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This PR:
- Extends `tagset_validator` to support regex tags
- Uses `tagset_validator` to validate dict `source_datasets` | {
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- `other-stuctured-to-text` (before)
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- [ ] #2526
- [x] #1842
- [ ] #1810
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
@VictorSanh feel free to add and sort by priority any interesting dataset. I have added the multimodal dataset requests which were already present as issues. | {
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Currently, task tags are either exclusively related to text or speech processing:
- https://github.com/huggingface/datasets/blob/master/src/datasets/utils/resources/tasks.json
## **Describe the solution you'd like**
We should also add tasks related to:
- multimodality
- image
- video
CC: @VictorSanh @lewtun @lhoestq @merveenoyan @SBrandeis | {
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Fix #3361 | {
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* adapts the ImageClassification template to use the new Image feature
* adapts the following datasets to use the new Image feature:
* beans (+ fixes streaming)
* cast_vs_dogs (+ fixes streaming)
* cifar10
* cifar100
* fashion_mnist
* mnist
* head_qa
cc @nateraw | {
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https://api.github.com/repos/huggingface/datasets/issues/3361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3361/comments | https://api.github.com/repos/huggingface/datasets/issues/3361/events | https://github.com/huggingface/datasets/issues/3361 | 1,068,736,268 | I_kwDODunzps4_s58M | 3,361 | Jeopardy _URL access denied | {
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"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
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] | closed | false | null | [] | null | 1 | "2021-12-01T18:21:33Z" | "2021-12-11T12:50:23Z" | "2021-12-06T11:16:31Z" | CONTRIBUTOR | null | null | null | ## Describe the bug
http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz returns Access Denied now.
However, https://drive.google.com/file/d/0BwT5wj_P7BKXb2hfM3d2RHU1ckE/view?usp=sharing from the original Reddit post https://www.reddit.com/r/datasets/comments/1uyd0t/200000_jeopardy_questions_in_a_json_file/ may work.
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
```
```python
>>> from datasets import load_dataset
>>> load_dataset("jeopardy")
```
## Expected results
The download completes.
## Actual results
```shell
Downloading: 4.18kB [00:00, 1.60MB/s]
Downloading: 2.03kB [00:00, 1.04MB/s]
Using custom data configuration default
Downloading and preparing dataset jeopardy/default (download: 12.13 MiB, generated: 34.46 MiB, post-processed: Unknown size, total: 46.59 MiB) to /Users/mike/.cache/huggingface/datasets/jeopardy/default/0.1.0/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/load.py", line 1632, in load_dataset
use_auth_token=use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 608, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/mike/.cache/huggingface/modules/datasets_modules/datasets/jeopardy/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810/jeopardy.py", line 72, in _split_generators
filepath = dl_manager.download_and_extract(_DATA_URL)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 197, in download
download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, disable_tqdm=False
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 197, in map_nested
return function(data_struct)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 305, in cached_path
use_auth_token=download_config.use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
---
```shell
> curl http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
```xml
<?xml version="1.0" encoding="UTF-8"?>
<Error><Code>AccessDenied</Code><Message>Access Denied</Message><RequestId>70Y9R36XNPEQXMGV</RequestId><HostId>G6F5AK4qo7JdaEdKGMtS0P6gdLPeFOdEfSEfvTOZEfk9km0/jAfp08QLfKSTFFj1oWIKoAoBehM=</HostId></Error>
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.14.0
- Platform: macOS Catalina 10.15.7
- Python version: 3.7.12
- PyArrow version: 6.0.1
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- USPTO subset of The Pile: "uspto" config
Close bigscience-workshop/data_tooling#297.
CC: @StellaAthena | {
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- Free Law subset of The Pile: "free_law" config
Close bigscience-workshop/data_tooling#75.
CC: @StellaAthena | {
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} | [] | closed | false | null | [] | null | 2 | "2021-12-01T16:35:38Z" | "2021-12-02T02:26:22Z" | "2021-12-02T02:26:22Z" | NONE | null | null | null | after adding new field **tokenized_examples["example_id"]**, and get errors below,
I think it is due to changing data to tensor, and **tokenized_examples["example_id"]** is string list
**all fields**
```
***************** train_dataset 1: Dataset({
features: ['attention_mask', 'end_positions', 'example_id', 'input_ids', 'start_positions', 'token_type_ids'],
num_rows: 87714
})
```
**Errors**
```
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py", line 705, in convert_to_tensors
tensor = as_tensor(value)
ValueError: too many dimensions 'str'
``` | {
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As far as I know, it is solely in English (en-US). There are only a few mails in Spanish, French or German (less than a dozen I would estimate). | {
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- A collator is always required (there was way too much hackiness making things like labels work without it)
- Lots of cleanup and a lot of code moved to `_get_output_signature`
- Should now handle it gracefully when the data collator adds unexpected columns | {
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} | This PR fixes error:
```
ValueError: Cannot seek streaming HTTP file
```
CC: @severo | {
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- ajgt_twitter_ar
- emotone_ar | {
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```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0]], device='cuda:0'), 'end_positions': tensor([ 25, 97, 93, 44, 25, 112, 109, 134], device='cuda:0'), 'input_ids': tensor([[ 101, 2054, 2390, ..., 0, 0, 0],
[ 101, 2054, 2515, ..., 0, 0, 0],
[ 101, 2054, 2106, ..., 0, 0, 0],
...,
[ 101, 2339, 2001, ..., 0, 0, 0],
[ 101, 2054, 2515, ..., 0, 0, 0],
[ 101, 2054, 2003, ..., 0, 0, 0]], device='cuda:0'), 'start_positions': tensor([ 20, 90, 89, 41, 25, 96, 106, 132], device='cuda:0'), 'token_type_ids': tensor([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]], device='cuda:0')}
```
```
# This function preprocesses a question answering dataset, tokenizing the question and context text
# and finding the right offsets for the answer spans in the tokenized context (to use as labels).
# Adapted from https://github.com/huggingface/transformers/blob/master/examples/pytorch/question-answering/run_qa.py
def prepare_train_dataset_qa(examples, tokenizer, max_seq_length=None):
questions = [q.lstrip() for q in examples["question"]]
max_seq_length = tokenizer.model_max_length
# tokenize both questions and the corresponding context
# if the context length is longer than max_length, we split it to several
# chunks of max_length
tokenized_examples = tokenizer(
questions,
examples["context"],
truncation="only_second",
max_length=max_seq_length,
stride=min(max_seq_length // 2, 128),
return_overflowing_tokens=True,
return_offsets_mapping=True,
padding="max_length"
)
# Since one example might give us several features if it has a long context,
# we need a map from a feature to its corresponding example.
sample_mapping = tokenized_examples.pop("overflow_to_sample_mapping")
# The offset mappings will give us a map from token to character position
# in the original context. This will help us compute the start_positions
# and end_positions to get the final answer string.
offset_mapping = tokenized_examples.pop("offset_mapping")
tokenized_examples["start_positions"] = []
tokenized_examples["end_positions"] = []
tokenized_examples["example_id"] = []
for i, offsets in enumerate(offset_mapping):
input_ids = tokenized_examples["input_ids"][i]
# We will label features not containing the answer the index of the CLS token.
cls_index = input_ids.index(tokenizer.cls_token_id)
sequence_ids = tokenized_examples.sequence_ids(i)
# from the feature idx to sample idx
sample_index = sample_mapping[i]
# get the answer for a feature
answers = examples["answers"][sample_index]
tokenized_examples["example_id"].append(examples["id"][sample_index])
if len(answers["answer_start"]) == 0:
tokenized_examples["start_positions"].append(cls_index)
tokenized_examples["end_positions"].append(cls_index)
else:
# Start/end character index of the answer in the text.
start_char = answers["answer_start"][0]
end_char = start_char + len(answers["text"][0])
# Start token index of the current span in the text.
token_start_index = 0
while sequence_ids[token_start_index] != 1:
token_start_index += 1
# End token index of the current span in the text.
token_end_index = len(input_ids) - 1
while sequence_ids[token_end_index] != 1:
token_end_index -= 1
# Detect if the answer is out of the span (in which case this feature is labeled with the CLS index).
if not (offsets[token_start_index][0] <= start_char and
offsets[token_end_index][1] >= end_char):
tokenized_examples["start_positions"].append(cls_index)
tokenized_examples["end_positions"].append(cls_index)
else:
# Otherwise move the token_start_index and token_end_index to the two ends of the answer.
# Note: we could go after the last offset if the answer is the last word (edge case).
while token_start_index < len(offsets) and \
offsets[token_start_index][0] <= start_char:
token_start_index += 1
tokenized_examples["start_positions"].append(
token_start_index - 1)
while offsets[token_end_index][1] >= end_char:
token_end_index -= 1
tokenized_examples["end_positions"].append(token_end_index + 1)
return tokenized_examples
```
_Originally posted by @yanllearnn in https://github.com/huggingface/datasets/issues/3333#issuecomment-983457161_ | {
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Related to: #3350. | {
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} | This PR will fix streaming of datasets served with gzip content-encoding:
```
ClientPayloadError: 400, message='Can not decode content-encoding: gzip'
```
Fix #2918.
CC: @severo | {
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} | In order to properly locate downloaded ckpt files key name needs to match filename. Correcting change introduced in #3235 | {
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} | [] | closed | false | null | [] | null | 1 | "2021-11-30T22:34:17Z" | "2021-12-04T00:22:22Z" | "2021-12-04T00:22:11Z" | CONTRIBUTOR | null | 0 | {
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} | * In this PR, I added the option to iterate through zipfiles for `download_manager.py` only.
* Next PR will be the same applied to `streaming_download_manager.py`.
* Related issue #3272.
## Comments :
* There is no `.isreg()` equivalent in zipfile library to check if file is Regular so I used `.is_dir()` instead to skip directories.
* For now I got `streaming_download_manager.py` working for local zip files, but not for urls. I get the following error when I test it on an archive in google drive, so still working on it. `BlockSizeError: Got more bytes so far (>2112) than requested (22)`
## Tasks :
- [x] download_manager.py
- [ ] streaming_download_manager.py | {
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] | null | 2 | "2021-11-30T20:11:42Z" | "2021-12-14T14:39:05Z" | "2021-12-14T14:39:05Z" | CONTRIBUTOR | null | null | null | ## Describe the bug
Loading QED was fine until 1.15.0.
related: bigscience-workshop/promptsource#659, bigscience-workshop/promptsource#670
Not sure where the root cause is, but here are some candidates:
- #3158
- #3120
- #3196
- #2891
## Steps to reproduce the bug
```python
load_dataset("qed")
```
## Expected results
Loading completed.
## Actual results
```shell
ArrowInvalid: Could not convert in with type str: tried to convert to boolean
Traceback:
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/streamlit/script_runner.py", line 354, in _run_script
exec(code, module.__dict__)
File "/Users/s0s0cr3/Documents/GitHub/promptsource/promptsource/app.py", line 260, in <module>
dataset = get_dataset(dataset_key, str(conf_option.name) if conf_option else None)
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/streamlit/caching.py", line 543, in wrapped_func
return get_or_create_cached_value()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/streamlit/caching.py", line 527, in get_or_create_cached_value
return_value = func(*args, **kwargs)
File "/Users/s0s0cr3/Documents/GitHub/promptsource/promptsource/utils.py", line 49, in get_dataset
builder_instance.download_and_prepare()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/builder.py", line 1106, in _prepare_split
num_examples, num_bytes = writer.finalize()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/arrow_writer.py", line 456, in finalize
self.write_examples_on_file()
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/arrow_writer.py", line 325, in write_examples_on_file
pa_array = pa.array(typed_sequence)
File "pyarrow/array.pxi", line 222, in pyarrow.lib.array
File "pyarrow/array.pxi", line 110, in pyarrow.lib._handle_arrow_array_protocol
File "/Users/s0s0cr3/Library/Python/3.9/lib/python/site-packages/datasets/arrow_writer.py", line 121, in __arrow_array__
out = pa.array(cast_to_python_objects(self.data, only_1d_for_numpy=True), type=type)
File "pyarrow/array.pxi", line 305, in pyarrow.lib.array
File "pyarrow/array.pxi", line 39, in pyarrow.lib._sequence_to_array
File "pyarrow/error.pxi", line 122, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.0, 1.16.1
- Platform: macOS 1.15.7 or above
- Python version: 3.7.12 and 3.9
- PyArrow version: 3.0.0, 5.0.0, 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3345 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3345/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3345/comments | https://api.github.com/repos/huggingface/datasets/issues/3345/events | https://github.com/huggingface/datasets/issues/3345 | 1,067,622,951 | I_kwDODunzps4_oqIn | 3,345 | Failed to download species_800 from Google Drive zip file | {
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] | closed | false | null | [] | null | 3 | "2021-11-30T20:00:28Z" | "2021-12-01T17:53:15Z" | "2021-12-01T17:53:15Z" | CONTRIBUTOR | null | null | null | ## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
```
```python
>>> from datasets import load_dataset
>>> s800 = load_dataset("species_800")
```
## Expected results
species_800 downloaded.
## Actual results
```shell
Downloading: 5.68kB [00:00, 1.22MB/s]
Downloading: 2.70kB [00:00, 691kB/s]
Downloading and preparing dataset species800/species_800 (download: 17.36 MiB, generated: 3.53 MiB, post-processed: Unknown size, total: 20.89 MiB) to /Users/mike/.cache/huggingface/datasets/species800/species_800/1.0.0/532167f0bb8fbc0d77d6d03c4fd642c8c55527b9c5f2b1da77f3d00b0e559976...
0%| | 0/1 [00:00<?, ?it/s]Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/load.py", line 1632, in load_dataset
use_auth_token=use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 608, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/mike/.cache/huggingface/modules/datasets_modules/datasets/species_800/532167f0bb8fbc0d77d6d03c4fd642c8c55527b9c5f2b1da77f3d00b0e559976/species_800.py", line 104, in _split_generators
downloaded_files = dl_manager.download_and_extract(urls_to_download)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 197, in download
download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, disable_tqdm=False
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 209, in map_nested
for obj in utils.tqdm(iterable, disable=disable_tqdm)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 209, in <listcomp>
for obj in utils.tqdm(iterable, disable=disable_tqdm)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 143, in _single_map_nested
return function(data_struct)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 305, in cached_path
use_auth_token=download_config.use_auth_token,
File "/Users/mike/Library/Caches/pypoetry/virtualenvs/promptsource-hsdAcWsQ-py3.7/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.14,0 1.15.0, 1.16.1
- Platform: macOS Catalina 10.15.7
- Python version: 3.7.12
- PyArrow version: 6.0.1
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} | Documents support for dynamic first dimension in `ArrayXD` from #2891, and explain the `ArrayXD` feature in general.
Let me know if I'm missing anything @lhoestq :) | {
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https://api.github.com/repos/huggingface/datasets/issues/3343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3343/comments | https://api.github.com/repos/huggingface/datasets/issues/3343/events | https://github.com/huggingface/datasets/pull/3343 | 1,067,505,507 | PR_kwDODunzps4vM8yB | 3,343 | Better error message when download fails | {
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} | From our discussions in https://github.com/huggingface/datasets/issues/3269 and https://github.com/huggingface/datasets/issues/3282 it would be nice to have better messages if a download fails.
In particular the error now shows:
- the error from the HEAD request if there's one
- otherwise the response code of the HEAD request
I also added an error to tell users to pass `use_auth_token` when the Hugging Face Hub returns 401 (Unauthorized).
While paying around with this I also fixed a minor issue with the `force_download` parameter that was not always taken into account | {
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} | Change the branch name "master" to "main" in the data URLs, since facebookresearch has changed that. | {
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] | null | 2 | "2021-11-30T16:42:05Z" | "2022-01-26T14:47:37Z" | "2022-01-26T14:47:37Z" | CONTRIBUTOR | null | null | null | - [ ] create a repo on https://hf.co/datasets for every canonical dataset
- [ ] on every commit related to a dataset, update the hf.co repo
See https://github.com/huggingface/moon-landing/pull/1562
@SBrandeis: I let you edit this description if needed to precise the intent. | {
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https://api.github.com/repos/huggingface/datasets/issues/3340 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3340/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3340/comments | https://api.github.com/repos/huggingface/datasets/issues/3340/events | https://github.com/huggingface/datasets/pull/3340 | 1,067,292,636 | PR_kwDODunzps4vMP6Z | 3,340 | Fix JSON ClassLabel casting for integers | {
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} | [] | closed | false | null | [] | null | 0 | "2021-11-30T14:19:54Z" | "2021-12-01T11:27:30Z" | "2021-12-01T11:27:30Z" | MEMBER | null | 0 | {
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} | Loading a JSON dataset with ClassLabel feature types currently fails if the JSON data already has integers. Indeed currently it tries to convert the strings to integers without even checking if the data are not integers already.
For example this currently fails:
```python
from datasets import load_dataset, Features, ClassLabel
path = "data.json"
f = Features({"a": ClassLabel(names=["neg", "pos"])})
d = load_dataset("json", data_files=path, features=f)
```
data.json
```json
{"a": 0}
{"a": 1}
```
I fixed that by adding a line that checks the type of the JSON data before trying to convert them
cc @albertvillanova let me know if it sounds good to you | {
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https://api.github.com/repos/huggingface/datasets/issues/3339 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3339/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3339/comments | https://api.github.com/repos/huggingface/datasets/issues/3339/events | https://github.com/huggingface/datasets/issues/3339 | 1,066,662,477 | I_kwDODunzps4_k_pN | 3,339 | to_tf_dataset fails on TPU | {
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] | open | false | null | [] | null | 5 | "2021-11-30T00:50:52Z" | "2021-12-02T14:21:27Z" | null | NONE | null | null | null | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=sharing
## Expected results
dataset from `to_tf_dataset` works in `model.fit`
Right below the first error in the colab I use `tf.data.Dataset.from_tensor_slices` and `model.fit` works just fine. This is the desired outcome.
## Actual results
```
InternalError: 5 root error(s) found.
(0) INTERNAL: {{function_node __inference_train_function_30558}} failed to connect to all addresses
Additional GRPC error information from remote target /job:localhost/replica:0/task:0/device:CPU:0:
:{"created":"@1638231897.932218653","description":"Failed to pick subchannel","file":"third_party/grpc/src/core/ext/filters/client_channel/client_channel.cc","file_line":3151,"referenced_errors":[{"created":"@1638231897.932216754","description":"failed to connect to all addresses","file":"third_party/grpc/src/core/lib/transport/error_utils.cc","file_line":161,"grpc_status":14}]}
[[{{node StatefulPartitionedCall}}]]
[[MultiDeviceIteratorGetNextFromShard]]
Executing non-communication op <MultiDeviceIteratorGetNextFromShard> originally returned UnavailableError, and was replaced by InternalError to avoid invoking TF network error handling logic.
[[RemoteCall]]
[[IteratorGetNextAsOptional]]
[[tpu_compile_succeeded_assert/_14023832043698465348/_7/_439]]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 3.0.0
- Tensorflow 2.7.0
- `transformers` 4.12.5
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} | Opening a PR as discussed with @LysandreJik for some help with doctest issues. The goal is to add doctests for each of the tutorials in the documentation to make sure the code samples work as shown.
### Issues
A doctest has been added in the docstring of the `load_dataset_builder` function in `load.py` to handle variable outputs with the `ELLIPSIS` directive. When I run doctest on the `load_hub.rst` file, doctest should recognize the expected output from the docstring, and the corresponding code sample in `load_hub.rst` should pass. I am having the same issue with handling tracebacks in the `load_dataset` function.
From the docstring:
```
>>> dataset_builder.cache_dir #doctest: +ELLIPSIS
/Users/.../.cache/huggingface/datasets/imdb/plain_text/1.0.0/...
```
Test result:
```
Failed example:
dataset_builder.cache_dir
Expected:
/Users/.../.cache/huggingface/datasets/imdb/plain_text/1.0.0/...
Got:
/Users/steven/.cache/huggingface/datasets/imdb/plain_text/1.0.0/2fdd8b9bcadd6e7055e742a706876ba43f19faee861df134affd7a3f60fc38a1
```
I am able to get the doctest to pass by adding the doctest directives (`ELLIPSIS` and `NORMALIZE_WHITESPACE`) to the code samples in the `rst` file directly. But my understanding is that these directives should also work in the docstrings of the functions. I am running the test from the root of the directory:
```
python -m doctest -v docs/source/load_hub.rst
``` | {
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] | null | 2 | "2021-11-29T16:20:11Z" | "2021-12-14T10:28:54Z" | "2021-12-14T10:28:54Z" | CONTRIBUTOR | null | null | null | ## Describe the bug
The newly added typing for Dataset.__getitem__ is Union[Dict, List]. This makes tools like mypy a bit awkward to use as we need to check the type manually. We could use type overloading to make this easier. [Documentation](https://docs.python.org/3/library/typing.html#typing.overload)
## Steps to reproduce the bug
Let's have a file `test.py`
```python
from typing import List, Dict, Any
from datasets import Dataset
ds = Dataset.from_dict({
'a': [1,2,3],
'b': ["1", "2", "3"]
})
one_colum: List[str] = ds['a']
some_index: Dict[Any, Any] = ds[1]
```
## Expected results
Running `mypy test.py` should not give any error.
## Actual results
```
test.py:10: error: Incompatible types in assignment (expression has type "Union[Dict[Any, Any], List[Any]]", variable has type "List[str]")
test.py:11: error: Incompatible types in assignment (expression has type "Union[Dict[Any, Any], List[Any]]", variable has type "Dict[Any, Any]")
Found 2 errors in 1 file (checked 1 source file)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.13.3
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.8
- PyArrow version: 6.0.1
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} | [] | closed | false | null | [] | null | 0 | "2021-11-29T15:58:59Z" | "2023-09-24T09:53:52Z" | "2023-05-16T18:24:46Z" | CONTRIBUTOR | null | 1 | {
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} | Add support for multiple dynamic dimensions (e.g. `(None, None, 3)` for arbitrary sized images) and `to_pandas()` conversion for dynamic arrays.
TODOs:
* [ ] Cleaner code
* [ ] Formatting issues (if NumPy doesn't allow broadcasting even though dtype is np.object)
* [ ] Fix some issues with zero-dim tensors
* [ ] Tests
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] | open | false | null | [] | null | 4 | "2021-11-29T12:31:54Z" | "2023-09-12T14:53:27Z" | null | MEMBER | null | null | null | Check potential integration of the Polars library: https://github.com/pola-rs/polars
- Benchmark: https://h2oai.github.io/db-benchmark/
CC: @thomwolf @lewtun
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https://api.github.com/repos/huggingface/datasets/issues/3333 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3333/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3333/comments | https://api.github.com/repos/huggingface/datasets/issues/3333/events | https://github.com/huggingface/datasets/issues/3333 | 1,065,346,919 | I_kwDODunzps4_f-dn | 3,333 | load JSON files, get the errors | {
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} | [] | closed | false | null | [] | null | 12 | "2021-11-28T14:29:58Z" | "2021-12-01T09:34:31Z" | "2021-12-01T03:57:48Z" | NONE | null | null | null | Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs/datasets/loading.html
`dataset = datasets.load_dataset('json', data_files=args.dataset)`
Errors:
`Downloading and preparing dataset json/default (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/json/default-c1e124ad488911b8/0.0.0/45636811569ec4a6630521c18235dfbbab83b7ab572e3393c5ba68ccabe98264...
`
_Originally posted by @yanllearnn in https://github.com/huggingface/datasets/issues/730#issuecomment-981095050_ | {
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https://api.github.com/repos/huggingface/datasets/issues/3332 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3332/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3332/comments | https://api.github.com/repos/huggingface/datasets/issues/3332/events | https://github.com/huggingface/datasets/pull/3332 | 1,065,345,853 | PR_kwDODunzps4vGBig | 3,332 | Fix error message and add extension fallback | {
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} | Fix the error message raised if `infered_module_name` is `None` in `CommunityDatasetModuleFactoryWithoutScript.get_module` and make `infer_module_for_data_files` more robust.
In the linked issue, `infer_module_for_data_files` returns `None` because `json` is the second most common extension due to the suffix ordering. Now, we go from the most common to the least common extension and try to map it or return `None`.
Fix #3331 | {
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] | closed | false | null | [] | null | 1 | "2021-11-28T08:54:05Z" | "2021-11-29T13:49:44Z" | "2021-11-29T13:34:14Z" | NONE | null | null | null | ## Describe the bug
I add a new question answering dataset to huggingface datasets manually. Here is the link: [luozhouyang/question-answering-datasets](https://huggingface.co/datasets/luozhouyang/question-answering-datasets)
But when I load the dataset, an error raised:
```bash
AttributeError: 'CommunityDatasetModuleFactoryWithoutScript' object has no attribute 'path'
```
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("luozhouyang/question-answering-datasets", data_files=["dureader_robust.train.json"])
```
## Expected results
Load dataset successfully without any error.
## Actual results
```bash
Traceback (most recent call last):
File "/mnt/home/zhouyang.lzy/github/naivenlp/naivenlp/tests/question_answering_tests/dataset_test.py", line 89, in test_load_dataset_with_hf
data_files=["dureader_robust.train.json"],
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1616, in load_dataset
**config_kwargs,
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1443, in load_dataset_builder
path, revision=revision, download_config=download_config, download_mode=download_mode, data_files=data_files
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1157, in dataset_module_factory
raise e1 from None
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 1144, in dataset_module_factory
download_mode=download_mode,
File "/mnt/home/zhouyang.lzy/.conda/envs/naivenlp/lib/python3.6/site-packages/datasets/load.py", line 798, in get_module
raise FileNotFoundError(f"No data files or dataset script found in {self.path}")
AttributeError: 'CommunityDatasetModuleFactoryWithoutScript' object has no attribute 'path'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: linux
- Python version: 3.6.13
- PyArrow version: 6.0.1
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] | closed | false | null | [] | null | 4 | "2021-11-27T17:53:05Z" | "2021-11-29T20:40:15Z" | "2021-11-29T20:40:15Z" | NONE | null | null | null | ## Describe the bug
Using the map function, it throws a type error on iter #999
Here is the code I am calling:
```
dataset = datasets.load_dataset('squad')
dataset['validation'].map(text_numbers_to_int, input_columns=['context'], fn_kwargs={'column': 'context'})
```
text_numbers_to_int returns the input text with numbers replaced in the format {'context': text}
It happens at
`
File "C:\Users\lonek\anaconda3\envs\ai\Lib\site-packages\datasets\arrow_writer.py", line 289, in <listcomp>
[row[0][col] for row in self.current_examples], type=col_type, try_type=col_try_type, col=col
`
The issue is that the list comprehension expects self.current_examples to be type tuple(dict, str), but for some reason 26 out of 1000 of the sefl.current_examples are type tuple(str, str)
Here is an example of what self.current_examples should be
({'context': 'Super Bowl 50 was an...merals 50.'}, '')
Here is an example of what self.current_examples are when it throws the error:
('The Panthers used th... Marriott.', '')
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} | While working on a dataset, I got the error
```
TypeError: Provided `function` which is applied to all elements of table returns a `dict` of types {[type(x) for x in processed_inputs.values()]}. When using `batched=True`, make sure provided `function` returns a `dict` of types like `{allowed_batch_return_types}`.
```
This PR should fix the formatting of this error | {
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] | closed | false | null | [] | null | 1 | "2021-11-26T16:26:36Z" | "2021-11-26T16:44:11Z" | "2021-11-26T16:44:11Z" | CONTRIBUTOR | null | null | null | ## Describe the bug
Passing a correctly shaped Numpy-Array to get_nearest_examples leads to the Exception
"Shape of query is incorrect, it has to be either a 1D array or 2D (1, N)"
Probably the reason for this is a wrongly converted assertion.
1.15.1:
`assert len(query.shape) == 1 or (len(query.shape) == 2 and query.shape[0] == 1)`
1.16.1:
```
if len(query.shape) != 1 or (len(query.shape) == 2 and query.shape[0] != 1):
raise ValueError("Shape of query is incorrect, it has to be either a 1D array or 2D (1, N)")
```
## Steps to reproduce the bug
follow the steps described here: https://huggingface.co/course/chapter5/6?fw=tf
```python
question_embedding.shape # (1, 768)
scores, samples = embeddings_dataset.get_nearest_examples(
"embeddings", question_embedding, k=5 # Error
)
# "Shape of query is incorrect, it has to be either a 1D array or 2D (1, N)"
```
## Expected results
Should work without exception
## Actual results
Throws exception
## Environment info
- `datasets` version: 1.15.1
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.12
- PyArrow version: 6.0.
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} | In python 3.10 it's no longer possible to use `functools.wraps` on a method decorated with `classmethod`.
To fix this I inverted the order of the `inject_arrow_table_documentation` and `classmethod` decorators
Fix #3324 | {
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] | null | 0 | "2021-11-26T16:06:14Z" | "2021-11-26T16:31:23Z" | "2021-11-26T16:31:23Z" | MEMBER | null | null | null | When importing `datasets` I'm getting this error in python 3.10:
```python
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/__init__.py", line 34, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_dataset.py", line 47, in <module>
from .arrow_reader import ArrowReader
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_reader.py", line 33, in <module>
from .table import InMemoryTable, MemoryMappedTable, Table, concat_tables
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 334, in <module>
class InMemoryTable(TableBlock):
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 361, in InMemoryTable
def from_pandas(cls, *args, **kwargs):
File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 24, in wrapper
out = wraps(arrow_table_method)(method)
File "/Users/quentinlhoest/.pyenv/versions/3.10.0/lib/python3.10/functools.py", line 61, in update_wrapper
wrapper.__wrapped__ = wrapped
AttributeError: readonly attribute
```
This makes the conda build fail.
I'm opening a PR to fix this and do a patch release 1.16.1 | {
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} | Updates the URL of the tatoeba subset of xtreme. Additionally, replaces `os.path.join` with `xjoin` to correctly join the URL segments on Windows.
Fix #3320 | {
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] | closed | false | null | [] | null | 0 | "2021-11-25T12:31:11Z" | "2021-11-26T10:30:29Z" | "2021-11-26T10:30:29Z" | NONE | null | null | null | ## Describe the bug
It gives an error.
> FileNotFoundError: Couldn't find file at https://github.com/facebookresearch/LASER/raw/master/data/tatoeba/v1/tatoeba.rus-eng.rus
## Steps to reproduce the bug
```python
data=load_dataset("xtreme","tatoeba.rus", split="validation")
```
## Solution
The library tries to access the **master** branch. In the github repo of facebookresearch, it is in the **main** branch. | {
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} | Since #3098 it's now possible to upload a dataset on the Hub directly from python using the `push_to_hub` method.
I just added a section in the "Upload a dataset to the Hub" tutorial.
I kept the section quite simple but let me know if it sounds good to you @LysandreJik @stevhliu :) | {
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] | closed | false | null | [] | null | 4 | "2021-11-24T11:01:36Z" | "2022-01-05T18:31:24Z" | "2022-01-05T18:31:24Z" | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
As I was filtering very large datasets I noticed the filter method doesn't have the desc parameter which is available in the map method. Why don't we add a desc parameter to the filter method both for consistency and it's nice to give some feedback to users during long operations on Datasets?
**Describe the solution you'd like**
Add desc parameter to Dataset filter method
**Describe alternatives you've considered**
N/A
**Additional context**
N/A
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] | null | 0 | "2021-11-24T09:23:02Z" | "2022-01-12T14:13:15Z" | "2022-01-12T14:13:15Z" | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** RedCaps
- **Description:** Web-curated image-text data created by the people, for the people
- **Paper:** https://arxiv.org/abs/2111.11431
- **Data:** https://redcaps.xyz/
- **Motivation:** Multimodal image-text dataset: 12M+ Image-text pairs
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Proposed by @patil-suraj | {
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https://api.github.com/repos/huggingface/datasets/issues/3315 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3315/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3315/comments | https://api.github.com/repos/huggingface/datasets/issues/3315/events | https://github.com/huggingface/datasets/pull/3315 | 1,061,678,452 | PR_kwDODunzps4u7WpU | 3,315 | Removing query params for dynamic URL caching | {
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} | The main use case for this is to make dynamically generated private URLs (like the ones returned by CommonVoice API) compatible with the datasets' caching logic.
Usage example:
```python
import datasets
class CommonVoice(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo()
def _split_generators(self, dl_manager):
dl_manager.download_config.ignore_url_params = True
HUGE_URL = "https://mozilla-common-voice-datasets.s3.dualstack.us-west-2.amazonaws.com/cv-corpus-7.0-2021-07-21/cv-corpus-7.0-2021-07-21-ab.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQ3GQRTO3IU5JYB5K%2F20211125%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20211125T131423Z&X-Amz-Expires=43200&X-Amz-Security-Token=FwoGZXIvYXdzEL7%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaDLsZw7Nj0d9h4rgheyKSBJJ6bxo1JdWLXAUhLMrUB8AXfhP8Ge4F8dtjwXmvGJgkIvdMT7P4YOEE1pS3mW8AyKsz7Z7IRVCIGQrOH1AbxGVVcDoCMMswXEOqL3nJFihKLf99%2F6l8iJVZdzftRUNgMhX5Hz0xSIL%2BzRDpH5nYa7C6YpEdOdW81CFVXybx7WUrX13wc8X4ZlUj7zrWcWf5p2VEIU5Utb7YHVi0Y5TQQiZSDoedQl0j4VmMuFkDzoobIO%2BvilgGeE2kIX0E62X423mEGNu4uQV5JsOuLAtv3GVlemsqEH3ZYrXDuxLmnvGj5HfMtySwI4vKv%2BlnnirD29o7hxvtidXiA8JMWhp93aP%2Fw7sod%2BPPbb5EqP%2B4Qb2GJ1myClOKcLEY0cqoy7XWm8NeVljLJojnFJVS5mNFBAzCCTJ%2FidxNsj8fflzkRoAzYaaPBuOTL1dgtZCdslK3FAuEvw0cik7P9A7IYiULV33otSHKMPcVfNHFsWQljs03gDztsIUWxaXvu6ck5vCcGULsHbfe6xoMPm2bR9jtKLONsslPcnzWIf7%2Fch2w%2F%2BjtTCd9IxaH4kytyJ6mIjpV%2FA%2F2h9qeDnDFsCphnMjAzPQn6tqCgTtPcyJ2b8c94ncgUnE4mepx%2FDa%2FanAEsrg9RPdmbdoPswzHn1IClh91IfSN74u95DZUxlPeZrHG5HxVCN3dKO6j%2Ft1xd20L0hEtazDdKOr8%2FYwGMirp8rp%2BII0pYOwQOrYHqH%2FREX2dRJctJtwE86Qj1eU8BAdXuFIkLC4NWXw%3D&X-Amz-Signature=1b8108d29b0e9c2bf6c7246e58ca8d5749a83de0704757ad8e8a44d78194691f&X-Amz-SignedHeaders=host"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
HUGE_URL += "&some_new_or_changed_param=12345"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
dl_manager = datasets.DownloadManager(dataset_name="common_voice")
CommonVoice()._split_generators(dl_manager)
```
Output:
```
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3314 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3314/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3314/comments | https://api.github.com/repos/huggingface/datasets/issues/3314/events | https://github.com/huggingface/datasets/pull/3314 | 1,061,448,227 | PR_kwDODunzps4u6mdX | 3,314 | Adding arg to pass process rank to `map` | {
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} | This PR adds a `with_rank` argument to `map` that gives the user the possibility to pass the rank of each process to their function. This is mostly designed for multi-GPU map (each process can be sent to a different device thanks to the rank). I've also added tests. I'm putting the PR up so you can check the code, I'll add a multi-GPU example to the doc (+ write a bit in the doc for the new arg) | {
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https://api.github.com/repos/huggingface/datasets/issues/3313 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3313/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3313/comments | https://api.github.com/repos/huggingface/datasets/issues/3313/events | https://github.com/huggingface/datasets/issues/3313 | 1,060,933,392 | I_kwDODunzps4_PI8Q | 3,313 | TriviaQA License Mismatch | {
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] | closed | false | null | [] | null | 1 | "2021-11-23T08:00:15Z" | "2021-11-29T11:24:21Z" | "2021-11-29T11:24:21Z" | NONE | null | null | null | ## Describe the bug
TriviaQA Webpage at http://nlp.cs.washington.edu/triviaqa/ says they do not own the copyright to the data. However, Huggingface datasets at https://huggingface.co/datasets/trivia_qa mentions that the dataset is released under Apache License
Is the License Information on HuggingFace correct? | {
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https://api.github.com/repos/huggingface/datasets/issues/3312 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3312/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3312/comments | https://api.github.com/repos/huggingface/datasets/issues/3312/events | https://github.com/huggingface/datasets/pull/3312 | 1,060,440,346 | PR_kwDODunzps4u3duV | 3,312 | add bl books genre dataset | {
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} | First of all thanks for the fantastic library/collection of datasets 🤗
This pull request adds a dataset of metadata from digitised (mostly 19th Century) books from the British Library The [data](https://bl.iro.bl.uk/concern/datasets/1e1ccb46-65b4-4481-b6f8-b8129d5da053) contains various metadata about the books. In addition, a subset of the data includes 'genre' information which can be used for supervised text classification tasks. I hope that this offers easier access to a dataset for doing text classification on GLAM (galleries, libraries, archives and museums) data.
I have tried to create three configurations that provide both an 'easy' version of the dataset if you want to use it for training a genre classification model and a more 'raw' version of the data for other potential use cases for the data. I am open to suggestions if this doesn't make sense.
Similarly, for some of the arrow datatypes, I have had to fall back to strings since there are missing values for some fields/rows but I may have missed a more elegant way of dealing with it. | {
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] | open | false | null | [] | null | 0 | "2021-11-22T16:58:33Z" | "2021-11-22T16:58:33Z" | null | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** WebSRC
- **Description:** WebSRC is a novel Web-based Structural Reading Comprehension dataset. It consists of 0.44M question-answer pairs, which are collected from 6.5K web pages with corresponding HTML source code, screenshots and metadata.
- **Paper:** https://arxiv.org/abs/2101.09465
- **Data:** https://x-lance.github.io/WebSRC/dashboard.html#
- **Motivation:** Currently adding MarkupLM to HuggingFace Transformers, which achieves SOTA on 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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Fatal error when using the library
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('wikiann', 'en')
```
## Expected results
No fatal errors
## Actual results
```
Fatal error condition occurred in D:\bld\aws-c-io_1633633258269\work\source\event_loop.c:74: aws_thread_launch(&cleanup_thread, s_event_loop_destroy_async_thread_fn, el_group, &thread_options) == AWS_OP_SUCCESS
Exiting Application
```
## Environment info
- `datasets` version: 1.15.2.dev0
- Platform: Windows-10-10.0.22504-SP0
- Python version: 3.8.12
- PyArrow version: 6.0.0
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```
my_dataset_local_path/
├── README.md
└── data/
├── train/
│ ├── shard_0.csv
│ ├── shard_1.csv
│ ├── shard_2.csv
│ └── shard_3.csv
└── valid/
├── shard_0.csv
└── shard_1.csv
```
The reason is that they were matching both `*train*/*` and `*train*/**/*`.
This PR fixes it. @lhoestq | {
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] | open | false | null | [] | null | 3 | "2021-11-21T00:07:22Z" | "2022-01-19T13:55:32Z" | null | NONE | null | null | null | ## Describe the bug
In the repository, every dataset has its metadata in a file called`dataset_infos.json`. But, this file is missing for two datasets: `chr_en` and `mc4`.
## Steps to reproduce the bug
Check [chr_en](https://github.com/huggingface/datasets/tree/master/datasets/chr_en) and [mc4](https://github.com/huggingface/datasets/tree/master/datasets/mc4) | {
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https://api.github.com/repos/huggingface/datasets/issues/3307 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3307/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3307/comments | https://api.github.com/repos/huggingface/datasets/issues/3307/events | https://github.com/huggingface/datasets/pull/3307 | 1,059,226,297 | PR_kwDODunzps4uzlWa | 3,307 | Add IndoNLI dataset | {
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As the title, nested sequence feature won't encode example if the first item of the outside sequence is an empty list.
## Steps to reproduce the bug
```python
from datasets import Features, Sequence, ClassLabel
features = Features({
'x': Sequence(Sequence(ClassLabel(names=['a', 'b']))),
})
print(features.encode_batch({
'x': [
[['a'], ['b']],
[[], ['b']],
]
}))
```
## Expected results
print `{'x': [[[0], [1]], [[], ['1']]]}`
## Actual results
print `{'x': [[[0], [1]], [[], ['b']]]}`
## Environment info
- `datasets` version: 1.15.1
- Platform: Linux-5.13.0-21-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.0
## Additional information
I think the issue stems from [here](https://github.com/huggingface/datasets/blob/8555197a3fe826e98bd0206c2d031c4488c53c5c/src/datasets/features/features.py#L847-L848).
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Fixes exception for ``fingerprint.py``, ``search.py``, ``arrow_writer.py`` and ``metric.py`` and modified tests | {
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] | closed | false | null | [] | null | 1 | "2021-11-20T12:03:59Z" | "2021-11-21T07:07:25Z" | "2021-11-21T07:07:25Z" | NONE | null | null | null | I am following HuggingFace Course. I am at Fine-tuning a model.
Link: https://huggingface.co/course/chapter3/2?fw=tf
I use tokenize_function and `map` as mentioned in the course to process data.
`# define a tokenize function`
`def Tokenize_function(example):`
` return tokenizer(example['sentence'], truncation=True)`
`# tokenize entire data`
`tokenized_data = raw_data.map(Tokenize_function, batched=True)`
I get Dataset object at this point. When I try converting this to a TF dataset object as mentioned in the course, it throws the following error.
`# convert to TF dataset`
`train_data = tokenized_data["train"].to_tf_dataset( `
` columns = ['attention_mask', 'input_ids', 'token_type_ids'], `
` label_cols = ['label'], `
` shuffle = True, `
` collate_fn = data_collator, `
` batch_size = 8 `
`)`
Output:
`---------------------------------------------------------------------------`
`AttributeError Traceback (most recent call last)`
`/tmp/ipykernel_42/103099799.py in <module>`
` 1 # convert to TF dataset`
`----> 2 train_data = tokenized_data["train"].to_tf_dataset( \`
` 3 columns = ['attention_mask', 'input_ids', 'token_type_ids'], \`
` 4 label_cols = ['label'], \`
` 5 shuffle = True, \`
`AttributeError: 'Dataset' object has no attribute 'to_tf_dataset'`
When I look for `dir(tokenized_data["train"])`, there is no method or attribute in the name of `to_tf_dataset`.
Why do I get this error? And how to clear this?
Please help me. | {
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https://api.github.com/repos/huggingface/datasets/issues/3303 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3303/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3303/comments | https://api.github.com/repos/huggingface/datasets/issues/3303/events | https://github.com/huggingface/datasets/issues/3303 | 1,059,129,732 | I_kwDODunzps4_IQmE | 3,303 | DataCollatorWithPadding: TypeError | {
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I am following the HuggingFace course. I am now at Fine-tuning [https://huggingface.co/course/chapter3/3?fw=tf](https://huggingface.co/course/chapter3/3?fw=tf). When I set up `DataCollatorWithPadding` as following I got an error while trying to reproduce the course code in Kaggle. This error occurs with either a CPU-only-device or a GPU-device.
Input:
```checkpoint = 'bert-base-uncased'
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="tf")
```
Output:
```---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_42/1563280798.py in <module>
1 checkpoint = 'bert-base-uncased'
2 tokenizer = AutoTokenizer.from_pretrained(checkpoint)
----> 3 data_collator = DataCollatorWithPadding(tokenizer=tokenizer, return_tensors="pt")
TypeError: __init__() got an unexpected keyword argument 'return_tensors'
```
When I call `help` method, it too confirms that there is no argument `return_tensors`.
Input:
```
help(DataCollatorWithPadding.__init__)
```
Output:
```
Help on function __init__ in module transformers.data.data_collator:
__init__(self, tokenizer: transformers.tokenization_utils_base.PreTrainedTokenizerBase, padding: Union[bool, str, transformers.file_utils.PaddingStrategy] = True, max_length: Union[int, NoneType] = None, pad_to_multiple_of: Union[int, NoneType] = None) -> None
```
But, the source file *[Data Collator - docs](https://huggingface.co/transformers/main_classes/data_collator.html#datacollatorwithpadding)* says that there is such an argument. By default, it returns Pytorch tensors while I need TF tensors.
Where do I miss?
Please help me. | {
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https://api.github.com/repos/huggingface/datasets/issues/3302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3302/comments | https://api.github.com/repos/huggingface/datasets/issues/3302/events | https://github.com/huggingface/datasets/pull/3302 | 1,058,907,168 | PR_kwDODunzps4uynjc | 3,302 | fix old_val typo in f-string | {
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This PR is to correct a typo in #3277 that @Carlosbogo revieled in a comment.
Related closed issue : #3257
Sorry about that 😅. | {
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https://api.github.com/repos/huggingface/datasets/issues/3301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3301/comments | https://api.github.com/repos/huggingface/datasets/issues/3301/events | https://github.com/huggingface/datasets/pull/3301 | 1,058,718,957 | PR_kwDODunzps4uyA9o | 3,301 | Add wikipedia tags | {
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} | [] | closed | false | null | [] | null | 0 | "2021-11-19T16:39:25Z" | "2021-11-19T16:49:30Z" | "2021-11-19T16:49:29Z" | MEMBER | null | 0 | {
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} | Add the missing tags to the wikipedia dataset card.
I also added the missing languages code in our language codes list.
This should also fix the code snippet that is presented on the Hub to load the dataset: fix https://github.com/huggingface/datasets/issues/3292 | {
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https://api.github.com/repos/huggingface/datasets/issues/3300 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3300/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3300/comments | https://api.github.com/repos/huggingface/datasets/issues/3300/events | https://github.com/huggingface/datasets/issues/3300 | 1,058,644,459 | I_kwDODunzps4_GaHr | 3,300 | ❓ Dataset loading script from Hugging Face Hub | {
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] | null | 8 | "2021-11-19T15:20:52Z" | "2021-12-22T10:57:56Z" | "2021-12-22T10:57:56Z" | NONE | null | null | null | Hi there,
I am trying to add my custom `ag_news` with its own loading script on the Hugging Face datasets hub. In particular, I would like to test the addition of a second configuration to the existing `ag_news` dataset. Once it works in my hub, I plan to make a PR to the original dataset. However, in trying to do so I have encountered certain problems as detailed below.
Issues I have encountered:
- Without a loading script, the train and test files are loaded together into a unique `dataset.Dataset` -> so I wrote a loading script. Also, I need a loading script otherwise I cannot specify multiple configurations
- Once my loading script is working locally, I do not manage to make it work on the hub. In particular, I would like to be able to load the dataset like this
```python
load_dataset("pietrolesci/ag_news", name="my_configuration")
```
Apparently, the `load_dataset` is able to pick up the loading script from the hub and run it. However, it errors because it is unable to find the files. The structure of my hub repo is the following
```
ag_news.py
train.csv
test.csv
```
and the loading script I specify `data_dir=Path(__file__).parent` and `data_files=DataFilesDict({"train": "train.csv", "test": "test.csv"})`. In the documentation I could not find info regarding loading a dataset from the hub using a loading script present on the hub.
Any suggestion is very much appreciated.
Best,
Pietro
Link to the hub repo: https://huggingface.co/datasets/pietrolesci/ag_news
BONUS: how can I make the data viewer work in this specific case? :) | {
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https://api.github.com/repos/huggingface/datasets/issues/3299 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3299/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3299/comments | https://api.github.com/repos/huggingface/datasets/issues/3299/events | https://github.com/huggingface/datasets/issues/3299 | 1,058,518,213 | I_kwDODunzps4_F7TF | 3,299 | Add option to find unique elements in nested sequences when calling `Dataset.unique` | {
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] | closed | false | null | [] | null | 3 | "2021-11-19T11:18:59Z" | "2021-12-21T16:24:05Z" | "2021-12-21T16:24:05Z" | NONE | null | null | null | ## Dataset viewer issue for '*name of the dataset*'
**Link:** https://huggingface.co/datasets/ag_news
Hi there, the `ag_news` dataset viewer is not working.
Am I the one who added this dataset? No
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https://api.github.com/repos/huggingface/datasets/issues/3297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3297/comments | https://api.github.com/repos/huggingface/datasets/issues/3297/events | https://github.com/huggingface/datasets/issues/3297 | 1,058,263,859 | I_kwDODunzps4_E9Mz | 3,297 | .map() cache is wrongfully reused - only happens when the mapping function is imported | {
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] | open | false | null | [] | null | 3 | "2021-11-19T08:18:36Z" | "2023-01-30T12:40:17Z" | null | CONTRIBUTOR | null | null | null | ## Describe the bug
When `.map` is used with a mapping function that is imported, the cache is reused even if the mapping function has been modified.
The reason for this is that `dill` that is used for creating the fingerprint [pickles imported functions by reference](https://stackoverflow.com/a/67851411).
I guess it is not a widespread case, but it can still lead to unwanted results unnoticeably.
## Steps to reproduce the bug
Create files `a.py` and `b.py`:
```python
# a.py
from datasets import load_dataset
def main():
squad = load_dataset("squad")
squad.map(mapping_func, batched=True)
def mapping_func(examples):
ID_LENGTH = 4
examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
return examples
if __name__ == "__main__":
main()
```
```python
# b.py
from datasets import load_dataset
from a import mapping_func
def main():
squad = load_dataset("squad")
squad.map(mapping_func, batched=True)
if __name__ == "__main__":
main()
```
Run `python b.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python b.py` again. You'll see that `.map` loads from the cache the result of the previous mapping function.
## Expected results
Run `python a.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python a.py` again. You'll see that the dataset is being processed and that there's no reuse of the previous mapping function result.
## Workaround
Put the mapping function inside a dummy class as a static method:
```python
# a.py
class MappingFuncClass:
@staticmethod
def mapping_func(examples):
ID_LENGTH = 4
examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
return examples
```
```python
# b.py
from datasets import load_dataset
from a import MappingFuncClass
def main():
squad = load_dataset("squad")
squad.map(MappingFuncClass.mapping_func, batched=True)
if __name__ == "__main__":
main()
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.4.0-19041-Microsoft-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 4.0.1
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} | [] | closed | false | null | [] | null | 2 | "2021-11-18T23:32:45Z" | "2021-12-06T10:45:04Z" | "2021-12-06T10:45:04Z" | CONTRIBUTOR | null | 0 | {
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} | This aims to close #3295 | {
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] | closed | false | null | [] | null | 1 | "2021-11-18T23:24:02Z" | "2021-12-06T10:45:04Z" | "2021-12-06T10:45:04Z" | CONTRIBUTOR | null | null | null | ## Describe the bug
When trying to build a temporary dataset path from a remote URI in this block of code:
https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1038-L1042
the result is not the expected when passing an absolute path in an URI like `hdfs:///absolute/path`.
## Steps to reproduce the bug
```python
dataset_path = "hdfs:///absolute/path"
src_dataset_path = extract_path_from_uri(dataset_path)
tmp_dir = get_temporary_cache_files_directory()
dataset_path = Path(tmp_dir, src_dataset_path)
print(dataset_path)
```
## Expected results
With the code above, we would expect a value in `dataset_path` similar to:
`/tmp/tmpnwxyvao5/absolute/path`
## Actual results
However, we get a `dataset_path` value like:
`/absolute/path`
This is because this line here: https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1041
returns the last absolute path when two absolute paths (the one in `tmp_dir` and the one extracted from the URI in `src_dataset_path`) are passed as arguments.
## Environment info
- `datasets` version: 1.13.3
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.33
- Python version: 3.9.7
- PyArrow version: 5.0.0
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] | open | false | null | [] | null | 0 | "2021-11-18T15:34:44Z" | "2021-12-08T12:00:02Z" | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** Natural Adversarial Objects (NAO)
- **Description:** Natural Adversarial Objects (NAO) is a new dataset to evaluate the robustness of object detection models. NAO contains 7,934 images and 9,943 objects that are unmodified and representative of real-world scenarios, but cause state-of-the-art detection models to misclassify with high confidence.
- **Paper:** https://arxiv.org/abs/2111.04204v1
- **Data:** https://drive.google.com/drive/folders/15P8sOWoJku6SSEiHLEts86ORfytGezi8
- **Motivation:** interesting object detection dataset useful for miscclassifications
cc @NielsRogge
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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Related to #3289, #3286. | {
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] | null | 1 | "2021-11-18T05:41:18Z" | "2021-11-19T16:49:29Z" | "2021-11-19T16:49:29Z" | NONE | null | null | null | ## Describe the bug
I am following the instruction for loading the wikipedia dataset using datasets. However getting the below error.
## Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset("wikipedia")
```
## Expected results
A clear and concise description of the expected results.
## Actual results
~/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/datasets/builder.py in _create_builder_config(self, name, custom_features, **config_kwargs)
339 "Config name is missing."
340 "\nPlease pick one among the available configs: %s" % list(self.builder_configs.keys())
--> 341 + "\nExample of usage:\n\t`{}`".format(example_of_usage)
342 )
343 builder_config = self.BUILDER_CONFIGS[0]
ValueError: Config name is missing.
Please pick one among the available configs: ['20200501.aa', '20200501.ab', '20200501.ace', '20200501.ady', '20200501.af', '20200501.ak', '20200501.als', '20200501.am', '20200501.an', '20200501.ang', '20200501.ar', '20200501.arc', '20200501.arz', '20200501.as', '20200501.ast', '20200501.atj', '20200501.av', '20200501.ay', '20200501.az', '20200501.azb', '20200501.ba', '20200501.bar', '20200501.bat-smg', '20200501.bcl', '20200501.be', '20200501.be-x-old', '20200501.bg', '20200501.bh', '20200501.bi', '20200501.bjn', '20200501.bm', '20200501.bn', '20200501.bo', '20200501.bpy', '20200501.br', '20200501.bs', '20200501.bug', '20200501.bxr', '20200501.ca', '20200501.cbk-zam', '20200501.cdo', '20200501.ce', '20200501.ceb', '20200501.ch', '20200501.cho', '20200501.chr', '20200501.chy', '20200501.ckb', '20200501.co', '20200501.cr', '20200501.crh', '20200501.cs', '20200501.csb', '20200501.cu', '20200501.cv', '20200501.cy', '20200501.da', '20200501.de', '20200501.din', '20200501.diq', '20200501.dsb', '20200501.dty', '20200501.dv', '20200501.dz', '20200501.ee', '20200501.el', '20200501.eml', '20200501.en', '20200501.eo', '20200501.es', '20200501.et', '20200501.eu', '20200501.ext', '20200501.fa', '20200501.ff', '20200501.fi', '20200501.fiu-vro', '20200501.fj', '20200501.fo', '20200501.fr', '20200501.frp', '20200501.frr', '20200501.fur', '20200501.fy', '20200501.ga', '20200501.gag', '20200501.gan', '20200501.gd', '20200501.gl', '20200501.glk', '20200501.gn', '20200501.gom', '20200501.gor', '20200501.got', '20200501.gu', '20200501.gv', '20200501.ha', '20200501.hak', '20200501.haw', '20200501.he', '20200501.hi', '20200501.hif', '20200501.ho', '20200501.hr', '20200501.hsb', '20200501.ht', '20200501.hu', '20200501.hy', '20200501.ia', '20200501.id', '20200501.ie', '20200501.ig', '20200501.ii', '20200501.ik', '20200501.ilo', '20200501.inh', '20200501.io', '20200501.is', '20200501.it', '20200501.iu', '20200501.ja', '20200501.jam', '20200501.jbo', '20200501.jv', '20200501.ka', '20200501.kaa', '20200501.kab', '20200501.kbd', '20200501.kbp', '20200501.kg', '20200501.ki', '20200501.kj', '20200501.kk', '20200501.kl', '20200501.km', '20200501.kn', '20200501.ko', '20200501.koi', '20200501.krc', '20200501.ks', '20200501.ksh', '20200501.ku', '20200501.kv', '20200501.kw', '20200501.ky', '20200501.la', '20200501.lad', '20200501.lb', '20200501.lbe', '20200501.lez', '20200501.lfn', '20200501.lg', '20200501.li', '20200501.lij', '20200501.lmo', '20200501.ln', '20200501.lo', '20200501.lrc', '20200501.lt', '20200501.ltg', '20200501.lv', '20200501.mai', '20200501.map-bms', '20200501.mdf', '20200501.mg', '20200501.mh', '20200501.mhr', '20200501.mi', '20200501.min', '20200501.mk', '20200501.ml', '20200501.mn', '20200501.mr', '20200501.mrj', '20200501.ms', '20200501.mt', '20200501.mus', '20200501.mwl', '20200501.my', '20200501.myv', '20200501.mzn', '20200501.na', '20200501.nah', '20200501.nap', '20200501.nds', '20200501.nds-nl', '20200501.ne', '20200501.new', '20200501.ng', '20200501.nl', '20200501.nn', '20200501.no', '20200501.nov', '20200501.nrm', '20200501.nso', '20200501.nv', '20200501.ny', '20200501.oc', '20200501.olo', '20200501.om', '20200501.or', '20200501.os', '20200501.pa', '20200501.pag', '20200501.pam', '20200501.pap', '20200501.pcd', '20200501.pdc', '20200501.pfl', '20200501.pi', '20200501.pih', '20200501.pl', '20200501.pms', '20200501.pnb', '20200501.pnt', '20200501.ps', '20200501.pt', '20200501.qu', '20200501.rm', '20200501.rmy', '20200501.rn', '20200501.ro', '20200501.roa-rup', '20200501.roa-tara', '20200501.ru', '20200501.rue', '20200501.rw', '20200501.sa', '20200501.sah', '20200501.sat', '20200501.sc', '20200501.scn', '20200501.sco', '20200501.sd', '20200501.se', '20200501.sg', '20200501.sh', '20200501.si', '20200501.simple', '20200501.sk', '20200501.sl', '20200501.sm', '20200501.sn', '20200501.so', '20200501.sq', '20200501.sr', '20200501.srn', '20200501.ss', '20200501.st', '20200501.stq', '20200501.su', '20200501.sv', '20200501.sw', '20200501.szl', '20200501.ta', '20200501.tcy', '20200501.te', '20200501.tet', '20200501.tg', '20200501.th', '20200501.ti', '20200501.tk', '20200501.tl', '20200501.tn', '20200501.to', '20200501.tpi', '20200501.tr', '20200501.ts', '20200501.tt', '20200501.tum', '20200501.tw', '20200501.ty', '20200501.tyv', '20200501.udm', '20200501.ug', '20200501.uk', '20200501.ur', '20200501.uz', '20200501.ve', '20200501.vec', '20200501.vep', '20200501.vi', '20200501.vls', '20200501.vo', '20200501.wa', '20200501.war', '20200501.wo', '20200501.wuu', '20200501.xal', '20200501.xh', '20200501.xmf', '20200501.yi', '20200501.yo', '20200501.za', '20200501.zea', '20200501.zh', '20200501.zh-classical', '20200501.zh-min-nan', '20200501.zh-yue', '20200501.zu']
Example of usage:
`load_dataset('wikipedia', '20200501.aa')`
I think the other parameter is missing in the load_dataset function that is not shown in the instruction. | {
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} | <s>Needs https://github.com/huggingface/datasets/pull/3129 to be merged first</s>
Make those audio datasets streamable:
- [x] common_voice
- [x] openslr
- [x] vivos
- [x] librispeech_asr <s>(still has some issues to read FLAC)</s> *actually it's ok*
- [ ] <s>multilingual_librispeech (yet to be converted)</S> *TODO in a separate PR* | {
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} | Calls `flatten_indices` on the datasets with indices table in `concatenate_datasets` to fix issues when concatenating along `axis=1`.
cc @lhoestq: I decided to flatten all the datasets instead of flattening all the datasets except the largest one in the end. The latter approach fails on the following example:
```python
a = Dataset.from_dict({"a": [10, 20, 30, 40]})
b = Dataset.from_dict({"b": [10, 20, 30, 40, 50, 60]}) # largest dataset
a = a.select([1, 2, 3])
b = b.select([1, 2, 3])
concatenate_datasets([a, b], axis=1) # fails at line concat_tables(...) because the real length of b's data is 6 and a's length is 3 after flattening (was 4 before flattening)
```
Also, it requires additional re-ordering of indices to prepare them for working with the indices table of the largest dataset. IMO not worth when we save only one `flatten_indices` call. (feel free to check the code of that approach at https://github.com/huggingface/datasets/commit/6acd10481c70950dcfdbfd2bab0bf0c74ad80bcb if you are interested)
Fixes #3273
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} | Add:
- The complete final version of The Pile dataset: "all" config
- PubMed Central subset of The Pile: "pubmed_central" config
Close #1675, close bigscience-workshop/data_tooling#74.
CC: @StellaAthena, @lewtun | {
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- **Name:** IEMOCAP
- **Description:** acted, multimodal and multispeaker database
- **Paper:** https://sail.usc.edu/iemocap/Busso_2008_iemocap.pdf
- **Data:** https://sail.usc.edu/iemocap/index.html
- **Motivation:** Useful multimodal dataset
cc @anton-l
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:** VoxLingua107
- **Description:** VoxLingua107 is a speech dataset for training spoken language identification models. The dataset consists of short speech segments automatically extracted from YouTube videos and labeled according the language of the video title and description, with some post-processing steps to filter out false positives.
- **Paper:** https://arxiv.org/abs/2011.12998
- **Data:** http://bark.phon.ioc.ee/voxlingua107/
- **Motivation:** Nice audio classification dataset
cc @anton-l
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:** Speech commands
- **Description:** A Dataset for Limited-Vocabulary Speech Recognition
- **Paper:** https://arxiv.org/abs/1804.03209
- **Data:** https://www.tensorflow.org/datasets/catalog/speech_commands, Available:
http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz
- **Motivation:** Nice dataset for audio classification training
cc @anton-l
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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**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/oscar-corpus/OSCAR-2109)*
*The dataset library cannot download any language from the oscar-corpus/OSCAR-2109 dataset. By entering the URL in your browser I can access the file.*
```
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/resolve/main/OSCAR-2109.py
```
Am I the one who added this dataset ? No
Using the older version of [OSCAR](https://huggingface.co/datasets/oscar) I don't have any issues downloading languages with the dataset library. | {
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} | It's currently quite confusing to understand the manual data download instruction of Covost and not very user-friendly.
Currenty the user has to:
1. Go on Common Voice website
2. Find the correct dataset which is **not** mentioned in the error message
3. Download it
4. Untar it
5. Create a language id folder (why? this folder does not exist in the `.tar` downloaded file)
6. pass the folder containing the created language id folder
This PR improves this to:
1. Go on Common Voice website
2. Find the correct dataset which **is** mentioned in the error message
3. Download it
4. Untar it
5. pass the untared folder
**Note**: This PR is not at all time-critical | {
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} | Each document is a full book, so the default arrow writer batch size of 10,000 is too big, and it can fill up RAM quickly before flushing the first batch on disk. I changed its batch size to 256 to use maximum 100MB of memory
Fix #3167. | {
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https://api.github.com/repos/huggingface/datasets/issues/3278 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3278/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3278/comments | https://api.github.com/repos/huggingface/datasets/issues/3278/events | https://github.com/huggingface/datasets/pull/3278 | 1,054,249,463 | PR_kwDODunzps4uj2EQ | 3,278 | Proposed update to the documentation for WER | {
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} | I wanted to submit a minor update to the description of WER for your consideration.
Because of the possibility of insertions, the numerator in the WER formula can be larger than N, so the value of WER can be greater than 1.0:
```
>>> from datasets import load_metric
>>> metric = load_metric("wer")
>>> metric.compute(predictions=["hello how are you"], references=["hello"])
3.0
```
and similarly from the underlying jiwer module's `wer` function:
```
>>> from jiwer import wer
>>> wer("hello", "hello how are you")
3.0
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3277/comments | https://api.github.com/repos/huggingface/datasets/issues/3277/events | https://github.com/huggingface/datasets/pull/3277 | 1,054,122,656 | PR_kwDODunzps4ujk11 | 3,277 | f-string formatting | {
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} | **Fix #3257**
Replaced _.format()_ and _%_ by f-strings in the following modules :
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**
- [x] **src/Datasets/\*.py**
Modules in **_src/Datasets/_**:
- [x] **commands**
- [x] **features**
- [x] **formatting**
- [x] **io**
- [x] **tasks**
- [x] **utils**
Module **datasets** will not be edited as asked by @mariosasko
-A correction of the first PR (#3267)-
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} | Avoids weird issues when redownloading a dataset due to cached data not being fully updated.
With this change, issues #3122 and https://github.com/huggingface/datasets/issues/2956 (not a fix, but a workaround) can be fixed as follows:
```python
dset = load_dataset(..., download_mode="force_redownload")
``` | {
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} | As reported in https://github.com/huggingface/datasets/issues/3188 some contact information are not displayed correctly.
This PR fixes this for CoNLL-2002 and some other datasets with the same issue | {
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] | closed | false | null | [] | null | 0 | "2021-11-15T11:27:14Z" | "2021-11-17T15:41:11Z" | "2021-11-17T15:41:11Z" | CONTRIBUTOR | null | null | null | Currently, there is a bug when concatenating datasets along `axis=1` if more than one dataset has the `_indices` attribute defined. In that scenario, all indices mappings except the first one get ignored.
A minimal reproducible example:
```python
>>> from datasets import Dataset, concatenate_datasets
>>> a = Dataset.from_dict({"a": [30, 20, 10]})
>>> b = Dataset.from_dict({"b": [2, 1, 3]})
>>> d = concatenate_datasets([a.sort("a"), b.sort("b")], axis=1)
>>> print(d[:3]) # expected: {'a': [10, 20, 30], 'b': [1, 2, 3]}
{'a': [10, 20, 30], 'b': [3, 1, 2]}
```
I've noticed the bug while working on #3195. | {
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] | null | 4 | "2021-11-15T10:50:42Z" | "2021-11-25T00:08:47Z" | null | MEMBER | null | null | null | Currently users can use `dl_manager.iter_archive` in their dataset script to iterate over all the files of a TAR archive.
It would be nice if it could work with ZIP files too ! | {
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https://api.github.com/repos/huggingface/datasets/issues/3271 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3271/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3271/comments | https://api.github.com/repos/huggingface/datasets/issues/3271/events | https://github.com/huggingface/datasets/pull/3271 | 1,053,482,919 | PR_kwDODunzps4uhgi1 | 3,271 | Decode audio from remote | {
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} | Currently the Audio feature type can only decode local audio files, not remote files.
To fix this I replaced `open` with our `xopen` functoin that is compatible with remote files in audio.py
cc @albertvillanova @mariosasko | {
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https://api.github.com/repos/huggingface/datasets/issues/3270 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3270/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3270/comments | https://api.github.com/repos/huggingface/datasets/issues/3270/events | https://github.com/huggingface/datasets/pull/3270 | 1,053,465,662 | PR_kwDODunzps4uhcxm | 3,270 | Add os.listdir for streaming | {
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] | null | 18 | "2021-11-15T05:04:07Z" | "2022-01-19T13:58:19Z" | "2022-01-19T13:58:19Z" | NONE | null | null | null | ```
>>> from datasets import load_dataset
>>> dataset = load_dataset("coqa")
Downloading: 3.82kB [00:00, 1.26MB/s]
Downloading: 1.79kB [00:00, 733kB/s]
Using custom data configuration default
Downloading and preparing dataset coqa/default (download: 55.40 MiB, generated: 18.35 MiB, post-processed: Unknown size, total: 73.75 MiB) to /Users/zhaofengw/.cache/huggingface/datasets/coqa/default/1.0.0/553ce70bfdcd15ff4b5f4abc4fc2f37137139cde1f58f4f60384a53a327716f0...
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.38MB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.32MB/s]
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00, 1.91it/s]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1117.44it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 679, in _download_and_prepare
verify_checksums(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json', 'https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json']
``` | {
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