition
#### :warning: Note
These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingface.co/datasets/anton-l/superb_source_data_dumps/tree/main | {
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https://api.github.com/repos/huggingface/datasets/issues/2883 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2883/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2883/comments | https://api.github.com/repos/huggingface/datasets/issues/2883/events | https://github.com/huggingface/datasets/pull/2883 | 991,969,875 | MDExOlB1bGxSZXF1ZXN0NzMwMzYzNTQz | 2,883 | Fix data URLs and metadata in DocRED dataset | {
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} | [] | closed | false | null | [] | null | [] | 1,631,177,734,000 | 1,631,532,271,000 | 1,631,532,271,000 | MEMBER | null | The host of `docred` dataset has updated the `dev` data file. This PR:
- Updates the dev URL
- Updates dataset metadata
This PR also fixes the URL of the `train_distant` split, which was wrong.
Fix #2882. | {
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https://api.github.com/repos/huggingface/datasets/issues/2882 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2882/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2882/comments | https://api.github.com/repos/huggingface/datasets/issues/2882/events | https://github.com/huggingface/datasets/issues/2882 | 991,800,141 | MDU6SXNzdWU5OTE4MDAxNDE= | 2,882 | `load_dataset('docred')` results in a `NonMatchingChecksumError` | {
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"Hi @tmpr, thanks for reporting.\r\n\r\nTwo weeks ago (23th Aug), the host of the source `docred` dataset updated one of the files (`dev.json`): you can see it [here](https://drive.google.com/drive/folders/1c5-0YwnoJx8NS6CV2f-NoTHR__BdkNqw).\r\n\r\nTherefore, the checksum needs to be updated.\r\n\r\nNormally, in the meantime, you could avoid the error by passing `ignore_verifications=True` to `load_dataset`. However, as the old link points to a non-existing file, the link must be updated too.\r\n\r\nI'm fixing all this.\r\n\r\n"
] | 1,631,166,902,000 | 1,631,532,270,000 | 1,631,532,270,000 | NONE | null | ## Describe the bug
I get consistent `NonMatchingChecksumError: Checksums didn't match for dataset source files` errors when trying to execute `datasets.load_dataset('docred')`.
## Steps to reproduce the bug
It is quasi only this code:
```python
import datasets
data = datasets.load_dataset('docred')
```
## Expected results
The DocRED dataset should be loaded without any problems.
## Actual results
```
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-4-b1b83f25a16c> in <module>
----> 1 d = datasets.load_dataset('docred')
~/anaconda3/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, streaming, **config_kwargs)
845
846 # Download and prepare data
--> 847 builder_instance.download_and_prepare(
848 download_config=download_config,
849 download_mode=download_mode,
~/anaconda3/lib/python3.8/site-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
613 logger.warning("HF google storage unreachable. Downloading and preparing it from source")
614 if not downloaded_from_gcs:
--> 615 self._download_and_prepare(
616 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
617 )
~/anaconda3/lib/python3.8/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
673 # Checksums verification
674 if verify_infos:
--> 675 verify_checksums(
676 self.info.download_checksums, dl_manager.get_recorded_sizes_checksums(), "dataset source files"
677 )
~/anaconda3/lib/python3.8/site-packages/datasets/utils/info_utils.py in verify_checksums(expected_checksums, recorded_checksums, verification_name)
38 if len(bad_urls) > 0:
39 error_msg = "Checksums didn't match" + for_verification_name + ":\n"
---> 40 raise NonMatchingChecksumError(error_msg + str(bad_urls))
41 logger.info("All the checksums matched successfully" + for_verification_name)
42
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1fDmfUUo5G7gfaoqWWvK81u08m71TK2g7']
```
## Environment info
- `datasets` version: 1.11.0
- Platform: Linux-5.11.0-7633-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 5.0.0
This error also happened on my Windows-partition, after freshly installing python 3.9 and `datasets`.
## Remarks
- I have already called `rm -rf /home/<user>/.cache/huggingface`, i.e., I have tried clearing the cache.
- The problem does not exist for other datasets, i.e., it seems to be DocRED-specific. | {
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https://api.github.com/repos/huggingface/datasets/issues/2881 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2881/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2881/comments | https://api.github.com/repos/huggingface/datasets/issues/2881/events | https://github.com/huggingface/datasets/pull/2881 | 991,639,142 | MDExOlB1bGxSZXF1ZXN0NzMwMDc1OTAy | 2,881 | Add BIOSSES dataset | {
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} | [] | closed | false | null | [] | null | [] | 1,631,147,736,000 | 1,631,542,840,000 | 1,631,542,840,000 | CONTRIBUTOR | null | Adding the biomedical semantic sentence similarity dataset, BIOSSES, listed in "Biomedical Datasets - BigScience Workshop 2021" | {
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https://api.github.com/repos/huggingface/datasets/issues/2880 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2880/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2880/comments | https://api.github.com/repos/huggingface/datasets/issues/2880/events | https://github.com/huggingface/datasets/pull/2880 | 990,877,940 | MDExOlB1bGxSZXF1ZXN0NzI5NDIzMDMy | 2,880 | Extend support for streaming datasets that use pathlib.Path stem/suffix | {
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} | [] | closed | false | null | [] | null | [] | 1,631,090,563,000 | 1,631,193,209,000 | 1,631,193,209,000 | MEMBER | null | This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the properties `pathlib.Path.stem` and `pathlib.Path.suffix`.
Related to #2876, #2874, #2866.
CC: @severo | {
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"Hi @rcgale, thanks for reporting.\r\n\r\nPlease note that this bug was fixed on `datasets` version 1.5.0: https://github.com/huggingface/datasets/commit/a23c73e526e1c30263834164f16f1fdf76722c8c#diff-f12a7a42d4673bb6c2ca5a40c92c29eb4fe3475908c84fd4ce4fad5dc2514878\r\n\r\nIf you update `datasets` version, that should work.\r\n\r\nOn the other hand, would it be possible for @patrickvonplaten to update the [blog post](https://huggingface.co/blog/fine-tune-wav2vec2-english) with the correct version of `datasets`?",
"I just proposed a change in the blog post.\r\n\r\nI had assumed there was a data format change that broke a previous version of the code, since presumably @patrickvonplaten tested the tutorial with the version they explicitly referenced. But that fix you linked suggests a problem in the code, which surprised me.\r\n\r\nI still wonder, though, is there a way for downloads to be invalidated server-side? If the client can announce its version during a download request, perhaps the server could reject known incompatibilities? It would save much valuable time if `datasets` raised an informative error on a known problem (\"Error: the requested data set requires `datasets>=1.5.0`.\"). This kind of API versioning is a prudent move anyhow, as there will surely come a time when you'll need to make a breaking change to data.",
"Also, thank you for a quick and helpful reply!"
] | 1,631,040,825,000 | 1,631,120,119,000 | 1,631,092,348,000 | NONE | null | ## Describe the bug
Using version 1.4.1 of `datasets`, TIMIT transcripts are all the same.
## Steps to reproduce the bug
I was following this tutorial
- https://huggingface.co/blog/fine-tune-wav2vec2-english
But here's a distilled repro:
```python
!pip install datasets==1.4.1
from datasets import load_dataset
timit = load_dataset("timit_asr", cache_dir="./temp")
unique_transcripts = set(timit["train"]["text"])
print(unique_transcripts)
assert len(unique_transcripts) > 1
```
## Expected results
Expected the correct TIMIT data. Or an error saying that this version of `datasets` can't produce it.
## Actual results
Every train transcript was "Would such an act of refusal be useful?" Every test transcript was "The bungalow was pleasantly situated near the shore."
## Environment info
- `datasets` version: 1.4.1
- Platform: Darwin-18.7.0-x86_64-i386-64bit
- Python version: 3.7.9
- PyTorch version (GPU?): 1.9.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: tried both
- Using distributed or parallel set-up in script?: no
-
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] | open | false | null | [] | null | [] | 1,631,027,705,000 | 1,631,027,705,000 | null | NONE | null | ## Describe the bug
Trying to load saved dataset or dataset directory from Amazon S3 on a Windows machine fails.
Performing the same operation succeeds on non-windows environment (AWS Sagemaker).
## Steps to reproduce the bug
```python
# Followed https://huggingface.co/docs/datasets/filesystems.html#loading-a-processed-dataset-from-s3
from datasets import load_from_disk
from datasets.filesystems import S3FileSystem
s3_file = "output of save_to_disk"
s3_filesystem = S3FileSystem()
load_from_disk(s3_file, fs=s3_filesystem)
```
## Expected results
load_from_disk succeeds without error
## Actual results
Seems like it succeeds in pulling the file into a windows temp directory, as it exists in my system, but fails to process it.
```
Exception ignored in: <finalize object at 0x26409231ce0; dead>
Traceback (most recent call last):
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__
return info.func(*info.args, **(info.kwargs or {}))
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup
cls._rmtree(name)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
[Previous line repeated 2 more times]
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror
cls._rmtree(path)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe
onerror(os.scandir, path, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe
with os.scandir(path) as scandir_it:
NotADirectoryError: [WinError 267] The directory name is invalid: 'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow'
Exception ignored in: <finalize object at 0x264091c7880; dead>
Traceback (most recent call last):
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__
return info.func(*info.args, **(info.kwargs or {}))
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup
cls._rmtree(name)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe
_rmtree_unsafe(fullname, onerror)
[Previous line repeated 2 more times]
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe
onerror(os.unlink, fullname, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror
cls._rmtree(path)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree
_shutil.rmtree(name, onerror=onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree
return _rmtree_unsafe(path, onerror)
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe
onerror(os.scandir, path, sys.exc_info())
File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe
with os.scandir(path) as scandir_it:
NotADirectoryError: [WinError 267] The directory name is invalid:
'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: Windows-10-10.0.19042-SP0
- Python version: 3.8.11
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2877 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2877/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2877/comments | https://api.github.com/repos/huggingface/datasets/issues/2877/events | https://github.com/huggingface/datasets/issues/2877 | 990,027,249 | MDU6SXNzdWU5OTAwMjcyNDk= | 2,877 | Don't keep the dummy data folder or dataset_infos.json when resolving data files | {
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"Hi @lhoestq I am new to huggingface datasets, I would like to work on this issue!\r\n",
"Thanks for the help :) \r\n\r\nAs mentioned in the PR, excluding files named \"dummy_data.zip\" is actually more general than excluding the files inside a \"dummy\" folder. I just did the change in the PR, I think we can merge it now"
] | 1,631,023,744,000 | 1,632,906,338,000 | 1,632,906,338,000 | MEMBER | null | When there's no dataset script, all the data files of a folder or a repository on the Hub are loaded as data files.
There are already a few exceptions:
- files starting with "." are ignored
- the dataset card "README.md" is ignored
- any file named "config.json" is ignored (currently it isn't used anywhere, but it could be used in the future to define splits or configs for example, but not 100% sure)
However any data files in a folder named "dummy" should be ignored as well as they should only be used to test the dataset.
Same for "dataset_infos.json" which should only be used to get the `dataset.info` | {
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"I am thinking that ideally we should call `fs.glob()` instead...",
"Thanks, @lhoestq: the idea of adding the mock filesystem is to avoid network calls and reduce testing time ;) \r\n\r\nI have added `rglob` as well and fixed some bugs."
] | 1,631,022,225,000 | 1,631,267,449,000 | 1,631,267,448,000 | MEMBER | null | This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the method `pathlib.Path.glob`.
Related to #2874, #2866.
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/2875 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2875/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2875/comments | https://api.github.com/repos/huggingface/datasets/issues/2875/events | https://github.com/huggingface/datasets/issues/2875 | 989,919,398 | MDU6SXNzdWU5ODk5MTkzOTg= | 2,875 | Add Congolese Swahili speech datasets | {
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- **Name:** Congolese Swahili speech corpora
- **Data:** https://gamayun.translatorswb.org/data/
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Also related: https://mobile.twitter.com/OktemAlp/status/1435196393631764482 | {
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"I've tried https://github.com/huggingface/datasets/issues/2866 again, and I get the same error.\r\n\r\n```python\r\nimport datasets as ds\r\nds.load_dataset('counter', split=\"train\", streaming=False)\r\n```",
"@severo Issue #2866 is not fully fixed yet: multiple patches need to be implemented for `pathlib`, as that dataset uses quite a lot of `pathlib` functions... π
",
"No worry and no stress, I just wanted to check for that case :) I'm very happy that you're working on issues I'm interested in!"
] | 1,631,000,149,000 | 1,631,039,122,000 | 1,631,014,875,000 | MEMBER | null | This PR extends the support in streaming mode for datasets that use `pathlib.Path`.
Related to: #2866.
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/2873 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2873/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2873/comments | https://api.github.com/repos/huggingface/datasets/issues/2873/events | https://github.com/huggingface/datasets/pull/2873 | 989,587,695 | MDExOlB1bGxSZXF1ZXN0NzI4MzA0MTMw | 2,873 | adding swedish_medical_ner | {
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"Hi, what's the current status of this request? It says Changes requested, but I can't see what changes?",
"Hi, it looks like this PR includes changes to other files that `swedish_medical_ner`.\r\n\r\nFeel free to remove these changes, or simply create a new PR that only contains the addition of the dataset"
] | 1,630,989,893,000 | 1,631,911,657,000 | 1,631,911,657,000 | CONTRIBUTOR | null | Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021"
Code refactored | {
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https://api.github.com/repos/huggingface/datasets/issues/2872 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2872/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2872/comments | https://api.github.com/repos/huggingface/datasets/issues/2872/events | https://github.com/huggingface/datasets/pull/2872 | 989,453,069 | MDExOlB1bGxSZXF1ZXN0NzI4MTkzMjkz | 2,872 | adding swedish_medical_ner | {
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} | [] | closed | false | null | [] | null | [] | 1,630,965,652,000 | 1,630,989,392,000 | 1,630,989,392,000 | CONTRIBUTOR | null | Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021" | {
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https://api.github.com/repos/huggingface/datasets/issues/2871 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2871/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2871/comments | https://api.github.com/repos/huggingface/datasets/issues/2871/events | https://github.com/huggingface/datasets/issues/2871 | 989,436,088 | MDU6SXNzdWU5ODk0MzYwODg= | 2,871 | datasets.config.PYARROW_VERSION has no attribute 'major' | {
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"I have changed line 288 to `if int(datasets.config.PYARROW_VERSION.split(\".\")[0]) < 3:` just to get around it.",
"Hi @bwang482,\r\n\r\nI'm sorry but I'm not able to reproduce your bug.\r\n\r\nPlease note that in our current master branch, we made a commit (d03223d4d64b89e76b48b00602aba5aa2f817f1e) that simultaneously modified:\r\n- test_dataset_common.py: https://github.com/huggingface/datasets/commit/d03223d4d64b89e76b48b00602aba5aa2f817f1e#diff-a1bc225bd9a5bade373d1f140e24d09cbbdc97971c2f73bb627daaa803ada002L289 that introduces the usage of `datasets.config.PYARROW_VERSION.major`\r\n- but also changed config.py: https://github.com/huggingface/datasets/commit/d03223d4d64b89e76b48b00602aba5aa2f817f1e#diff-e021fcfc41811fb970fab889b8d245e68382bca8208e63eaafc9a396a336f8f2L40, so that `datasets.config.PYARROW_VERSION.major` exists\r\n",
"Sorted. Thanks!",
"Reopening this. Although the `test_dataset_common.py` script works fine now.\r\n\r\nHas this got something to do with my pull request not passing `ci/circleci: run_dataset_script_tests_pyarrow` tests?\r\n\r\nhttps://github.com/huggingface/datasets/pull/2873",
"Hi @bwang482,\r\n\r\nIf you click on `Details` (on the right of your non passing CI test names: `ci/circleci: run_dataset_script_tests_pyarrow`), you can have more information about the non-passing tests.\r\n\r\nFor example, for [\"ci/circleci: run_dataset_script_tests_pyarrow_1\" details](https://circleci.com/gh/huggingface/datasets/46324?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link), you can see that the only non-passing test has to do with the dataset card (missing information in the `README.md` file): `test_changed_dataset_card`\r\n```\r\n=========================== short test summary info ============================\r\nFAILED tests/test_dataset_cards.py::test_changed_dataset_card[swedish_medical_ner]\r\n= 1 failed, 3214 passed, 2874 skipped, 2 xfailed, 1 xpassed, 15 warnings in 175.59s (0:02:55) =\r\n```\r\n\r\nTherefore, your PR non-passing test has nothing to do with this issue."
] | 1,630,962,417,000 | 1,631,091,112,000 | 1,631,091,112,000 | CONTRIBUTOR | null | In the test_dataset_common.py script, line 288-289
```
if datasets.config.PYARROW_VERSION.major < 3:
packaged_datasets = [pd for pd in packaged_datasets if pd["dataset_name"] != "parquet"]
```
which throws the error below. `datasets.config.PYARROW_VERSION` itself return the string '4.0.1'. I have tested this on both datasets.__version_=='1.11.0' and '1.9.0'. I am using Mac OS.
```
import datasets
datasets.config.PYARROW_VERSION.major
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/var/folders/1f/0wqmlgp90qjd5mpj53fnjq440000gn/T/ipykernel_73361/2547517336.py in <module>
1 import datasets
----> 2 datasets.config.PYARROW_VERSION.major
AttributeError: 'str' object has no attribute 'major'
```
## Environment info
- `datasets` version: 1.11.0
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/2870 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2870/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2870/comments | https://api.github.com/repos/huggingface/datasets/issues/2870/events | https://github.com/huggingface/datasets/pull/2870 | 988,276,859 | MDExOlB1bGxSZXF1ZXN0NzI3MjI4Njk5 | 2,870 | Fix three typos in two files for documentation | {
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} | [] | closed | false | null | [] | null | [] | 1,630,756,183,000 | 1,630,916,481,000 | 1,630,916,375,000 | CONTRIBUTOR | null | Changed "bacth_size" to "batch_size" (2x)
Changed "intsructions" to "instructions" | {
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https://api.github.com/repos/huggingface/datasets/issues/2869 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2869/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2869/comments | https://api.github.com/repos/huggingface/datasets/issues/2869/events | https://github.com/huggingface/datasets/issues/2869 | 987,676,420 | MDU6SXNzdWU5ODc2NzY0MjA= | 2,869 | TypeError: 'NoneType' object is not callable | {
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"Hi, @Chenfei-Kang.\r\n\r\nI'm sorry, but I'm not able to reproduce your bug:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset(\"glue\", 'cola')\r\nds\r\n```\r\n```\r\nDatasetDict({\r\n train: Dataset({\r\n features: ['sentence', 'label', 'idx'],\r\n num_rows: 8551\r\n })\r\n validation: Dataset({\r\n features: ['sentence', 'label', 'idx'],\r\n num_rows: 1043\r\n })\r\n test: Dataset({\r\n features: ['sentence', 'label', 'idx'],\r\n num_rows: 1063\r\n })\r\n})\r\n```\r\n\r\nCould you please give more details and environment info (platform, PyArrow version)?",
"> Hi, @Chenfei-Kang.\r\n> \r\n> I'm sorry, but I'm not able to reproduce your bug:\r\n> \r\n> ```python\r\n> from datasets import load_dataset\r\n> \r\n> ds = load_dataset(\"glue\", 'cola')\r\n> ds\r\n> ```\r\n> \r\n> ```\r\n> DatasetDict({\r\n> train: Dataset({\r\n> features: ['sentence', 'label', 'idx'],\r\n> num_rows: 8551\r\n> })\r\n> validation: Dataset({\r\n> features: ['sentence', 'label', 'idx'],\r\n> num_rows: 1043\r\n> })\r\n> test: Dataset({\r\n> features: ['sentence', 'label', 'idx'],\r\n> num_rows: 1063\r\n> })\r\n> })\r\n> ```\r\n> \r\n> Could you please give more details and environment info (platform, PyArrow version)?\r\n\r\nSorry to reply you so late.\r\nplatform: pycharm 2021 + anaconda with python 3.7\r\nPyArrow version: 5.0.0\r\nhuggingface-hub: 0.0.16\r\ndatasets: 1.9.0\r\n",
"- For the platform, we need to know the operating system of your machine. Could you please run the command `datasets-cli env` and copy-and-paste its output below?\r\n- In relation with the error, you just gave us the error type and message (`TypeError: 'NoneType' object is not callable`). Could you please copy-paste the complete stack trace, so that we know exactly which part of the code threw the error?",
"> * For the platform, we need to know the operating system of your machine. Could you please run the command `datasets-cli env` and copy-and-paste its output below?\r\n> * In relation with the error, you just gave us the error type and message (`TypeError: 'NoneType' object is not callable`). Could you please copy-paste the complete stack trace, so that we know exactly which part of the code threw the error?\r\n\r\n1. For the platform, here are the output:\r\n - datasets` version: 1.11.0\r\n - Platform: Windows-10-10.0.19041-SP0\r\n - Python version: 3.7.10\r\n - PyArrow version: 5.0.0\r\n2. For the code and errorοΌ\r\n ```python\r\n from datasets import load_dataset, load_metric\r\n dataset = load_dataset(\"glue\", \"cola\")\r\n ```\r\n ```python\r\n Traceback (most recent call last):\r\n ....\r\n ....\r\n File \"my_file.py\", line 2, in <module>\r\n dataset = load_dataset(\"glue\", \"cola\")\r\n File \"My environments\\lib\\site-packages\\datasets\\load.py\", line 830, in load_dataset\r\n **config_kwargs,\r\n File \"My environments\\lib\\site-packages\\datasets\\load.py\", line 710, in load_dataset_builder\r\n **config_kwargs,\r\n TypeError: 'NoneType' object is not callable\r\n ```\r\n Thank you!",
"For that environment, I am sorry but I can't reproduce the bug: I can load the dataset without any problem.",
"One naive question: do you have internet access from the machine where you execute the code?",
"> For that environment, I am sorry but I can't reproduce the bug: I can load the dataset without any problem.\r\n\r\nBut I can download other task dataset such as `dataset = load_dataset('squad')`. I don't know what went wrong. Thank you so much!",
"Hi,friends. I meet the same problem. Do you have a way to fix this? Thanks!\r\n"
] | 1,630,668,459,000 | 1,648,618,238,000 | 1,631,093,095,000 | NONE | null | ## Describe the bug
TypeError: 'NoneType' object is not callable
## Steps to reproduce the bug
```python
from datasets import load_dataset, load_metric
dataset = datasets.load_dataset("glue", 'cola')
```
## Expected results
A clear and concise description of the expected results.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform:
- Python version: 3.7
- PyArrow version:
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- **Name:** *Common Objects in 3D (CO3D)*
- **Description:** *See blog post [here](https://ai.facebook.com/blog/common-objects-in-3d-dataset-for-3d-reconstruction)*
- **Paper:** *[link to paper](https://arxiv.org/abs/2109.00512)*
- **Data:** *[link to data](https://ai.facebook.com/datasets/co3d-downloads/)*
- **Motivation:** *excerpt from above blog post:*
> As the first data set of its kind, CO3D will aptly enable reconstruction of real-life 3D objects. Indeed, CO3D already provides training data to enable our NeRFormer to tackle the new-view synthesis (NVS) task. Here, photorealistic NVS is a major step on the path to fully immersive AR/VR effects, where objects can be virtually transported across different environments, which will allow connecting users by sharing or recollecting their experiences.
>
> Besides practical applications in AR/VR, we hope that the data set will become a standard testbed for the recent proliferation of methods (including NeRFormer, Implicit Differentiable Renderer, NeRF, and others) that reconstruct 3D scenes by means of an implicit shape model.
>
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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"Hi @lhoestq \r\n\r\nJust a request to look at the dataset. Please let me know if any changes are necessary before merging it into the repo. Thank you.",
"Hey @lhoestq \r\n\r\nThanks for merging it. One question: I still cannot find the dataset on https://huggingface.co/datasets. Does it take some time or did I miss something?",
"Hi ! It takes a few hours or a day for the list of datasets on the website to be updated ;)"
] | 1,630,602,383,000 | 1,631,805,174,000 | 1,631,784,224,000 | CONTRIBUTOR | null | Hi. I request you to add our dataset to the repository.
This data was recently published at NAACL 2021: https://aclanthology.org/2021.naacl-main.254.pdf | {
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https://api.github.com/repos/huggingface/datasets/issues/2866 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2866/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2866/comments | https://api.github.com/repos/huggingface/datasets/issues/2866/events | https://github.com/huggingface/datasets/issues/2866 | 986,706,676 | MDU6SXNzdWU5ODY3MDY2NzY= | 2,866 | "counter" dataset raises an error in normal mode, but not in streaming mode | {
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"Hi @severo, thanks for reporting.\r\n\r\nJust note that currently not all canonical datasets support streaming mode: this is one case!\r\n\r\nAll datasets that use `pathlib` joins (using `/`) instead of `os.path.join` (as in this dataset) do not support streaming mode yet.",
"OK. Do you think it's possible to detect this, and raise an exception (maybe `NotImplementedError`, or a specific `StreamingError`)?",
"We should definitely support datasets using `pathlib` in streaming mode...\r\n\r\nFor non-supported datasets in streaming mode, we have already a request of raising an error/warning: see #2654.",
"Hi @severo, please note that \"counter\" dataset will be streamable (at least until it arrives at the missing file, error already in normal mode) once these PRs are merged:\r\n- #2874\r\n- #2876\r\n- #2880\r\n\r\nI have tested it. π ",
"Now (on master), we get:\r\n\r\n```\r\nimport datasets as ds\r\nds.load_dataset('counter', split=\"train\", streaming=False)\r\n```\r\n\r\n```\r\nUsing custom data configuration default\r\nDownloading and preparing dataset counter/default (download: 1.29 MiB, generated: 2.48 MiB, post-processed: Unknown size, total: 3.77 MiB) to /home/slesage/.cache/huggingface/datasets/counter/default/1.0.0/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9...\r\nTraceback (most recent call last):\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 726, in _download_and_prepare\r\n self._prepare_split(split_generator, **prepare_split_kwargs)\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 1124, in _prepare_split\r\n for key, record in utils.tqdm(\r\n File \"/home/slesage/hf/datasets/.venv/lib/python3.8/site-packages/tqdm/std.py\", line 1185, in __iter__\r\n for obj in iterable:\r\n File \"/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9/counter.py\", line 161, in _generate_examples\r\n with derived_file.open(encoding=\"utf-8\") as f:\r\n File \"/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py\", line 1222, in open\r\n return io.open(self, mode, buffering, encoding, errors, newline,\r\n File \"/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py\", line 1078, in _opener\r\n return self._accessor.open(self, flags, mode)\r\nFileNotFoundError: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'\r\n\r\nDuring handling of the above exception, another exception occurred:\r\n\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/home/slesage/hf/datasets/src/datasets/load.py\", line 1112, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 636, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/home/slesage/hf/datasets/src/datasets/builder.py\", line 728, in _download_and_prepare\r\n raise OSError(\r\nOSError: Cannot find data file.\r\nOriginal error:\r\n[Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'\r\n```\r\n\r\nThe error is now the same with or without streaming. I close the issue, thanks @albertvillanova and @lhoestq!\r\n",
"Note that we might want to open an issue to fix the \"counter\" dataset by itself, but I let it up to you.",
"Fixed here: https://github.com/huggingface/datasets/pull/2894. Thanks @albertvillanova ",
"On master, I get:\r\n\r\n```python\r\n>>> import datasets as ds\r\n>>> iterable_dataset = ds.load_dataset('counter', split=\"train\", streaming=True)\r\n>>> rows = list(iterable_dataset.take(100))\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 341, in __iter__\r\n for key, example in self._iter():\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 338, in _iter\r\n yield from ex_iterable\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 273, in __iter__\r\n yield from islice(self.ex_iterable, self.n)\r\n File \"/home/slesage/hf/datasets/src/datasets/iterable_dataset.py\", line 78, in __iter__\r\n for key, example in self.generate_examples_fn(**self.kwargs):\r\n File \"/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/b9e4378dbd3f5ce235d2302e48168c00196e67bbcd13cc7e1f6e69ef82c0cf2a/counter.py\", line 153, in _generate_examples\r\n files = sorted(base_path.glob(r\"[0-9][0-9][0-9][0-9].xml\"))\r\nTypeError: xpathglob() missing 1 required positional argument: 'pattern'\r\n```",
"Associated to the above exception, if I create a test and run it with pytest, I get an awful traceback.\r\n\r\n- create a file `test_counter.py`\r\n\r\n```python\r\nimport pytest\r\nfrom datasets import load_dataset, IterableDataset\r\nfrom typing import Any, cast\r\n\r\n\r\ndef test_counter() -> Any:\r\n iterable_dataset = cast(IterableDataset, load_dataset(\"counter\", split=\"train\", streaming=True))\r\n with pytest.raises(TypeError):\r\n list(iterable_dataset.take(100))\r\n```\r\n\r\n- run the test with pytest\r\n\r\n```bash\r\n$ python -m pytest -x test_counter.py\r\n============================================================================================================================= test session starts ==============================================================================================================================\r\nplatform linux -- Python 3.9.6, pytest-6.2.5, py-1.10.0, pluggy-1.0.0\r\nrootdir: /home/slesage/hf/datasets-preview-backend, configfile: pyproject.toml\r\nplugins: anyio-3.3.2, cov-2.12.1\r\ncollected 1 item\r\n\r\ntests/test_counter.py . [100%]Traceback (most recent call last):\r\n File \"/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/runpy.py\", line 197, in _run_module_as_main\r\n return _run_code(code, main_globals, None,\r\n File \"/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/runpy.py\", line 87, in _run_code\r\n exec(code, run_globals)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pytest/__main__.py\", line 5, in <module>\r\n raise SystemExit(pytest.console_main())\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/config/__init__.py\", line 185, in console_main\r\n code = main()\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/config/__init__.py\", line 162, in main\r\n ret: Union[ExitCode, int] = config.hook.pytest_cmdline_main(\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_hooks.py\", line 265, in __call__\r\n return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_manager.py\", line 80, in _hookexec\r\n return self._inner_hookexec(hook_name, methods, kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 60, in _multicall\r\n return outcome.get_result()\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_result.py\", line 60, in get_result\r\n raise ex[1].with_traceback(ex[2])\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 39, in _multicall\r\n res = hook_impl.function(*args)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/main.py\", line 316, in pytest_cmdline_main\r\n return wrap_session(config, _main)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/main.py\", line 304, in wrap_session\r\n config.hook.pytest_sessionfinish(\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_hooks.py\", line 265, in __call__\r\n return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_manager.py\", line 80, in _hookexec\r\n return self._inner_hookexec(hook_name, methods, kwargs, firstresult)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 55, in _multicall\r\n gen.send(outcome)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/terminal.py\", line 803, in pytest_sessionfinish\r\n outcome.get_result()\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_result.py\", line 60, in get_result\r\n raise ex[1].with_traceback(ex[2])\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/pluggy/_callers.py\", line 39, in _multicall\r\n res = hook_impl.function(*args)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/cacheprovider.py\", line 428, in pytest_sessionfinish\r\n config.cache.set(\"cache/nodeids\", sorted(self.cached_nodeids))\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/_pytest/cacheprovider.py\", line 188, in set\r\n f = path.open(\"w\")\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py\", line 199, in xpathopen\r\n return xopen(_as_posix(path), *args, **kwargs)\r\n File \"/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py\", line 117, in _as_posix\r\n path_as_posix = path.as_posix()\r\nAttributeError: 'str' object has no attribute 'as_posix'\r\n```\r\n",
"I opened a PR to fix these issues.\r\nAlso in your test you expect a TypeError but I don't know why. On my side it works fine without raising a TypeError",
"I had the issue (TypeError raised) on my branch, but it's fixed now. Thanks"
] | 1,630,588,253,000 | 1,634,203,449,000 | 1,634,203,449,000 | CONTRIBUTOR | null | ## Describe the bug
`counter` dataset raises an error on `load_dataset()`, but simply returns an empty iterator in streaming mode.
## Steps to reproduce the bug
```python
>>> import datasets as ds
>>> a = ds.load_dataset('counter', split="train", streaming=False)
Using custom data configuration default
Downloading and preparing dataset counter/default (download: 1.29 MiB, generated: 2.48 MiB, post-processed: Unknown size, total: 3.77 MiB) to /home/slesage/.cache/huggingface/datasets/counter/default/1.0.0/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9...
Traceback (most recent call last):
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 726, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 1124, in _prepare_split
for key, record in utils.tqdm(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/tqdm/std.py", line 1185, in __iter__
for obj in iterable:
File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9/counter.py", line 161, in _generate_examples
with derived_file.open(encoding="utf-8") as f:
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1222, in open
return io.open(self, mode, buffering, encoding, errors, newline,
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1078, in _opener
return self._accessor.open(self, flags, mode)
FileNotFoundError: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 728, in _download_and_prepare
raise OSError(
OSError: Cannot find data file.
Original error:
[Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'
```
```python
>>> import datasets as ds
>>> b = ds.load_dataset('counter', split="train", streaming=True)
Using custom data configuration default
>>> list(b)
[]
```
## Expected results
An exception should be raised in streaming mode
## Actual results
No exception is raised in streaming mode: there is no way to tell if something has broken or if the dataset is simply empty.
## Environment info
- `datasets` version: 1.11.1.dev0
- Platform: Linux-5.11.0-1016-aws-x86_64-with-glibc2.29
- Python version: 3.8.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/2865 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2865/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2865/comments | https://api.github.com/repos/huggingface/datasets/issues/2865/events | https://github.com/huggingface/datasets/pull/2865 | 986,460,698 | MDExOlB1bGxSZXF1ZXN0NzI1NjY1ODgx | 2,865 | Add MultiEURLEX dataset | {
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"Hi @lhoestq, we have this new cool multilingual dataset coming at EMNLP 2021. It would be really nice if we could have it in Hugging Face asap. Thanks! ",
"Hi @lhoestq, I adopted most of your suggestions:\r\n\r\n- Dummy data files reduced, including the 2 smallest documents per subset JSONL.\r\n- README was updated with the publication URL and instructions on how to download and use label descriptors. Excessive newlines were deleted.\r\n\r\nI would prefer to keep the label list in a pure format (original ids), to enable people to combine those with more information or possibly in the future explore the dataset, find inconsistencies and fix those to release a new version. ",
"Thanks for the changes :)\r\n\r\nRegarding the labels:\r\n\r\nIf you use the ClassLabel feature type, the only change is that it will store the ids as integers instead of (currently) string.\r\nThe advantage is that if people want to know what id corresponds to which label name, they can use `classlabel.int2str`. It is also the format that helps automate model training for classification in `transformers`.\r\n\r\nLet me know if that sounds good to you or if you still want to stick with the labels as they are now.",
"Hey @lhoestq, thanks for providing this information. This sounds great. I updated my code accordingly to use `ClassLabel`. Could you please provide a minimal example of how `classlabel.int2str` works in practice in my case, where labels are a sequence?\r\n\r\n```python\r\nfrom datasets import load_dataset\r\ndataset = load_dataset('multi_eurlex', 'all_languages')\r\n# Read strs from the labels (list of integers) for the 1st sample of the training split\r\n```\r\n\r\nI would like to include this in the README file.\r\n\r\nCould you also provide some info on how I could define the supervized key to automate model training, as you said?\r\n\r\nThanks!",
"Thanks for the update :)\r\n\r\nHere is an example of usage:\r\n```python\r\nfrom datasets import load_dataset\r\ndataset = load_dataset('multi_eurlex', 'all_languages', split='train')\r\nclasslabel = dataset.features[\"labels\"].feature\r\nprint(dataset[0][\"labels\"])\r\n# [1, 20, 7, 3, 0]\r\nprint(classlabel.int2str(dataset[0][\"labels\"]))\r\n# ['100160', '100155', '100158', '100147', '100149']\r\n```\r\n\r\nThe ClassLabel is simply used to define the `id2label` dictionary of classification models, to make the ids match between the model and the dataset. There nothing more to do :p \r\n\r\nI think one last thing to do is just update the `dataset_infos.json` file and we'll be good !",
"Everything is ready! π \r\n"
] | 1,630,575,744,000 | 1,631,274,606,000 | 1,631,274,606,000 | CONTRIBUTOR | null | **Add new MultiEURLEX Dataset**
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource). Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU. As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels); this is multi-label classification task (given the text, predict multiple labels). | {
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Fix #2860. | {
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https://api.github.com/repos/huggingface/datasets/issues/2863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2863/comments | https://api.github.com/repos/huggingface/datasets/issues/2863/events | https://github.com/huggingface/datasets/pull/2863 | 986,156,755 | MDExOlB1bGxSZXF1ZXN0NzI1MzkwMTkx | 2,863 | Update dataset URL | {
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"Superseded by PR #2864.\r\n\r\n@mrm8488 next time you would like to work on an issue, you can first self-assign it to you (by writing `#self-assign` in a comment on the issue). That way, other people can see you are already working on it and there are not multiple people working on the same issue. π "
] | 1,630,560,138,000 | 1,630,570,250,000 | 1,630,570,250,000 | CONTRIBUTOR | null | null | {
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"To give more context: after our discussion, if I understood properly, you are trying to fix a call to `datasets` that takes 15 minutes: https://github.com/huggingface/datasets-preview-backend/issues/17 Is this right?\r\n\r\n",
"Yes, that's it. And to do that I'm trying to use https://pypi.org/project/stopit/, which will raise a stopit.TimeoutException exception. But currently, if this exception is raised, it's caught and considered as a \"FileNotFoundError\" while it should not be caught. ",
"And what about passing the `timeout` parameter instead?",
"It might be a good idea, but I would have to add a timeout argument to several methods, I'm not sure we want that (I want to ensure all my queries in https://github.com/huggingface/datasets-preview-backend/tree/master/src/datasets_preview_backend/queries resolve in a given time, be it with an error in case of timeout, or with the successful response). The methods are `prepare_module`, `import_main_class`, *builder_cls.*`get_all_exported_dataset_infos`, `load_dataset_builder`, and `load_dataset`",
"I understand, you are trying to find a fix for your use case. OK.\r\n\r\nJust note that it is also an issue for `datasets` users. Once #2859 fixed in `datasets`, you will no longer have this issue...",
"Closing, since 1. my problem is more #2859, and I was asking for that change in order to make a hack work on my side, 2. if we want to change how exceptions are handled, we surely want to do it on all the codebase, not only in this particular case."
] | 1,630,498,692,000 | 1,630,576,416,000 | 1,630,576,323,000 | CONTRIBUTOR | null | The same specific exception is catched in other parts of the same
function. | {
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"Hola @mrm8488, thanks for reporting.\r\n\r\nApparently, the data source host changed their URL one week ago: https://github.com/google-research-datasets/ToTTo/commit/cebeb430ec2a97747e704d16a9354f7d9073ff8f\r\n\r\nI'm fixing it."
] | 1,630,494,250,000 | 1,630,565,260,000 | 1,630,565,260,000 | CONTRIBUTOR | null | Error: Couldn't find file at https://storage.googleapis.com/totto/totto_data.zip
`datasets version: 1.11.0`
# How to reproduce:
```py
from datasets import load_dataset
dataset = load_dataset('totto')
```
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"https://github.com/huggingface/datasets/blob/6c766f9115d686182d76b1b937cb27e099c45d68/src/datasets/builder.py#L179-L186",
"Thanks a lot!!!"
] | 1,630,444,264,000 | 1,634,024,152,000 | 1,633,950,351,000 | MEMBER | null | This does 60,000+ HEAD requests to get all the ETags of all the data files:
```python
from datasets import load_dataset
load_dataset("allenai/c4", streaming=True)
```
It makes loading the dataset completely impractical.
The ETags are used to compute the config id (it must depend on the data files being used).
Instead of using the ETags, we could simply use the commit hash of the dataset repository on the hub, as well and the glob pattern used to resolve the files (here it's `*` by default, to load all the files of the repository) | {
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https://api.github.com/repos/huggingface/datasets/issues/2858 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2858/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2858/comments | https://api.github.com/repos/huggingface/datasets/issues/2858/events | https://github.com/huggingface/datasets/pull/2858 | 984,145,568 | MDExOlB1bGxSZXF1ZXN0NzIzNjEzNzQ0 | 2,858 | Fix s3fs version in CI | {
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This PR changes the constrains to avoid the new conflicts
In particular it pins the version of s3fs. | {
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https://api.github.com/repos/huggingface/datasets/issues/2857 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2857/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2857/comments | https://api.github.com/repos/huggingface/datasets/issues/2857/events | https://github.com/huggingface/datasets/pull/2857 | 984,093,938 | MDExOlB1bGxSZXF1ZXN0NzIzNTY5OTE4 | 2,857 | Update: Openwebtext - update size | {
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"merging since the CI error in unrelated to this PR and fixed on master"
] | 1,630,429,863,000 | 1,644,921,483,000 | 1,631,007,872,000 | MEMBER | null | Update the size of the Openwebtext dataset
I also regenerated the dataset_infos.json but the data file checksum didn't change, and the number of examples either (8013769 examples)
Close #2839, close #726. | {
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https://api.github.com/repos/huggingface/datasets/issues/2856 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2856/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2856/comments | https://api.github.com/repos/huggingface/datasets/issues/2856/events | https://github.com/huggingface/datasets/pull/2856 | 983,876,734 | MDExOlB1bGxSZXF1ZXN0NzIzMzg2NzIw | 2,856 | fix: π remove URL's query string only if it's ?dl=1 | {
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} | [] | closed | false | null | [] | null | [] | 1,630,417,207,000 | 1,630,419,732,000 | 1,630,419,732,000 | CONTRIBUTOR | null | A lot of URL use the query strings, for example
http://opus.nlpl.eu/download.php?f=Bianet/v1/moses/en-ku.txt.zip, we
must not remove it when trying to detect the protocol. We thus remove it
only in the case of the query string being ?dl=1 which occurs on dropbox
and dl.orangedox.com. Also: add unit tests.
See https://github.com/huggingface/datasets/pull/2843 for the original
discussion. | {
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https://api.github.com/repos/huggingface/datasets/issues/2855 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2855/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2855/comments | https://api.github.com/repos/huggingface/datasets/issues/2855/events | https://github.com/huggingface/datasets/pull/2855 | 983,858,229 | MDExOlB1bGxSZXF1ZXN0NzIzMzcxMTIy | 2,855 | Fix windows CI CondaError | {
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We can fix the conda error
```
CondaError: Cannot link a source that does not exist.
C:\Users\...\Anaconda3\Scripts\conda.exe
```
by doing
```bash
conda update conda
```
before doing any install in the windows CI | {
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https://api.github.com/repos/huggingface/datasets/issues/2854 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2854/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2854/comments | https://api.github.com/repos/huggingface/datasets/issues/2854/events | https://github.com/huggingface/datasets/pull/2854 | 983,726,084 | MDExOlB1bGxSZXF1ZXN0NzIzMjU3NDg5 | 2,854 | Fix caching when moving script | {
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"Merging since the CI failure is unrelated to this PR"
] | 1,630,407,515,000 | 1,630,415,616,000 | 1,630,415,616,000 | MEMBER | null | When caching the result of a `map` function, the hash that is computed depends on many properties of this function, such as all the python objects it uses, its code and also the location of this code.
Using the full path of the python script for the location of the code makes the hash change if a script like `run_mlm.py` is moved.
I changed this by simply using the base name of the script instead of the full path.
Note that this change also affects the hash of the code used from imported modules, but I think it's fine. Indeed it hashes the code of the imported modules anyway, so the location of the python files of the imported modules doesn't matter when computing the hash.
Close https://github.com/huggingface/datasets/issues/2825 | {
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https://api.github.com/repos/huggingface/datasets/issues/2853 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2853/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2853/comments | https://api.github.com/repos/huggingface/datasets/issues/2853/events | https://github.com/huggingface/datasets/pull/2853 | 983,692,026 | MDExOlB1bGxSZXF1ZXN0NzIzMjI4NDY3 | 2,853 | Add AMI dataset | {
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"Hey @cahya-wirawan, \r\n\r\nI played around with the dataset a bit and it looks already very good to me! That's exactly how it should be constructed :-) I can help you a bit with defining the config, etc... on Monday!",
"@lhoestq - I think the dataset is ready to be merged :-) \r\n\r\nAt the moment, I don't really see how the failing tests correspond to this PR:\r\n- https://app.circleci.com/pipelines/github/huggingface/datasets/7838/workflows/932a40a2-3e11-48be-84f0-c6434510058e/jobs/48318?invite=true#step-107-18\r\n- https://app.circleci.com/pipelines/github/huggingface/datasets/7838/workflows/932a40a2-3e11-48be-84f0-c6434510058e/jobs/48316?invite=true#step-102-136\r\n\r\ncould you maybe give it a look? :-)"
] | 1,630,405,141,000 | 1,632,907,159,000 | 1,632,907,159,000 | CONTRIBUTOR | null | This is an initial commit for AMI dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2852 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2852/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2852/comments | https://api.github.com/repos/huggingface/datasets/issues/2852/events | https://github.com/huggingface/datasets/pull/2852 | 983,609,352 | MDExOlB1bGxSZXF1ZXN0NzIzMTU4Mzc4 | 2,852 | Fix: linnaeus - fix url | {
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"Merging since the CI error is unrelated this this PR"
] | 1,630,399,873,000 | 1,630,415,530,000 | 1,630,415,529,000 | MEMBER | null | The url was causing a `ConnectionError` because of the "/" at the end
Close https://github.com/huggingface/datasets/issues/2821 | {
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https://api.github.com/repos/huggingface/datasets/issues/2851 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2851/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2851/comments | https://api.github.com/repos/huggingface/datasets/issues/2851/events | https://github.com/huggingface/datasets/pull/2851 | 982,789,593 | MDExOlB1bGxSZXF1ZXN0NzIyNDg4MDY2 | 2,851 | Update `column_names` showed as `:func:` in exploring.st | {
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One mention of `column_names` in exploring.st was showing it as `:func:` instead of `:attr:`. | {
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https://api.github.com/repos/huggingface/datasets/issues/2850 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2850/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2850/comments | https://api.github.com/repos/huggingface/datasets/issues/2850/events | https://github.com/huggingface/datasets/issues/2850 | 982,654,644 | MDU6SXNzdWU5ODI2NTQ2NDQ= | 2,850 | Wound segmentation datasets | {
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"name": "dataset request",
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] | open | false | null | [] | null | [] | 1,630,320,272,000 | 1,638,964,920,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** Wound segmentation datasets
- **Description:** annotated wound image dataset
- **Paper:** https://www.nature.com/articles/s41598-020-78799-w
- **Data:** https://github.com/uwm-bigdata/wound-segmentation
- **Motivation:** Interesting simple image dataset, useful for segmentation, with visibility due to http://www.miccai.org/special-interest-groups/challenges/ and https://fusc.grand-challenge.org/
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/2849 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2849/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2849/comments | https://api.github.com/repos/huggingface/datasets/issues/2849/events | https://github.com/huggingface/datasets/issues/2849 | 982,631,420 | MDU6SXNzdWU5ODI2MzE0MjA= | 2,849 | Add Open Catalyst Project Dataset | {
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] | open | false | null | [] | null | [] | 1,630,318,479,000 | 1,630,318,479,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** Open Catalyst 2020 (OC20) Dataset
- **Website:** https://opencatalystproject.org/
- **Data:** https://github.com/Open-Catalyst-Project/ocp/blob/master/DATASET.md
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/2848 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2848/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2848/comments | https://api.github.com/repos/huggingface/datasets/issues/2848/events | https://github.com/huggingface/datasets/pull/2848 | 981,953,908 | MDExOlB1bGxSZXF1ZXN0NzIxODYyMDQx | 2,848 | Update README.md | {
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"Merging since the CI error is unrelated to this PR and fixed on master"
] | 1,630,195,106,000 | 1,631,007,632,000 | 1,631,007,632,000 | CONTRIBUTOR | null | Changed 'Tain' to 'Train'. | {
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https://api.github.com/repos/huggingface/datasets/issues/2847 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2847/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2847/comments | https://api.github.com/repos/huggingface/datasets/issues/2847/events | https://github.com/huggingface/datasets/pull/2847 | 981,589,693 | MDExOlB1bGxSZXF1ZXN0NzIxNjA3OTA0 | 2,847 | fix regex to accept negative timezone | {
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https://api.github.com/repos/huggingface/datasets/issues/2846 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2846/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2846/comments | https://api.github.com/repos/huggingface/datasets/issues/2846/events | https://github.com/huggingface/datasets/issues/2846 | 981,587,590 | MDU6SXNzdWU5ODE1ODc1OTA= | 2,846 | Negative timezone | {
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"Fixed by #2847."
] | 1,630,097,433,000 | 1,631,274,667,000 | 1,631,274,667,000 | CONTRIBUTOR | null | ## Describe the bug
The load_dataset method do not accept a parquet file with a negative timezone, as it has the following regex:
```
"^(s|ms|us|ns),\s*tz=([a-zA-Z0-9/_+:]*)$"
```
So a valid timestap ```timestamp[us, tz=-03:00]``` returns an error when loading parquet files.
## Steps to reproduce the bug
```python
# Where the timestamp column has a tz of -03:00
datasets = load_dataset('parquet', data_files={'train': train_files, 'validation': validation_files,
'test': test_files}, cache_dir="./cache_teste/")
```
## Expected results
The -03:00 is a valid tz so the regex should accept this without raising an error.
## Actual results
As this regex disaproves a valid tz it raises the following error:
```python
raise ValueError(
f"{datasets_dtype} is not a validly formatted string representation of a pyarrow timestamp."
f"Examples include timestamp[us] or timestamp[us, tz=America/New_York]"
f"See: https://arrow.apache.org/docs/python/generated/pyarrow.timestamp.html#pyarrow.timestamp"
)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: Ubuntu 20.04
- Python version: 3.8
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2845 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2845/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2845/comments | https://api.github.com/repos/huggingface/datasets/issues/2845/events | https://github.com/huggingface/datasets/issues/2845 | 981,487,861 | MDU6SXNzdWU5ODE0ODc4NjE= | 2,845 | [feature request] adding easy to remember `datasets.cache_dataset()` + `datasets.is_dataset_cached()` | {
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] | open | false | null | [] | null | [] | 1,630,088,511,000 | 1,630,088,645,000 | null | MEMBER | null | Often, there is a need to prepare a dataset but not use it immediately, e.g. think tests suite setup, so it'd be really useful to be able to do:
```
if not datasets.is_dataset_cached(ds): datasets.cache_dataset(ds)
```
This can already be done with:
```
builder = load_dataset_builder(ds)
if not os.path.idsir(builder.cache_dir):
builder.download_and_prepare()
```
but the current way is a way less intuitive and much harder to remember than the proposed API, IMHO.
One more way is to do:
```
_ = load_dataset(ds)
```
but it wastes resources loading the dataset when it's not needed.
this has been discussed at https://huggingface.slack.com/archives/C01229B19EX/p1630021912025800
Thank you!
@lhoestq
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https://api.github.com/repos/huggingface/datasets/issues/2844 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2844/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2844/comments | https://api.github.com/repos/huggingface/datasets/issues/2844/events | https://github.com/huggingface/datasets/pull/2844 | 981,382,806 | MDExOlB1bGxSZXF1ZXN0NzIxNDQzMjY2 | 2,844 | Fix: wikicorpus - fix keys | {
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"The CI error is unrelated to this PR\r\n\r\n... merging !"
] | 1,630,079,766,000 | 1,630,937,248,000 | 1,630,937,247,000 | MEMBER | null | As mentioned in https://github.com/huggingface/datasets/issues/2552, there is a duplicate keys error in `wikicorpus`.
I fixed that by taking into account the file index in the keys | {
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https://api.github.com/repos/huggingface/datasets/issues/2843 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2843/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2843/comments | https://api.github.com/repos/huggingface/datasets/issues/2843/events | https://github.com/huggingface/datasets/pull/2843 | 981,317,775 | MDExOlB1bGxSZXF1ZXN0NzIxMzkwODA5 | 2,843 | Fix extraction protocol inference from urls with params | {
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"merging since the windows error is just a CircleCI issue",
"It works, eg https://observablehq.com/@huggingface/datasets-preview-backend-client#{%22datasetId%22%3A%22discovery%22} and https://datasets-preview.huggingface.tech/rows?dataset=discovery&config=discovery&split=train",
"Nice !"
] | 1,630,075,257,000 | 1,630,343,509,000 | 1,630,329,121,000 | MEMBER | null | Previously it was unable to infer the compression protocol for files at URLs like
```
https://foo.bar/train.json.gz?dl=1
```
because of the query parameters.
I fixed that, this should allow 10+ datasets to work in streaming mode:
```
"discovery",
"emotion",
"grail_qa",
"guardian_authorship",
"pragmeval",
"simple_questions_v2",
"versae/adobo",
"w-nicole/childes_data",
"w-nicole/childes_data_no_tags_",
"w-nicole/childes_data_with_tags",
"w-nicole/childes_data_with_tags_"
```
cc @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/2842 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2842/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2842/comments | https://api.github.com/repos/huggingface/datasets/issues/2842/events | https://github.com/huggingface/datasets/issues/2842 | 980,725,899 | MDU6SXNzdWU5ODA3MjU4OTk= | 2,842 | always requiring the username in the dataset name when there is one | {
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"From what I can understand, you want the saved arrow file directory to have username as well instead of just dataset name if it was downloaded with the user prefix?",
"I don't think the user cares of how this is done, but the 2nd command should fail, IMHO, as its dataset name is invalid:\r\n```\r\n# first run\r\npython -c \"from datasets import load_dataset; load_dataset('stas/openwebtext-10k')\"\r\n# now run immediately\r\npython -c \"from datasets import load_dataset; load_dataset('openwebtext-10k')\"\r\n# the second command should fail, but it doesn't fail now.\r\n```\r\n\r\nMoreover, if someone were to create `openwebtext-10k` w/o the prefix, they will now get the wrong dataset, if they previously downloaded `stas/openwebtext-10k`.\r\n\r\nAnd if there are 2 users with the same dataset name `foo/ds` and `bar/ds` - currently this won't work to get the correct dataset.\r\n\r\nSo really there 3 unrelated issues hiding in the current behavior.",
"This has been fixed now, and we'll do a new release of the library today.\r\n\r\nNow the stas/openwebtext-10k dataset is cached at `.cache/huggingface/datasets/stas___openwebtext10k` and openwebtext-10k would be at `.cache/huggingface/datasets/openwebtext10k`. Since they are different, the cache won't fall back on loading the wrong one anymore.\r\n\r\nSame for the python script used to generate the dataset: stas/openwebtext-10k is cached at `.cache/huggingface/modules/datasets_modules/datasets/stas___openwebtext10k` and openwebtext-10k would be at `.cache/huggingface/modules/datasets_modules/datasets/openwebtext10k`",
"Amazing! Thank you for adding this improvement, @lhoestq!",
"(can be closed?)",
"Yes indeed :) thanks"
] | 1,630,020,713,000 | 1,634,895,815,000 | 1,634,895,815,000 | MEMBER | null | Me and now another person have been bitten by the `datasets`'s non-strictness on requiring a dataset creator's username when it's due.
So both of us started with `stas/openwebtext-10k`, somewhere along the lines lost `stas/` and continued using `openwebtext-10k` and it all was good until we published the software and things broke, since there is no `openwebtext-10k`
So this feature request is asking to tighten the checking and not allow dataset loading if it was downloaded with the user prefix, but then attempted to be used w/o it.
The same in code:
```
# first run
python -c "from datasets import load_dataset; load_dataset('stas/openwebtext-10k')"
# now run immediately
python -c "from datasets import load_dataset; load_dataset('openwebtext-10k')"
# the second command should fail, but it doesn't fail now.
```
Please let me know if I explained myself clearly.
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/2841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2841/comments | https://api.github.com/repos/huggingface/datasets/issues/2841/events | https://github.com/huggingface/datasets/issues/2841 | 980,497,321 | MDU6SXNzdWU5ODA0OTczMjE= | 2,841 | Adding GLUECoS Hinglish and Spanglish code-switching bemchmark | {
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"Hi @yjernite I am interested in adding this dataset. \r\nIn the repo they have also added a code mixed MT task from English to Hinglish [here](https://github.com/microsoft/GLUECoS#code-mixed-machine-translation-task). I think this could be a good dataset addition in itself and then I can add the rest of the GLUECoS tasks as one dataset. What do you think?"
] | 1,630,000,059,000 | 1,634,755,280,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** GLUECoS
- **Description:** a Microsoft Benchmark to evaluate code-switching for only two language pairs but a variety of tasks
- **Paper:** https://aclanthology.org/2020.acl-main.329/
- **Data:** https://github.com/microsoft/GLUECoS
- **Motivation:** We currently only have [one other](https://huggingface.co/datasets/lince) dataset for code-switching
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/2840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2840/comments | https://api.github.com/repos/huggingface/datasets/issues/2840/events | https://github.com/huggingface/datasets/issues/2840 | 980,489,074 | MDU6SXNzdWU5ODA0ODkwNzQ= | 2,840 | How can I compute BLEU-4 score use `load_metric` ? | {
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} | [] | closed | false | null | [] | null | [] | 1,629,999,397,000 | 1,630,052,004,000 | 1,630,052,004,000 | NONE | null | I have found the sacrebleu metric. But, I do not know the difference between it and BLEU-4.
If I want to compute BLEU-4 score, what can i do? | {
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https://api.github.com/repos/huggingface/datasets/issues/2839 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2839/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2839/comments | https://api.github.com/repos/huggingface/datasets/issues/2839/events | https://github.com/huggingface/datasets/issues/2839 | 980,271,715 | MDU6SXNzdWU5ODAyNzE3MTU= | 2,839 | OpenWebText: NonMatchingSplitsSizesError | {
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"Thanks for reporting, I'm updating the verifications metadata",
"I just regenerated the verifications metadata and noticed that nothing changed: the data file is fine (the checksum didn't change), and the number of examples is still 8013769. Not sure how you managed to get 7982430 examples.\r\n\r\nCan you try to delete your cache ( by default at `~/.cache/huggingface/datasets`) and try again please ?\r\nAlso, on which platform are you (linux/macos/windows) ?",
"I'll try without deleting the whole cache (we have large datasets already stored). I was under the impression that `download_mode=\"force_redownload\"` would bypass cache.\r\nSorry plateform should be linux (Redhat version 8.1)",
"Hi @thomasw21 , are you still having this issue after clearing your cache ?",
"Sorry I haven't had time to work on this. I'll close and re-open if I can't figure out why I'm having this issue. Thanks for taking a look !"
] | 1,629,985,826,000 | 1,632,233,560,000 | 1,632,233,383,000 | MEMBER | null | ## Describe the bug
When downloading `openwebtext`, I'm getting:
```
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=39769494896, num_examples=8013769, dataset_name='openwebtext'), 'recorded': SplitInfo(name='train', num_bytes=39611023912, num_examples=7982430, dataset_name='openwebtext')}]
```
I suspect that the file we download from has changed since the size doesn't look like to match with documentation
`Downloading: 0%| | 0.00/12.9G [00:00<?, ?B/s]` This suggest the total size is 12.9GB, whereas the one documented mentions `Size of downloaded dataset files: 12283.35 MB`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("openwebtext", download_mode="force_redownload")
```
## Expected results
Loading is successful
## Actual results
Loading throws above error.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.10.2
- Platform: linux (Redhat version 8.1)
- Python version: 3.8
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/2838 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2838/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2838/comments | https://api.github.com/repos/huggingface/datasets/issues/2838/events | https://github.com/huggingface/datasets/pull/2838 | 980,067,186 | MDExOlB1bGxSZXF1ZXN0NzIwMzcxMDk5 | 2,838 | Add error_bad_chunk to the JSON loader | {
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"Somebody reported the following error message which I think this is related to the goal of this PR:\r\n```Python\r\n03/24/2022 02:19:45 - INFO - __main__ - Step 5637: {'lr': 0.00018773333333333333, 'samples': 360768, 'batch_offset': 5637, 'completed_steps': 704, 'loss/train': 4.473083972930908, 'tokens/s': 6692.6176452714235}\r\n03/24/2022 02:19:46 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [1/20]\r\n03/24/2022 02:20:01 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [2/20]\r\n03/24/2022 02:20:09 - ERROR - datasets.packaged_modules.json.json - Failed to read file 'gzip://file-000000000007.json::https://huggingface.co/datasets/lvwerra/codeparrot-clean-train/resolve/1d740acb9d09cf7a3307553323e2c677a6535407/file-000000000007.json.gz' with error <class 'pyarrow.lib.ArrowInvalid'>: JSON parse error: Invalid value. in row 0\r\n03/24/2022 02:20:24 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [1/20]\r\n03/24/2022 02:20:37 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [2/20]\r\n03/24/2022 02:20:44 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [3/20]\r\n03/24/2022 02:20:49 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [4/20]\r\n03/24/2022 02:20:54 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [5/20]\r\n03/24/2022 02:20:59 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [6/20]\r\n03/24/2022 02:21:12 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [7/20]\r\n03/24/2022 02:21:20 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [8/20]\r\n03/24/2022 02:21:25 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [9/20]\r\n03/24/2022 02:21:30 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [10/20]\r\n03/24/2022 02:21:36 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [11/20]\r\n03/24/2022 02:21:41 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [12/20]\r\n03/24/2022 02:21:46 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [13/20]\r\n03/24/2022 02:21:51 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [14/20]\r\n03/24/2022 02:21:56 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [15/20]\r\n03/24/2022 02:22:01 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [16/20]\r\n03/24/2022 02:22:12 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [17/20]\r\n03/24/2022 02:22:21 - WARNING - datasets.utils.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [18/20]\r\nTraceback (most recent call last):\r\n File \"/opt/conda/lib/python3.7/site-packages/datasets/packaged_modules/json/json.py\", line 119, in _generate_tables\r\n io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)\r\n File \"pyarrow/_json.pyx\", line 246, in pyarrow._json.read_json\r\n File \"pyarrow/error.pxi\", line 143, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 99, in pyarrow.lib.check_status\r\npyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0\r\n```\r\nThis comes from the CodeParrot training script where streaming is used. When the connection fails it can happen that the JSON cannot be read anymore and then an error is thrown.\r\n\r\n",
"Yea if streaming makes a JSON unreadable then `error_bad_chunk` would help by skipping all the bad JSON data"
] | 1,629,972,452,000 | 1,648,130,408,000 | null | MEMBER | null | Add the `error_bad_chunk` parameter to the JSON loader.
Setting `error_bad_chunk=False` allows to skip an unparsable chunk of JSON data without raising an error.
Additional note:
In case of an unparsable JSON chunk, the JSON loader no longer tries to load the full JSON (which could take a lot of time in streaming mode) to get the JSON fields that the user may have forgotten to pass. Ex : for squad-like data, the user has to pass `field="data"` to tell the loader to get the list of examples from this field.
TODO: update docs
cc @lvwerra | {
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https://api.github.com/repos/huggingface/datasets/issues/2837 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2837/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2837/comments | https://api.github.com/repos/huggingface/datasets/issues/2837/events | https://github.com/huggingface/datasets/issues/2837 | 979,298,297 | MDU6SXNzdWU5NzkyOTgyOTc= | 2,837 | prepare_module issue when loading from read-only fs | {
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"Hello, I opened #2887 to fix this."
] | 1,629,904,886,000 | 1,633,456,702,000 | 1,633,456,702,000 | CONTRIBUTOR | null | ## Describe the bug
When we use prepare_module from a readonly file system, we create a FileLock using the `local_path`.
This path is not necessarily writable.
`lock_path = local_path + ".lock"`
## Steps to reproduce the bug
Run `load_dataset` on a readonly python loader file.
```python
ds = load_dataset(
python_loader, data_files={"train": train_path, "test": test_path}
)
```
where `python_loader` is a path to a file located in a readonly folder.
## Expected results
This should work I think?
## Actual results
```python
return load_dataset(
File "/usr/local/lib/python3.8/dist-packages/datasets/load.py", line 711, in load_dataset
module_path, hash, resolved_file_path = prepare_module(
File "/usr/local/lib/python3.8/dist-packages/datasets/load.py", line 465, in prepare_module
with FileLock(lock_path):
File "/usr/local/lib/python3.8/dist-packages/datasets/utils/filelock.py", line 314, in __enter__
self.acquire()
File "/usr/local/lib/python3.8/dist-packages/datasets/utils/filelock.py", line 263, in acquire
self._acquire()
File "/usr/local/lib/python3.8/dist-packages/datasets/utils/filelock.py", line 378, in _acquire
fd = os.open(self._lock_file, open_mode)
OSError: [Errno 30] Read-only file system: 'YOUR_FILE.py.lock'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.7.0
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.8
- PyArrow version: 3.0.0
| {
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https://api.github.com/repos/huggingface/datasets/issues/2836 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2836/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2836/comments | https://api.github.com/repos/huggingface/datasets/issues/2836/events | https://github.com/huggingface/datasets/pull/2836 | 979,230,142 | MDExOlB1bGxSZXF1ZXN0NzE5NjY5MDUy | 2,836 | Optimize Dataset.filter to only compute the indices to keep | {
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"Maybe worth updating the docs here as well?",
"Yup, will do !"
] | 1,629,902,482,000 | 1,631,631,113,000 | 1,631,548,221,000 | MEMBER | null | Optimize `Dataset.filter` to only compute the indices of the rows to keep, instead of creating a new Arrow table with the rows to keep. Creating a new table was an issue because it could take a lot of disk space.
This will be useful to process audio datasets for example cc @patrickvonplaten | {
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https://api.github.com/repos/huggingface/datasets/issues/2835 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2835/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2835/comments | https://api.github.com/repos/huggingface/datasets/issues/2835/events | https://github.com/huggingface/datasets/pull/2835 | 979,209,394 | MDExOlB1bGxSZXF1ZXN0NzE5NjUxOTE4 | 2,835 | Update: timit_asr - make the dataset streamable | {
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} | [] | closed | false | null | [] | null | [] | 1,629,901,369,000 | 1,631,020,547,000 | 1,631,020,546,000 | MEMBER | null | The TIMIT ASR dataset had two issues that was preventing it from being streamable:
1. it was missing a call to `open` before `pd.read_csv`
2. it was using `os.path.dirname` which is not supported for streaming
I made the dataset streamable by using `open` to load the CSV, and by adding the support for `os.path.dirname` in dataset scripts to stream data
You can now do
```python
from datasets import load_dataset
timit_asr = load_dataset("timit_asr", streaming=True)
print(next(iter(timit_asr["train"])))
```
prints:
```json
{"file": "zip://data/TRAIN/DR4/MMDM0/SI681.WAV::https://data.deepai.org/timit.zip",
"phonetic_detail": {"start": [0, 1960, 2466, 3480, 4000, 5960, 7480, 7880, 9400, 9960, 10680, 13480, 15680, 15880, 16920, 18297, 18882, 19480, 21723, 22516, 24040, 25190, 27080, 28160, 28560, 30120, 31832, 33240, 34640, 35968, 37720],
"utterance": ["h#", "w", "ix", "dcl", "s", "ah", "tcl", "ch", "ix", "n", "ae", "kcl", "t", "ix", "v", "r", "ix", "f", "y", "ux", "zh", "el", "bcl", "b", "iy", "y", "ux", "s", "f", "el", "h#"],
"stop": [1960, 2466, 3480, 4000, 5960, 7480, 7880, 9400, 9960, 10680, 13480, 15680, 15880, 16920, 18297, 18882, 19480, 21723, 22516, 24040, 25190, 27080, 28160, 28560, 30120, 31832, 33240, 34640, 35968, 37720, 39920]},
"sentence_type": "SI", "id": "SI681",
"speaker_id": "MMDM0",
"dialect_region": "DR4",
"text": "Would such an act of refusal be useful?",
"word_detail": {
"start": [1960, 4000, 9400, 10680, 15880, 18297, 27080, 30120],
"utterance": ["would", "such", "an", "act", "of", "refusal", "be", "useful"],
"stop": [4000, 9400, 10680, 15880, 18297, 27080, 30120, 37720]
}}
```
cc @patrickvonplaten @vrindaprabhu | {
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https://api.github.com/repos/huggingface/datasets/issues/2834 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2834/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2834/comments | https://api.github.com/repos/huggingface/datasets/issues/2834/events | https://github.com/huggingface/datasets/pull/2834 | 978,309,749 | MDExOlB1bGxSZXF1ZXN0NzE4OTE5NjQ0 | 2,834 | Fix IndexError by ignoring empty RecordBatch | {
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} | [] | closed | false | null | [] | null | [] | 1,629,824,773,000 | 1,629,825,678,000 | 1,629,825,678,000 | MEMBER | null | We need to ignore the empty record batches for the interpolation search to work correctly when querying arrow tables
Close #2833
cc @SaulLu | {
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https://api.github.com/repos/huggingface/datasets/issues/2833 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2833/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2833/comments | https://api.github.com/repos/huggingface/datasets/issues/2833/events | https://github.com/huggingface/datasets/issues/2833 | 978,296,140 | MDU6SXNzdWU5NzgyOTYxNDA= | 2,833 | IndexError when accessing first element of a Dataset if first RecordBatch is empty | {
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] | null | [] | 1,629,823,760,000 | 1,629,825,677,000 | 1,629,825,677,000 | MEMBER | null | The computation of the offsets of the underlying Table of a Dataset has some issues if the first RecordBatch is empty.
```python
from datasets import Dataset
import pyarrow as pa
pa_table = pa.Table.from_pydict({"a": [1]})
pa_table2 = pa.Table.from_pydict({"a": []}, schema=pa_table.schema)
ds_table = pa.concat_tables([pa_table2, pa_table])
dataset = Dataset(ds_table)
print([len(b) for b in dataset.data._batches])
# [0, 1]
print(dataset.data._offsets)
# [0 0 1] (should be [0, 1])
dataset[0]
```
raises
```python
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/datasets/table.py in _interpolation_search(arr, x)
90 else:
91 i, j = i, k
---> 92 raise IndexError(f"Invalid query '{x}' for size {arr[-1] if len(arr) else 'none'}.")
93
94
IndexError: Invalid query '0' for size 1.
```
This can be fixed by ignoring empty batches when computing `table._batches` and `table._offsets`
cc @SaulLu | {
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https://api.github.com/repos/huggingface/datasets/issues/2832 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2832/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2832/comments | https://api.github.com/repos/huggingface/datasets/issues/2832/events | https://github.com/huggingface/datasets/issues/2832 | 978,012,800 | MDU6SXNzdWU5NzgwMTI4MDA= | 2,832 | Logging levels not taken into account | {
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] | open | false | null | [] | null | [
"I just take a look at all the outputs produced by `datasets` using the different log-levels.\r\nAs far as i can tell using `datasets==1.17.0` they overall issue seems to be fixed.\r\n\r\nHowever, I noticed that there is one tqdm based progress indicator appearing on STDERR that I can simply not suppress.\r\n```\r\nResolving data files: 100%|ββββββββββ| 652/652 [00:00<00:00, 1604.52it/s]\r\n```\r\n\r\nAccording to _get_origin_metadata_locally_or_by_urls it shold be supressable by using the `NOTSET` log-level\r\nhttps://github.com/huggingface/datasets/blob/1406a04c3e911cec2680d8bc513653e0cafcaaa4/src/datasets/data_files.py#L491-L501\r\nSadly when specifiing the log-level `NOTSET` it seems to has no effect.\r\n\r\nBut appart from it not having any effect I must admit that it seems unintuitive to me.\r\nI would suggest changing this such that it is only shown when the log-level is greater or equal to INFO.\r\n\r\nThis would conform better to INFO according to the [documentation](https://huggingface.co/docs/datasets/v1.0.0/package_reference/logging_methods.html#datasets.logging.set_verbosity_info).\r\n> This will display most of the logging information and tqdm bars.\r\n\r\nAny inputs on this?\r\nI will be happy to supply a PR if desired π ",
"Hi! This should disable the tqdm output:\r\n```python\r\nimport datasets\r\ndatasets.set_progress_bar_enabled(False)\r\n```\r\n\r\nOn a side note: I believe the issue with logging (not tqdm) is still relevant on master."
] | 1,629,805,841,000 | 1,642,601,685,000 | null | MEMBER | null | ## Describe the bug
The `logging` module isn't working as intended relative to the levels to set.
## Steps to reproduce the bug
```python
from datasets import logging
logging.set_verbosity_debug()
logger = logging.get_logger()
logger.error("ERROR")
logger.warning("WARNING")
logger.info("INFO")
logger.debug("DEBUG"
```
## Expected results
I expect all logs to be output since I'm putting a `debug` level.
## Actual results
Only the two first logs are output.
## Environment info
- `datasets` version: 1.11.0
- Platform: Linux-5.13.9-arch1-1-x86_64-with-glibc2.33
- Python version: 3.9.6
- PyArrow version: 5.0.0
## To go further
This logging issue appears in `datasets` but not in `transformers`. It happens because there is no handler defined for the logger. When no handler is defined, the `logging` library will output a one-off error to stderr, using a `StderrHandler` with level `WARNING`.
`transformers` sets a default `StreamHandler` [here](https://github.com/huggingface/transformers/blob/5c6eca71a983bae2589eed01e5c04fcf88ba5690/src/transformers/utils/logging.py#L86) | {
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https://api.github.com/repos/huggingface/datasets/issues/2831 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2831/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2831/comments | https://api.github.com/repos/huggingface/datasets/issues/2831/events | https://github.com/huggingface/datasets/issues/2831 | 977,864,600 | MDU6SXNzdWU5Nzc4NjQ2MDA= | 2,831 | ArrowInvalid when mapping dataset with missing values | {
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] | open | false | null | [] | null | [
"Hi ! It fails because of the feature type inference.\r\n\r\nBecause the first 1000 examples all have null values in the \"match\" field, then it infers that the type for this field is `null` type before writing the data on disk. But as soon as it tries to map an example with a non-null \"match\" field, then it fails.\r\n\r\nTo fix that you can either:\r\n- increase the writer_batch_size to >2000 (default is 1000) so that some non-null values will be in the first batch written to disk\r\n```python\r\ndatasets = datasets.map(lambda e: {'labels': e['match']}, remove_columns=['id'], writer_batch_size=2000)\r\n```\r\n- OR force the feature type with:\r\n```python\r\nfrom datasets import Features, Value\r\n\r\nfeatures = Features({\r\n 'conflict': Value('int64'),\r\n 'date': Value('string'),\r\n 'headline': Value('string'),\r\n 'match': Value('float64'),\r\n 'label': Value('float64')\r\n})\r\ndatasets = datasets.map(lambda e: {'labels': e['match']}, remove_columns=['id'], features=features)\r\n```"
] | 1,629,795,042,000 | 1,630,419,334,000 | null | NONE | null | ## Describe the bug
I encountered an `ArrowInvalid` when mapping dataset with missing values.
Here are the files for a minimal example. The exception is only thrown when the first line in the csv has a missing value (if you move the last line to the top it isn't thrown).
[data_small.csv](https://github.com/huggingface/datasets/files/7037838/data_small.csv)
[data.csv](https://github.com/huggingface/datasets/files/7037842/data.csv)
## Steps to reproduce the bug
```python
from datasets import load_dataset
datasets = load_dataset("csv", data_files=['data_small.csv'])
datasets = datasets.map(lambda e: {'labels': e['match']},
remove_columns=['id'])
```
## Expected results
No error
## Actual results
```
File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Invalid null value
```
## Environment info
- `datasets` version: 1.5.0
- Platform: Linux-5.11.0-25-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyTorch version (GPU?): 1.7.1+cpu (False)
- Tensorflow version (GPU?): 2.4.1 (False)
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
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https://api.github.com/repos/huggingface/datasets/issues/2830 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2830/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2830/comments | https://api.github.com/repos/huggingface/datasets/issues/2830/events | https://github.com/huggingface/datasets/pull/2830 | 977,563,947 | MDExOlB1bGxSZXF1ZXN0NzE4MjkyMTM2 | 2,830 | Add imagefolder dataset | {
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} | [] | closed | false | null | [] | null | [
"@lhoestq @albertvillanova it would be super cool if we could get the Image Classification task to work with this. I'm not sure how to have the dataset find the unique label names _after_ the dataset has been loaded. Is that even possible? \r\n\r\nMy hacky community version [here](https://huggingface.co/datasets/nateraw/image-folder) does this, but it wouldn't pass the test suite here. Any thoughts?",
"Hi ! Dataset builders that require some `data_files` like `csv` or `json` are handled differently that actual dataset scripts.\r\n\r\nIn particular:\r\n- they are placed directly in the `src` folder of the lib so that you can use it without internet connection (more exactly in `src/datasets/packaged_modules/<builder_name>.py`). So feel free to move the dataset python file there. You also need to register it in `src/datasets/packaked_modules.__init__.py`\r\n- they are handled a bit differently in our test suite (see the `PackagedDatasetTest` class in `test_dataset_common.py`). To be able to test the builder with your dummy data, you just need to modify `get_packaged_dataset_dummy_data_files` in `test_dataset_common.py` to return the right `data_files` for your builder. The dummy data can stay in `datasets/image_folder/dummy`\r\n\r\nLet me know if you have questions or if I can help !",
"Hey @lhoestq , I actually already did both of those things. I'm trying to get the `image-classification` task to work now. \r\n\r\nFor example...When you run `ds = load_dataset('imagefolder', data_files='my_files')`, with a directory called `./my_files` that looks like this:\r\n\r\n```\r\nmy_files\r\n----| Cat\r\n--------| image1.jpg\r\n--------| ...\r\n----| Dog\r\n--------| image1.jpg\r\n--------| ...\r\n```\r\n\r\n...We should set the dataset's `labels` feature to `datasets.features.ClassLabel(names=['cat', 'dog'])` dynamically with class names we find by getting a list of directories in `my_files` (via `data_files`). Otherwise the `datasets.tasks.ImageClassification` task will break, as the `labels` feature is not a `ClassLabel`.\r\n\r\nI couldn't figure out how to access the `data_files` in the builder's `_info` function in a way that would pass in the test suite. ",
"Nice ! Then maybe you can use `self.config.data_files` in `_info()` ?\r\nWhat error are you getting in the test suite ?\r\n\r\nAlso note that `data_files` was first developed to accept paths to actual files, not directories. In particular, it fetches the metadata of all the data_files to get a unique hash for the caching mechanism. So we may need to do a few changes first.",
"I'm trying to make it work by getting the label names in the _info automatically.\r\nI'll let you know tomorrow how it goes :)\r\n\r\nAlso cc @mariosasko since we're going to use #3163 \r\n\r\nRight now I'm getting the label name per file by taking the first word (from regex `\\w+`) after the common prefix of all the files per split",
"Data files resolution takes too much time on my side for a dataset of a few 10,000s of examples. I'll speed it up with some multihreading tomorrow, and maybe by removing the unnecessary checksum verification",
"The code is a bit ugly for my taste. I'll try to simplify it tomorrow by avoiding the `os.path.commonprefix` computation and do something similar to @nateraw's ImageFolder instead, where only the second-to-last path component is considered a label (and see if I can update the class labels lazily in `_generate_examples`).\r\n\r\nAlso, as discussed offline with @lhoestq, I reverted the automatic directory globbing change in `data_files.py` and will investigate if we can use `data_dir` for that (e.g. `load_dataset(\"imagefolder\", data_dir=\"path/to/data\")` would be equal to `load_dataset(\"imagefolder\", data_files=[\"path/to/data/**/*\", \"path/to/data/*\"])`. The only problem with `data_dir` that it's equal to `dl_manager.manual_dir`, which would break scripts with `manul_download_instructions`, so maybe we can limit this behavior only to the packaged loaders? WDYT?",
"An updated example of usage: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1zJkAQm0Dk372EHcBq6hYgHuunsK4rR0r?usp=sharing)",
"> The code is a bit ugly for my taste. I'll try to simplify it tomorrow by avoiding the os.path.commonprefix computation and do something similar to @nateraw's ImageFolder instead, where only the second-to-last path component is considered a label (and see if I can update the class labels lazily in _generate_examples).\r\n\r\nSounds good ! It's fine if we just support the same format as pytorch ImageFolder.\r\n\r\nRegarding the `data_dir` parameter, what do you think is best ?\r\n\r\n1. `dl_manager.data_dir = data_dir`\r\n2. `dl_manager.data_files = resolve(os.path.join(data_dir, \"**\"))`\r\n\r\nor something else ?\r\n\r\n> The only problem with data_dir that it's equal to dl_manager.manual_dir, which would break scripts with manul_download_instructions, so maybe we can limit this behavior only to the packaged loaders? WDYT?\r\n\r\nWe can still have `dl_manager.manual_dir = data_dir` though",
"The example colab is amazing !",
"@lhoestq \r\n>Regarding the `data_dir` parameter, what do you think is best ?\r\n>\r\n>1. `dl_manager.data_dir = data_dir`\r\n>2. `dl_manager.data_files = resolve(os.path.join(data_dir, \"**\"))`\r\n\r\nThe second option. Basically, I would like `data_files` to be equal to:\r\n```python\r\ndef _split_generators(self, dl_manager):\r\n data_files = self.config.data_files\r\n if data_files is None: \r\n data_files = glob.glob(\"{self.config.data_dir}/**\", recursive=True)\r\n else:\r\n raise ValueError(f\"At least one data file must be specified, but got data_files={data_files}\")\r\n```\r\nin the scripts of packaged modules. It's probably better to do the resolution in `data_files.py` tho (to handle relative file paths on the Hub, for instance)",
"> The second option. Basically, I would like data_files to be equal to:\r\n> ```python\r\n> def _split_generators(self, dl_manager):\r\n> data_files = self.config.data_files\r\n> if data_files is None: \r\n> data_files = glob.glob(\"{self.config.data_dir}/**\", recursive=True)\r\n> else:\r\n> raise ValueError(f\"At least one data file must be specified, but got data_files={data_files}\")\r\n> ```\r\n> in the scripts of packaged modules. It's probably better to do the resolution in data_files.py tho (to handle relative file paths on the Hub, for instance)\r\n\r\nsounds good !",
"π",
"Hey @mariosasko are we still actually able to load an image folder?\r\n\r\nFor example...\r\n\r\n```\r\n! wget https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip\r\n! unzip kagglecatsanddogs_3367a.zip\r\n```\r\n\r\nfollowed by\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\n# Does not work\r\nds = load_dataset('imagefolder', data_files='/PetImages')\r\n\r\n# Also doesn't work\r\nds = load_dataset('imagefolder', data_dir='/PetImages')\r\n```\r\n\r\nAre we going forward with the assumption that the user always wants to download from URL and that they won't have a dataset locally already? This at least gets us part of the way, but is technically not an \"imagefolder\" as intended. \r\n\r\nEither way, was delighted to see the colab notebook work smoothly outside of the case I just described above. β€οΈ thanks so much for the work here.",
"> Hey @mariosasko are we still actually able to load an image folder?\r\n> \r\n> For example...\r\n> \r\n> ```\r\n> ! wget https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip\r\n> ! unzip kagglecatsanddogs_3367a.zip\r\n> ```\r\n> \r\n> followed by\r\n> \r\n> ```python\r\n> from datasets import load_dataset\r\n> \r\n> # Does not work\r\n> ds = load_dataset('imagefolder', data_files='/PetImages')\r\n\r\nI ran into this too when I was trying to out. At the moment you can still load from a local on disk directory using a glob pattern i.e. \r\n\r\n```python\r\nfrom datasets import load_dataset\r\nds = load_dataset(\"imagefolder\", data_files=\"PetImages/**/*\")\r\n```\r\n[Colab example](https://colab.research.google.com/drive/1IvAyYSAADHphzbtJMt02OXmnGwGtku3k?usp=sharing). I'm not sure if that is the intended behaviour or not. If it is, I think it would be good to document this because I also assumed the approach @nateraw used would work."
] | 1,629,761,646,000 | 1,646,152,184,000 | 1,646,152,184,000 | CONTRIBUTOR | null | A generic imagefolder dataset inspired by `torchvision.datasets.ImageFolder`.
Resolves #2508
---
Example Usage:
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/gist/nateraw/954fa8cba4ff806f6147a782fa9efd1a/imagefolder-official-example.ipynb) | {
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] | null | [] | 1,629,737,800,000 | 1,634,032,949,000 | null | MEMBER | null | Hi ! As you know TAR has some constraints for data streaming. While it is optimized for buffering, the files in the TAR archive **need to be streamed in order**. It means that we can't choose which file to stream from, and this notation is to be avoided for TAR archives:
```
tar://books_large_p1.txt::https://storage.googleapis.com/huggingface-nlp/datasets/bookcorpus/bookcorpus.tar.bz2
```
Instead, I suggest we implement `iter_archive` for the `StreamingDownloadManager`.
The regular `DownloadManager` already has it.
Then we will have to update the json/txt/csv/etc. loaders to make them use `iter_archive` on TAR archives.
That's also what Tensorflow Datasets is doing in this case.
See this [dataset](https://github.com/tensorflow/datasets/blob/93895059c80a9e05805e8f32a2e310f66a23fc98/tensorflow_datasets/image_classification/flowers.py) for example.
Therefore instead of doing
```python
uncompressed = dl_manager.extract(tar_archive)
filename = "books_large_p1.txt"
with open(os.path.join(uncompressed, filename)) as f:
for line in f:
...
```
we'll do
```python
for filename, f in dl_manager.iter_archive(tar_archive):
for line in f:
...
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/2828 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2828/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2828/comments | https://api.github.com/repos/huggingface/datasets/issues/2828/events | https://github.com/huggingface/datasets/pull/2828 | 977,181,517 | MDExOlB1bGxSZXF1ZXN0NzE3OTYwODg3 | 2,828 | Add code-mixed Kannada Hope speech dataset | {
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} | [] | closed | false | null | [] | null | [] | 1,629,734,109,000 | 1,633,108,863,000 | 1,633,108,863,000 | CONTRIBUTOR | null | ## Adding a Dataset
- **Name:** *KanHope*
- **Description:** *A code-mixed English-Kannada dataset for Hope speech detection*
- **Paper:** *https://arxiv.org/abs/2108.04616*
- **Data:** *https://github.com/adeepH/KanHope/tree/main/dataset*
- **Motivation:** *The dataset is amongst the very few resources available for code-mixed low-resourced Dravidian languages of India* | {
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https://api.github.com/repos/huggingface/datasets/issues/2827 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2827/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2827/comments | https://api.github.com/repos/huggingface/datasets/issues/2827/events | https://github.com/huggingface/datasets/pull/2827 | 976,976,552 | MDExOlB1bGxSZXF1ZXN0NzE3Nzg3MjEw | 2,827 | add a text classification dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2826 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2826/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2826/comments | https://api.github.com/repos/huggingface/datasets/issues/2826/events | https://github.com/huggingface/datasets/issues/2826 | 976,974,254 | MDU6SXNzdWU5NzY5NzQyNTQ= | 2,826 | Add a Text Classification dataset: KanHope | {
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"Hi ! In your script it looks like you're trying to load the dataset `bn_hate_speech,`, not KanHope.\r\n\r\nMoreover the error `KeyError: ' '` means that you have a feature of type ClassLabel, but for a certain example of the dataset, it looks like the label is empty (it's just a string with a space). Can you make sure that the data don't have missing labels, and that your dataset script parses the labels correctly ?"
] | 1,629,721,318,000 | 1,633,111,619,000 | 1,633,111,619,000 | CONTRIBUTOR | null | ## Adding a Dataset
- **Name:** *KanHope*
- **Description:** *A code-mixed English-Kannada dataset for Hope speech detection*
- **Paper:** *https://arxiv.org/abs/2108.04616* (I am the author of the paper}
- **Author:** *[AdeepH](https://github.com/adeepH)*
- **Data:** *https://github.com/adeepH/KanHope/tree/main/dataset*
- **Motivation:** *The dataset is amongst the very few resources available for code-mixed Dravidian languages*
- I tried following the steps as per the instructions. However, could not resolve an error. Any help would be appreciated.
- The dataset card and the scripts for the dataset *https://github.com/adeepH/datasets/tree/multilingual-hope-speech/datasets/mhs_eval*
```
Using custom data configuration default
Downloading and preparing dataset bn_hate_speech/default (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/bn_hate_speech/default/0.0.0/5f417ddc89777278abd29988f909f39495f0ec802090f7d8fa63b5bffb121762...
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-114-4a9cdb519e4c> in <module>()
1 from datasets import load_dataset
2
----> 3 data = load_dataset('/content/bn')
9 frames
/usr/local/lib/python3.7/dist-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, streaming, **config_kwargs)
850 ignore_verifications=ignore_verifications,
851 try_from_hf_gcs=try_from_hf_gcs,
--> 852 use_auth_token=use_auth_token,
853 )
854
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
614 if not downloaded_from_gcs:
615 self._download_and_prepare(
--> 616 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
617 )
618 # Sync info
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
691 try:
692 # Prepare split will record examples associated to the split
--> 693 self._prepare_split(split_generator, **prepare_split_kwargs)
694 except OSError as e:
695 raise OSError(
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _prepare_split(self, split_generator)
1107 disable=bool(logging.get_verbosity() == logging.NOTSET),
1108 ):
-> 1109 example = self.info.features.encode_example(record)
1110 writer.write(example, key)
1111 finally:
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_example(self, example)
1015 """
1016 example = cast_to_python_objects(example)
-> 1017 return encode_nested_example(self, example)
1018
1019 def encode_batch(self, batch):
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_nested_example(schema, obj)
863 if isinstance(schema, dict):
864 return {
--> 865 k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
866 }
867 elif isinstance(schema, (list, tuple)):
/usr/local/lib/python3.7/dist-packages/datasets/features.py in <dictcomp>(.0)
863 if isinstance(schema, dict):
864 return {
--> 865 k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
866 }
867 elif isinstance(schema, (list, tuple)):
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_nested_example(schema, obj)
890 # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks
891 elif isinstance(schema, (ClassLabel, TranslationVariableLanguages, Value, _ArrayXD)):
--> 892 return schema.encode_example(obj)
893 # Other object should be directly convertible to a native Arrow type (like Translation and Translation)
894 return obj
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_example(self, example_data)
665 # If a string is given, convert to associated integer
666 if isinstance(example_data, str):
--> 667 example_data = self.str2int(example_data)
668
669 # Allowing -1 to mean no label.
/usr/local/lib/python3.7/dist-packages/datasets/features.py in str2int(self, values)
623 if value not in self._str2int:
624 value = str(value).strip()
--> 625 output.append(self._str2int[str(value)])
626 else:
627 # No names provided, try to integerize
KeyError: ' '
``` | {
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"This also happened to me on COLAB.\r\nDetails:\r\nI ran the `run_mlm.py` in two different notebooks. \r\nIn the first notebook, I do tokenization since I can get 4 CPU cores without any GPUs, and save the cache into a folder which I copy to drive.\r\nIn the second notebook, I copy the cache folder from drive and re-run the run_mlm.py script (this time I uncomment the trainer code which happens after the tokenization)\r\n\r\nNote: I didn't change anything in the arguments, not even the preprocessing_num_workers\r\n ",
"Thanks for reporting ! This is indeed a bug, I'm looking into it",
"#2854 fixed the issue :)\r\n\r\nWe'll do a new release of `datasets` soon to make the fix available.\r\nIn the meantime, feel free to try it out by installing `datasets` from source\r\n\r\nIf you have other issues or any question, feel free to re-open the issue :)"
] | 1,629,689,017,000 | 1,630,415,681,000 | 1,630,415,616,000 | NONE | null | ## Describe the bug
The datasets.map function caches the processed data to a certain directory. When the map function is called another time with totally the same parameters, the cached data are supposed to be reloaded instead of re-processing. However, it doesn't reuse cached data sometimes. I use the common data processing in different tasks, the datasets are processed again, the only difference is that I run them in different files.
## Steps to reproduce the bug
Just run the following codes in different .py files.
```python
if __name__ == '__main__':
from datasets import load_dataset
from transformers import AutoTokenizer
raw_datasets = load_dataset("wikitext", "wikitext-2-raw-v1")
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
def tokenize_function(examples):
return tokenizer(examples["text"], padding="max_length", truncation=True)
tokenized_datasets = raw_datasets.map(tokenize_function, batched=True)
```
## Expected results
The map function should reload data in the second or any later runs.
## Actual results
The processing happens in each run.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: linux
- Python version: 3.7.6
- PyArrow version: 3.0.0
This is the first time I report a bug. If there is any problem or confusing description, please let me know π.
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https://api.github.com/repos/huggingface/datasets/issues/2824 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2824/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2824/comments | https://api.github.com/repos/huggingface/datasets/issues/2824/events | https://github.com/huggingface/datasets/pull/2824 | 976,394,721 | MDExOlB1bGxSZXF1ZXN0NzE3MzIyMzY5 | 2,824 | Fix defaults in cache_dir docstring in load.py | {
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https://api.github.com/repos/huggingface/datasets/issues/2823 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2823/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2823/comments | https://api.github.com/repos/huggingface/datasets/issues/2823/events | https://github.com/huggingface/datasets/issues/2823 | 976,135,355 | MDU6SXNzdWU5NzYxMzUzNTU= | 2,823 | HF_DATASETS_CACHE variable in Windows | {
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"Agh - I'm a muppet. No quote marks are needed.\r\nset HF_DATASETS_CACHE = C:\\Datasets\r\nworks as intended."
] | 1,629,551,864,000 | 1,629,552,011,000 | 1,629,552,011,000 | NONE | null | I can't seem to use a custom Cache directory in Windows. I have tried:
set HF_DATASETS_CACHE = "C:\Datasets"
set HF_DATASETS_CACHE = "C:/Datasets"
set HF_DATASETS_CACHE = "C:\\Datasets"
set HF_DATASETS_CACHE = "r'C:\Datasets'"
set HF_DATASETS_CACHE = "\Datasets"
set HF_DATASETS_CACHE = "/Datasets"
In each instance I get the "[WinError 123] The filename, directory name, or volume label syntax is incorrect" error when attempting to load a dataset | {
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