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https://api.github.com/repos/huggingface/datasets/issues/5030

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PR_kwDODunzps4_tfBO

Fast dataset iter

closed

COLLABORATOR

Use `pa.Table.to_reader` to make iteration over examples/batches faster in `Dataset.{__iter__, map}` TODO: * [x] benchmarking (the only benchmark for now - iterating over (single) examples of `bookcorpus` (75 mil examples) in Colab is approx. 2.3x faster) * [x] check if iterating over bigger chunks + slicing to fetch individual examples in `_iter` yields better performance

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PR_kwDODunzps4_r8-j

Fix import in `ClassLabel` docstring example

closed

CONTRIBUTOR

This PR addresses a super-simple fix: adding a missing `import` to the `ClassLabel` docstring example, as it was formatted as `from datasets Features`, so it's been fixed to `from datasets import Features`.

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https://github.com/huggingface/datasets/issues/5028

I_kwDODunzps5SoNcV

passing parameters to the method passed to Dataset.from_generator()

closed

NONE

Big thanks for providing dataset creation via a generator. I want to ask whether there is any way that parameters can be passed to the method Dataset.from_generator() method, like as follows. ``` from datasets import Dataset def gen(param1): for idx in len(custom_dataset): yield custom_dataset[idx] + param1 ds = Dataset.from_generator(gen(param1)) ```

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PR_kwDODunzps4_nFUE

Fix typo in error message

closed

CONTRIBUTOR

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https://github.com/huggingface/datasets/pull/5026

PR_kwDODunzps4_mz1w

patch CI_HUB_TOKEN_PATH with Path instead of str

closed

CONTRIBUTOR

Should fix the tests for `huggingface_hub==0.10.0rc0` prerelease (see [failed CI](https://github.com/huggingface/datasets/actions/runs/3127805250/jobs/5074879144)). Related to [this thread](https://huggingface.slack.com/archives/C02V5EA0A95/p1664195165294559) (internal link). Note: this should be a backward compatible fix (e.g. works also with previous versions of `huggingface_hub`) I am not sure where to put the changes so feel free to cherry-pick the commit and close this one without merging. cc @lhoestq

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I_kwDODunzps5SnNpn

Custom Json Dataset Throwing Error when batch is False

closed

NONE

## Describe the bug A clear and concise description of what the bug is. I tried to create my custom dataset using below code ``` from datasets import Features, Sequence, ClassLabel, Value, Array2D, Array3D from torchvision import transforms from transformers import AutoProcessor # we'll use the Auto API here - it will load LayoutLMv3Processor behind the scenes, # based on the checkpoint we provide from the hub from datasets import load_dataset def prepare_examples(examples): #Some preporcessing for each image and text as all my data saved in cloud #For this reason I couldn't set the batch to True. encoding = processor(img_as_tensor, words, boxes=boxes, word_labels=labels, truncation=True, padding="max_length") # encoding['pixel_values']=np.array(encoding['pixel_values']) return encoding dataset = load_dataset("json", data_files='issues.jsonl') processor = AutoProcessor.from_pretrained("microsoft/layoutlmv3-base", apply_ocr=False) features = dataset["train"].features column_names = dataset["train"].column_names # we need to define custom features for `set_format` (used later on) to work properly features = Features({ 'pixel_values': Array3D(dtype="float32", shape=(3, 224, 224)), 'input_ids': Sequence(feature=Value(dtype='int64')), 'attention_mask': Sequence(Value(dtype='int64')), 'bbox': Array2D(dtype="int64", shape=(512, 4)), 'labels': Sequence(feature=Value(dtype='int64')), }) train_dataset = dataset["train"].map( prepare_examples, batched=False, remove_columns=column_names, features=features ) ``` It throws below error. ``` /opt/conda/lib/python3.7/site-packages/datasets/arrow_writer.py in __arrow_array__(self, type) 172 storage = to_pyarrow_listarray(data, pa_type) --> 173 return pa.ExtensionArray.from_storage(pa_type, storage) 174 /opt/conda/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib.ExtensionArray.from_storage() TypeError: Incompatible storage type list<item: list<item: list<item: list<item: float>>>> for extension type extension<arrow.py_extension_type<Array3DExtensionType>> ``` ## Steps to reproduce the bug ```python # Sample code to reproduce the bug ``` rom datasets import Features, Sequence, ClassLabel, Value, Array2D, Array3D from torchvision import transforms from transformers import AutoProcessor # we'll use the Auto API here - it will load LayoutLMv3Processor behind the scenes, # based on the checkpoint we provide from the hub from datasets import load_dataset def prepare_examples(examples): #Some preporcessing for each image and text as all my data saved in cloud encoding = processor(img_as_tensor, words, boxes=boxes, word_labels=labels, truncation=True, padding="max_length") # encoding['pixel_values']=np.array(encoding['pixel_values']) return encoding dataset = load_dataset("json", data_files='issues.jsonl') processor = AutoProcessor.from_pretrained("microsoft/layoutlmv3-base", apply_ocr=False) features = dataset["train"].features column_names = dataset["train"].column_names # we need to define custom features for `set_format` (used later on) to work properly features = Features({ 'pixel_values': Array3D(dtype="float32", shape=(3, 224, 224)), 'input_ids': Sequence(feature=Value(dtype='int64')), 'attention_mask': Sequence(Value(dtype='int64')), 'bbox': Array2D(dtype="int64", shape=(512, 4)), 'labels': Sequence(feature=Value(dtype='int64')), }) train_dataset = dataset["train"].map( prepare_examples, batched=False, remove_columns=column_names, features=features ) ## Expected results A clear and concise description of the expected results. Expected would be similar to all the otherdatasets with no error. ## 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: - Platform: Unix - Python version: 3.9 - PyArrow version: 9.0.0

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https://github.com/huggingface/datasets/pull/5024

PR_kwDODunzps4_mZ3J

Fix string features of xcsr dataset

closed

MEMBER

This PR fixes string features of `xcsr` dataset to avoid character splitting. Fix #5023. CC: @yangxqiao, @yuchenlin

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I_kwDODunzps5Smt4Y

Text strings are split into lists of characters in xcsr dataset

closed

MEMBER

## Describe the bug Text strings are split into lists of characters. Example for "X-CSQA-en": ``` {'id': 'd3845adc08414fda', 'lang': 'en', 'question': {'stem': ['T', 'h', 'e', ' ', 'd', 'e', 'n', 't', 'a', 'l', ' ', 'o', 'f', 'f', 'i', 'c', 'e', ' ', 'h', 'a', 'n', 'd', 'l', 'e', 'd', ' ', 'a', ' ', 'l', 'o', 't', ' ', 'o', 'f', ' ', 'p', 'a', 't', 'i', 'e', 'n', 't', 's', ' ', 'w', 'h', 'o', ' ', 'e', 'x', 'p', 'e', 'r', 'i', 'e', 'n', 'c', 'e', 'd', ' ', 't', 'r', 'a', 'u', 'm', 'a', 't', 'i', 'c', ' ', 'm', 'o', 'u', 't', 'h', ' ', 'i', 'n', 'j', 'u', 'r', 'y', ',', ' ', 'w', 'h', 'e', 'r', 'e', ' ', 'w', 'e', 'r', 'e', ' ', 't', 'h', 'e', 's', 'e', ' ', 'p', 'a', 't', 'i', 'e', 'n', 't', 's', ' ', 'c', 'o', 'm', 'i', 'n', 'g', ' ', 'f', 'r', 'o', 'm', '?'], 'choices': [{'label': ['A'], 'text': ['t', 'o', 'w', 'n']}, {'label': ['B'], 'text': ['m', 'i', 'c', 'h', 'i', 'g', 'a', 'n']}, {'label': ['C'], 'text': ['h', 'o', 's', 'p', 'i', 't', 'a', 'l']}, {'label': ['D'], 'text': ['s', 'c', 'h', 'o', 'o', 'l', 's']}, {'label': ['E'], 'text': ['o', 'f', 'f', 'i', 'c', 'e', ' ', 'b', 'u', 'i', 'l', 'd', 'i', 'n', 'g']}]}, 'answerKey': 'C'} ## Steps to reproduce the bug ```python ds = load_dataset("datasets/xcsr", "X-CSQA-en", split="validation", streaming=True) item = next(iter(ds)) item ``` ## Expected results ``` {'id': 'd3845adc08414fda', 'lang': 'en', 'question': {'stem': 'The dental office handled a lot of patients who experienced traumatic mouth injury, where were these patients coming from?', 'choices': {'label': ['A', 'B', 'C', 'D', 'E'], 'text': ['town', 'michigan', 'hospital', 'schools', 'office building']}}, 'answerKey': 'C'} ```

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https://github.com/huggingface/datasets/pull/5022

PR_kwDODunzps4_kxYe

Fix languages of X-CSQA configs in xcsr dataset

closed

MEMBER

Fix #5017. CC: @yangxqiao, @yuchenlin

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I_kwDODunzps5SkshS

Split is inferred from filename and overrides metadata.jsonl

closed

NONE

## Describe the bug Including the strings "test" or "train" anywhere in a filename causes `datasets` to infer the split and silently ignore all other files. This behavior is documented for directory names but not filenames: https://huggingface.co/docs/datasets/image_dataset#imagefolder ## Steps to reproduce the bug `metadata.jsonl` ```json {"file_name": "photo of a cat.jpg", "text": "a photo of a cat"} {"file_name": "photo of a dog.jpg", "text": "a photo of a dog"} {"file_name": "photo of a train.jpg", "text": "a photo of a train"} {"file_name": "photo of test tubes.jpg", "text": "a photo of test tubes"} ``` `bug.py` ```python from datasets import load_dataset dataset = load_dataset("dataset") print(dataset) # DatasetDict({ # train: Dataset({ # features: ['image', 'text'], # num_rows: 1 # }) # test: Dataset({ # features: ['image', 'text'], # num_rows: 1 # }) # }) for split in dataset: for n in dataset[split]: print(n['text']) # a photo of a train # a photo of test tubes ``` ## Expected results One single dataset with all four images / a warning for unused files / documentation of this behavior ## Actual results Only the images with "test" or "train" in the name are loaded ## Environment info - `datasets` version: 2.5.1 - Platform: macOS-12.5.1-x86_64-i386-64bit - Python version: 3.10.4 - PyArrow version: 9.0.0 - Pandas version: 1.5.0

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PR_kwDODunzps4_istJ

Fix URLs of sbu_captions dataset

closed

CONTRIBUTOR

Forbidden You don't have permission to access /~vicente/sbucaptions/sbu-captions-all.tar.gz on this server. Additionally, a 403 Forbidden error was encountered while trying to use an ErrorDocument to handle the request. Apache/2.4.6 (Red Hat Enterprise Linux) OpenSSL/1.0.2k-fips PHP/5.4.16 mod_fcgid/2.3.9 mod_wsgi/3.4 Python/2.7.5 mod_perl/2.0.11 Perl/v5.16.3 Server at [www.cs.virginia.edu](mailto:csroot@virginia.edu) Port 443

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PR_kwDODunzps4_iq9b

Update swiss judgment prediction

closed

CONTRIBUTOR

Hi, I updated the dataset to include additional data made available recently. When I test it locally, it seems to work. However, I get the following error with the dummy data creation: `Dummy data generation done but dummy data test failed since splits ['train', 'validation', 'test'] have 0 examples for config 'fr'`. Do you know why this could be the case? Cheers, Joel

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PR_kwDODunzps4_hA0V

Create all YAML dataset_info

closed

MEMBER

Following https://github.com/huggingface/datasets/pull/4926 Creates all the `dataset_info` YAML fields in the dataset cards The JSON are also updated using the simplified backward compatible format added in https://github.com/huggingface/datasets/pull/4926 Needs https://github.com/huggingface/datasets/pull/4926 to be merged first

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I_kwDODunzps5SfoG_

xcsr: X-CSQA simply uses english for all alleged non-english data

closed

NONE

## Describe the bug All the alleged non-english subcollections for the X-CSQA task in the [xcsr benchmark dataset ](https://huggingface.co/datasets/xcsr) seem to be copies of the english subcollection, rather than translations. This is in contrast to the data description: > we automatically translate the original CSQA and CODAH datasets, which only have English versions, to 15 other languages, forming development and test sets for studying X-CSR ## Steps to reproduce the bug ```python # let's say you want to load the french X-CSQA subcollection french = datasets.load_dataset("xcsr", "X-CSQA-fr") # for good measure, let's load english too english = datasets.load_dataset("xcsr", "X-CSQA-en") # let's inspect "".join(english['test'][0]['question']['stem']) # output: 'The people wanted to stop the parade, so what did they set up to thwart it?' "".join(french['test'][0]['question']['stem']) # output: 'The people wanted to stop the parade, so what did they set up to thwart it?' # what? Why are they both in english? # I've checked this for validation and train splits too, across many datapoints. It's all the same english dataset # maybe i need to look better? french['test'].unique('lang') # output: ['en'] # no, it's all english ``` ## Expected results Accessing a subcollection in language X should return a subcollection containg samples in language X ## Actual results Accessing a subcollection in language X returns a subcollection containing samples in English. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.5.1 - Platform: macOS-10.15.7-x86_64-i386-64bit - Python version: 3.8.13 - PyArrow version: 9.0.0 - Pandas version: 1.4.3

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PR_kwDODunzps4_gKny

Fix tar extraction vuln

closed

MEMBER

Fix for CVE-2007-4559 Description: Directory traversal vulnerability in the (1) extract and (2) extractall functions in the tarfile module in Python allows user-assisted remote attackers to overwrite arbitrary files via a .. (dot dot) sequence in filenames in a TAR archive, a related issue to CVE-2001-1267. I fixed it by using the solution proposed in https://stackoverflow.com/questions/10060069/safely-extract-zip-or-tar-using-python It blocks extraction of files with an absolute path or double dots and symlinks.

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I_kwDODunzps5SdlB2

Transfer dataset scripts to Hub

closed

MEMBER

Before merging: - #4974 TODO: - [x] Create label: ["dataset contribution"](https://github.com/huggingface/datasets/pulls?q=label%3A%22dataset+contribution%22) - [x] Create project: [Datasets: Transfer datasets to Hub](https://github.com/orgs/huggingface/projects/22/) - [x] PRs: - [x] Add dataset: we should recommend transfer all additions of datasets to the Hub, under the appropriate namespace; no more additions of datasets on GitHub - [x] Update dataset: in general, we should merge bug fixes; enhancements should be considered on a case-by-case basis, depending on whether there is a more suitable namespace on the Hub - [ ] Issues Finally: - [x] #4974 Let me know what you think! :hugs:

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I_kwDODunzps5SdVqv

I need to read the custom dataset in conll format

open

NONE

I need to read the custom dataset in conll format

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I_kwDODunzps5SdUCj

would huggingface like publish cpp binding for datasets package ?

closed

NONE

HI: I use cpp env libtorch, I like use hugggingface ,but huggingface not cpp binding, would you like publish cpp binding for it. thanks

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I_kwDODunzps5SbKIY

Force JSON format regardless of file naming on S3

closed

NONE

I have a file on S3 created by Data Version Control, it looks like `s3://dvc/ac/badff5b134382a0f25248f1b45d7b2` but contains a json file. If I run ```python dataset = load_dataset( "json", data_files='s3://dvc/ac/badff5b134382a0f25248f1b45d7b2' ) ``` It gives me ``` InvalidSchema: No connection adapters were found for 's3://dvc/ac/badff5b134382a0f25248f1b45d7b2' ``` However, I cannot go ahead and change the names of the s3 file. Is there a way to "force" load a S3 url with certain decoder (JSON, CSV, etc.) regardless of s3 URL naming?

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I_kwDODunzps5SaPKz

Audio: `encode_example` fails with IndexError

closed

CONTRIBUTOR

## Describe the bug Loading the dataset [earnings-22](https://huggingface.co/datasets/sanchit-gandhi/earnings22_split) from the Hub yields an Index Error. I created this dataset locally and then pushed to hub at the specified URL. Thus, I expect the dataset should work out-of-the-box! Indeed, the dataset viewer functions correctly, and there were no issues when I had the dataset locally. Don't think it's a sound file bug as the version matches what worked previously. Update: the bug appeared for me on a GPU, mysteriously on a TPU I can't repro and it downloads correctly... ## Steps to reproduce the bug ```python from datasets import load_dataset earnings22 = load_dataset("sanchit-gandhi/earnings22_split") ``` ## Expected results ``` >>> earnings22 DatasetDict({ validation: Dataset({ features: ['source_id', 'audio', 'segment_id', 'sentence', 'start_ts', 'end_ts', 'id'], num_rows: 2650 }) train: Dataset({ features: ['source_id', 'audio', 'segment_id', 'sentence', 'start_ts', 'end_ts', 'id'], num_rows: 52006 }) test: Dataset({ features: ['source_id', 'audio', 'segment_id', 'sentence', 'start_ts', 'end_ts', 'id'], num_rows: 2735 }) }) ``` ## Actual results ``` Traceback (most recent call last): File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2764, in _map_single writer.write(example) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/arrow_writer.py", line 451, in write self.write_examples_on_file() File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/arrow_writer.py", line 409, in write_examples_on_file self.write_batch(batch_examples=batch_examples) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/arrow_writer.py", line 508, in write_batch arrays.append(pa.array(typed_sequence)) File "pyarrow/array.pxi", line 231, in pyarrow.lib.array File "pyarrow/array.pxi", line 110, in pyarrow.lib._handle_arrow_array_protocol File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/arrow_writer.py", line 197, in __arrow_array__ out = cast_array_to_feature(out, type, allow_number_to_str=not self.trying_type) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/table.py", line 1683, in wrapper return func(array, *args, **kwargs) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/table.py", line 1795, in cast_array_to_feature return feature.cast_storage(array) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/features/audio.py", line 190, in cast_storage storage = pa.array([Audio().encode_example(x) if x is not None else None for x in storage.to_pylist()]) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/features/audio.py", line 190, in <listcomp> storage = pa.array([Audio().encode_example(x) if x is not None else None for x in storage.to_pylist()]) File "/opt/conda/envs/hf/lib/python3.8/site-packages/datasets/features/audio.py", line 92, in encode_example sf.write(buffer, value["array"], value["sampling_rate"], format="wav") File "/opt/conda/envs/hf/lib/python3.8/site-packages/soundfile.py", line 313, in write channels = data.shape[1] IndexError: tuple index out of range ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.4.0 - Platform: Linux-4.19.0-21-cloud-amd64-x86_64-with-glibc2.10 - Python version: 3.8.13 - PyArrow version: 9.0.0 - Pandas version: 1.4.3 Plus: - SoundFile version: 0.10.3.post1 cc @lhoestq @polinaeterna

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PR_kwDODunzps4_bB3q

Add deprecation warning to multilingual_librispeech dataset card

closed

MEMBER

Besides the current deprecation warning in the script of `multilingual_librispeech`, this PR adds a deprecation warning to its dataset card as well. The format of the deprecation warning is aligned with the one in the library documentation when docstrings contain the `<Deprecated/>` tag. Related to: - #4060

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I_kwDODunzps5SU1lT

Error loading StonyBrookNLP/tellmewhy dataset from hub even though local copy loads correctly

closed

NONE

## Describe the bug I have added a new dataset with the identifier `StonyBrookNLP/tellmewhy` to the hub. When I load the individual files using my local copy using `dataset = datasets.load_dataset("json", data_files="data/train.jsonl")`, it loads the dataset correctly. However, when I try to load it from the hub, I get an error (pasted below). Additionally, `dataset = datasets.load_dataset("json", data_dir="data/")` throws the same error. ## Steps to reproduce the bug ```python dataset = datasets.load_dataset('StonyBrookNLP/tellmewhy') ``` ## Expected results Successfully load the `StonyBrookNLP/tellmewhy` dataset. ## Actual results ``` Using custom data configuration StonyBrookNLP--tellmewhy-82712924092694ff Downloading and preparing dataset json/StonyBrookNLP--tellmewhy to /home/yklal95/.cache/huggingface/datasets/StonyBrookNLP___json/StonyBrookNLP--tellmewhy-82712924092694ff/0.0.0/a3e658c4731e59120d44081ac10bf85dc7e1388126b92338344ce9661907f253... Downloading data files: 100%|██████████████████████████████| 3/3 [00:00<00:00, 957.46it/s] Extracting data files: 100%|███████████████████████████████| 3/3 [00:00<00:00, 299.14it/s] Traceback (most recent call last): File "/home/yklal95/tmw-generalization/src/load_datasets.py", line 17, in <module> main(args) File "/home/yklal95/tmw-generalization/src/load_datasets.py", line 11, in main dataset = datasets.load_dataset(args.dataset_name) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/load.py", line 1746, in load_dataset builder_instance.download_and_prepare( File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare self._download_and_prepare( File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 793, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 1277, in _prepare_split writer.write_table(table) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/arrow_writer.py", line 524, in write_table pa_table = table_cast(pa_table, self._schema) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 2005, in table_cast return cast_table_to_schema(table, schema) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1969, in cast_table_to_schema arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1969, in <listcomp> arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1681, in wrapper return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1681, in <listcomp> return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1822, in cast_array_to_feature casted_values = _c(array.values, feature.feature) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1683, in wrapper return func(array, *args, **kwargs) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1853, in cast_array_to_feature return array_cast(array, feature(), allow_number_to_str=allow_number_to_str) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1683, in wrapper return func(array, *args, **kwargs) File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1761, in array_cast raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}") TypeError: Couldn't cast array of type int64 to null ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.4.0 - Platform: Linux-4.15.0-121-generic-x86_64-with-glibc2.27 - Python version: 3.9.13 - PyArrow version: 9.0.0 - Pandas version: 1.5.0

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PR_kwDODunzps4_XAc5

Re-apply input columns change

closed

COLLABORATOR

Fixes the `filter` + `input_columns` combination, which is used in the `transformers` examples for instance. Revert #5006 (which in turn reverts #4971) Fix https://github.com/huggingface/datasets/issues/4858

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PR_kwDODunzps4_WvFQ

Add some note about running the transformers ci before a release

closed

MEMBER

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PR_kwDODunzps4_Wm8z

Revert input_columns change

closed

MEMBER

Revert https://github.com/huggingface/datasets/pull/4971 Fix https://github.com/huggingface/datasets/issues/5005

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I_kwDODunzps5ST6uA

Release 2.5.0 breaks transformers CI

closed

MEMBER

## Describe the bug As reported by @lhoestq: > see https://app.circleci.com/pipelines/github/huggingface/transformers/47634/workflows/b491886b-e66e-4edb-af96-8b459e72aa25/jobs/564563 this is used here: [https://github.com/huggingface/transformers/blob/3b19c0317b6909e2d7f11b5053895ac55[…]torch/speech-pretraining/run_wav2vec2_pretraining_no_trainer.py](https://github.com/huggingface/transformers/blob/3b19c0317b6909e2d7f11b5053895ac55250e7da/examples/pytorch/speech-pretraining/run_wav2vec2_pretraining_no_trainer.py#L482-L488)

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PR_kwDODunzps4_WQck

Remove license tag file and validation

closed

MEMBER

As requested, we are removing the validation of the licenses from `datasets` because this is done on the Hub. Fix #4994. Related to: - #4926, which is removing all the validation from `datasets`

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PR_kwDODunzps4_Vdko

Fix missing use_auth_token in streaming docstrings

closed

MEMBER

This PRs fixes docstrings: - adds the missing `use_auth_token` param - updates syntax of param types - adds params to docstrings without them - fixes return/yield types - fixes syntax

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I_kwDODunzps5SSh9a

Dataset Viewer issue for loubnabnl/humaneval-x

closed

NONE

### Link https://huggingface.co/datasets/loubnabnl/humaneval-x/viewer/ ### Description The dataset has subsets but the viewer gets stuck in the default subset even when I select another one (the data loading of the subsets works fine) ### Owner Yes

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PR_kwDODunzps4_TBWa

Support loading XML datasets

open

MEMBER

CC: @davanstrien

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I_kwDODunzps5SPLHW

Dataset Viewer issue for asapp/slue

closed

NONE

### Link https://huggingface.co/datasets/asapp/slue/viewer/ ### Description Hi, I wonder how to get the dataset viewer of our slue dataset to work. Best, Felix ### Owner Yes

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PR_kwDODunzps4_SQxL

Add EmptyDatasetError

closed

MEMBER

examples: from the hub: ```python Traceback (most recent call last): File "playground/ttest.py", line 3, in <module> print(load_dataset("lhoestq/empty")) File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1686, in load_dataset **config_kwargs, File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1458, in load_dataset_builder data_files=data_files, File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1171, in dataset_module_factory raise e1 from None File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1162, in dataset_module_factory download_mode=download_mode, File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 760, in get_module else get_data_patterns_in_dataset_repository(hfh_dataset_info, self.data_dir) File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/data_files.py", line 678, in get_data_patterns_in_dataset_repository ) from None datasets.data_files.EmptyDatasetError: The dataset repository at 'lhoestq/empty' doesn't contain any data file. ``` from local directory: ```python Traceback (most recent call last): File "playground/ttest.py", line 3, in <module> print(load_dataset("playground/empty")) File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1686, in load_dataset **config_kwargs, File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1458, in load_dataset_builder data_files=data_files, File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 1107, in dataset_module_factory path, data_dir=data_dir, data_files=data_files, download_mode=download_mode File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/load.py", line 625, in get_module else get_data_patterns_locally(base_path) File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/data_files.py", line 460, in get_data_patterns_locally raise EmptyDatasetError(f"The directory at {base_path} doesn't contain any data file") from None datasets.data_files.EmptyDatasetError: The directory at playground/empty doesn't contain any data file ``` Close https://github.com/huggingface/datasets/issues/4995

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PR_kwDODunzps4_Ryp3

Don't add a tag on the Hub on release

closed

MEMBER

Datasets with no namespace on the Hub have tags to redirect to the version of datasets where they come from. I’m about to remove them all because I think it looks bad/unexpected in the UI and it’s not actually useful Therefore I'm also disabling tagging. Note that the CI job will be completely removed in https://github.com/huggingface/datasets/pull/4974 anyway

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PR_kwDODunzps4_RrBU

Add support for parsing JSON files in array form

closed

COLLABORATOR

Support parsing JSON files in the array form (top-level object is an array). For simplicity, `json.load` is used for decoding. This means the entire file is loaded into memory. If requested, we can optimize this by introducing a param similar to `lines` in [`pandas.read_json`](https://pandas.pydata.org/docs/reference/api/pandas.read_json.html), which, if set to `True`, would allow us to read in chunks. Fixes https://github.com/huggingface/datasets/issues/4963

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I_kwDODunzps5SNyMJ

Dataset Viewer issue for Jean-Baptiste/wikiner_fr

closed

CONTRIBUTOR

### Link https://huggingface.co/datasets/Jean-Baptiste/wikiner_fr ### Description ``` Error code: StreamingRowsError Exception: FileNotFoundError Message: [Errno 2] No such file or directory: 'zip:/data/train::https:/huggingface.co/datasets/Jean-Baptiste/wikiner_fr/resolve/main/data.zip/state.json' Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/responses/first_rows.py", line 337, in get_first_rows_response rows = get_rows(dataset, config, split, streaming=True, rows_max_number=rows_max_number, hf_token=hf_token) File "/src/services/worker/src/worker/utils.py", line 123, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/responses/first_rows.py", line 77, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 718, in __iter__ for key, example in self._iter(): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 708, in _iter yield from ex_iterable File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 112, in __iter__ yield from self.generate_examples_fn(**self.kwargs) File "/tmp/modules-cache/datasets_modules/datasets/Jean-Baptiste--wikiner_fr/683a580ba6ec769d508f7dfc603a651667b0ed3817b1ae5bfd45f97cc024923f/wikiner_fr.py", line 165, in _generate_examples dataset = Dataset.load_from_disk(filepath) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 1210, in load_from_disk with open(Path(dataset_path, config.DATASET_STATE_JSON_FILENAME).as_posix(), encoding="utf-8") as state_file: FileNotFoundError: [Errno 2] No such file or directory: 'zip:/data/train::https:/huggingface.co/datasets/Jean-Baptiste/wikiner_fr/resolve/main/data.zip/state.json' ``` Is it an error with the dataset script, or the data itself, @huggingface/datasets? https://huggingface.co/datasets/Jean-Baptiste/wikiner_fr/tree/main ### Owner No

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I_kwDODunzps5SM4aC

Get a specific Exception when the dataset has no data

closed

CONTRIBUTOR

In the dataset viewer on the Hub (https://huggingface.co/datasets/glue/viewer), we would like (https://github.com/huggingface/moon-landing/issues/3882) to show a specific message when the repository lacks any data files. In that case, instead of showing a complex traceback, we want to show a call to action to help the user upload data. To do that, it would be very helpful to know for sure that the repository is missing any (supported) data files. It could be done by raising a custom exception, for example, `NoDataError`.

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I_kwDODunzps5SMybv

delete the hardcoded license list in `datasets`

closed

MEMBER

> Feel free to delete the license list in `datasets` [...] > > Also FYI in #4926 I also removed all the validation steps anyway (language, license, types etc.) _Originally posted by @lhoestq in https://github.com/huggingface/datasets/issues/4930#issuecomment-1238401662_ > [...], in my opinion we can just delete this file from `datasets`, the validation is happening hub-side anyways now? _Originally posted by @julien-c in https://github.com/huggingface/datasets/issues/4930#issuecomment-1238390659_

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PR_kwDODunzps4_QYas

fix: avoid casting tuples after Dataset.map

closed

CONTRIBUTOR

This PR updates features.py to avoid casting tuples to lists when reading the results of Dataset.map as suggested by @lhoestq [here](https://github.com/huggingface/datasets/issues/4676#issuecomment-1187371367) in https://github.com/huggingface/datasets/issues/4676.

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PR_kwDODunzps4_QVw4

Support streaming iwslt2017 dataset

closed

MEMBER

Support streaming iwslt2017 dataset. Once this PR is merged: - [x] Remove old ".tgz" data files from the Hub.

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PR_kwDODunzps4_P5hI

Fix missing tags in dataset cards

closed

MEMBER

Fix missing tags in dataset cards: - aeslc - empathetic_dialogues - event2Mind - gap - iwslt2017 - newsgroup - qa4mre - scicite This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task. Related to: - #4833 - #4891 - #4896 - #4908 - #4921 - #4931 - #4979

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I_kwDODunzps5SJHRm

"no-token" is passed to `huggingface_hub` when token is `None`

closed

CONTRIBUTOR

## Describe the bug In the 2 lines listed below, a token is passed to `huggingface_hub` to get information from a dataset. If no token is provided, a "no-token" string is passed. What is the purpose of it ? If no real, I would prefer if the `None` value could be sent directly to be handle by `huggingface_hub`. I feel that here it is working because we assume the token will never be validated. https://github.com/huggingface/datasets/blob/5b23f58535f14cc4dd7649485bce1ccc836e7bca/src/datasets/load.py#L753 https://github.com/huggingface/datasets/blob/5b23f58535f14cc4dd7649485bce1ccc836e7bca/src/datasets/load.py#L1121 ## Expected results Pass `token=None` to `huggingface_hub`. ## Actual results `token="no-token"` is passed. ## Environment info `huggingface_hub v0.10.0dev`

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I_kwDODunzps5SEMrp

Running add_column() seems to corrupt existing sequence-type column info

closed

NONE

I have a dataset that contains a column ("foo") that is a sequence type of length 4. So when I run .to_pandas() on it, the resulting dataframe correctly contains 4 columns - foo_0, foo_1, foo_2, foo_3. So the 1st row of the dataframe might look like: ds = load_dataset(...) df = ds.to_pandas() df: foo_0 | foo_1 | foo_2 | foo_3 0.0 | 1.0 | 2.0 | 3.0 If I run .add_column("new_col", data) on the dataset, and then .to_pandas() on the resulting new dataset, the resulting dataframe contains only 2 columns - foo, new_col. The values in column foo are lists of length 4, the 4 elements that should have been split into separate columns. Dataframe 1st row would be: ds = load_dataset(...) new_ds = ds.add_column("new_col", data) df = new_ds.to_pandas() df: foo | new_col [0.0, 1.0, 2.0, 3.0] | new_val I've explored the 2 datasets in a debugger and haven't noticed any changes to any attributes related to the foo column, but I can't determine why the dataframes are so different.

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I_kwDODunzps5SBZFI

Add `IterableDataset.from_generator` to the API

closed

COLLABORATOR

We've just added `Dataset.from_generator` to the API. It would also be cool to add `IterableDataset.from_generator` to support creating an iterable dataset from a generator. cc @lhoestq

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PR_kwDODunzps4_GlIu

Embed image/audio data in dl_and_prepare parquet

closed

MEMBER

Embed the bytes of the image or audio files in the Parquet files directly, instead of having a "path" that points to a local file. Indeed Parquet files are often used to share data or to be used by workers that may not have access to the local files.

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PR_kwDODunzps4_GNSd

[doc] Fix broken snippet that had too many quotes

closed

MEMBER

Hello! ### Pull request overview * Fix broken snippet in https://huggingface.co/docs/datasets/main/en/process that has too many quotes ### Details The snippet in question can be found here: https://huggingface.co/docs/datasets/main/en/process#map This screenshot shows the issue, there is a quote too many, causing the snippet to be colored incorrectly:  The change speaks for itself. Thank you for the detailed documentation, by the way. - Tom Aarsen

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PR_kwDODunzps4_F6kU

Prefer split patterns from directories over split patterns from filenames

closed

CONTRIBUTOR

related to https://github.com/huggingface/datasets/issues/4895

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PR_kwDODunzps4_FhTm

docs: ✏️ add links to the Datasets API

closed

CONTRIBUTOR

I added some links to the Datasets API in the docs. See https://github.com/huggingface/datasets-server/pull/566 for a companion PR in the datasets-server. The idea is to improve the discovery of the API through the docs. I'm a bit shy about pasting a lot of links to the API in the docs, so it's minimal for now. I'm interested in ideas to integrate the API better in these docs without being too much. cc @lhoestq @julien-c @albertvillanova @stevhliu.

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I_kwDODunzps5R_wXG

How to convert torch.utils.data.Dataset to huggingface dataset?

closed

NONE

I look through the huggingface dataset docs, and it seems that there is no offical support function to convert `torch.utils.data.Dataset` to huggingface dataset. However, there is a way to convert huggingface dataset to `torch.utils.data.Dataset`, like below: ```python from datasets import Dataset data = [[1, 2],[3, 4]] ds = Dataset.from_dict({"data": data}) ds = ds.with_format("torch") ds[0] ds[:2] ``` So is there something I miss, or there IS no function to convert `torch.utils.data.Dataset` to huggingface dataset. If so, is there any way to do this convert? Thanks.

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I_kwDODunzps5R_g_V

Create dataset_infos.json with VALIDATION and TEST splits

closed

NONE

The problem is described in that [issue](https://github.com/huggingface/datasets/issues/4895#issuecomment-1247975569). > When I try to create data_infos.json using datasets-cli test Peter.py --save_infos --all_configs I get an error: > ValueError: Unknown split "test". Should be one of ['train']. > > The data_infos.json is created perfectly fine when I use only one split - datasets.Split.TRAIN > > You can find the code here: https://huggingface.co/datasets/sberbank-ai/Peter/tree/add_splits (add_splits branch) I tried to clear the cache folder, than I got an another error. I run: ``` git clone https://huggingface.co/datasets/sberbank-ai/Peter cd Peter git checkout add_splits # switch to a add_splits branch rm dataset_infos.json # remove local dataset_infos.json rm -r ~/.cache/huggingface # remove cached dataset_infos.json datasets-cli test Peter.py --save_infos --all_configs # trying to create new dataset_infos.json ``` The error message: ``` Using custom data configuration default Testing builder 'default' (1/1) Downloading and preparing dataset peter/default to /Users/kalinin/.cache/huggingface/datasets/peter/default/0.0.0/ef579519e140d6a40df2555996f26165f04c47557d7373709c8d7e7b4fd7465d... Downloading data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 5160.63it/s] Extracting data files: 0%| | 0/4 [00:00<?, ?it/s]Traceback (most recent call last): File "/usr/local/bin/datasets-cli", line 8, in <module> sys.exit(main()) File "/usr/local/lib/python3.9/site-packages/datasets/commands/datasets_cli.py", line 39, in main service.run() File "/usr/local/lib/python3.9/site-packages/datasets/commands/test.py", line 137, in run builder.download_and_prepare( File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 1227, in _download_and_prepare super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos) File "/usr/local/lib/python3.9/site-packages/datasets/builder.py", line 771, in _download_and_prepare split_generators = self._split_generators(dl_manager, **split_generators_kwargs) File "/Users/kalinin/.cache/huggingface/modules/datasets_modules/datasets/Peter/ef579519e140d6a40df2555996f26165f04c47557d7373709c8d7e7b4fd7465d/Peter.py", line 23, in _split_generators data_files = dl_manager.download_and_extract(_URLS) File "/usr/local/lib/python3.9/site-packages/datasets/download/download_manager.py", line 431, in download_and_extract return self.extract(self.download(url_or_urls)) File "/usr/local/lib/python3.9/site-packages/datasets/download/download_manager.py", line 403, in extract extracted_paths = map_nested( File "/usr/local/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 393, in map_nested mapped = [ File "/usr/local/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 394, in <listcomp> _single_map_nested((function, obj, types, None, True, None)) File "/usr/local/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 330, in _single_map_nested return function(data_struct) File "/usr/local/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 213, in cached_path output_path = ExtractManager(cache_dir=download_config.cache_dir).extract( File "/usr/local/lib/python3.9/site-packages/datasets/utils/extract.py", line 46, in extract self.extractor.extract(input_path, output_path, extractor_format) File "/usr/local/lib/python3.9/site-packages/datasets/utils/extract.py", line 263, in extract with FileLock(lock_path): File "/usr/local/lib/python3.9/site-packages/datasets/utils/filelock.py", line 399, in __init__ max_filename_length = os.statvfs(os.path.dirname(lock_file)).f_namemax FileNotFoundError: [Errno 2] No such file or directory: '' Exception ignored in: <function BaseFileLock.__del__ at 0x11caeec10> Traceback (most recent call last): File "/usr/local/lib/python3.9/site-packages/datasets/utils/filelock.py", line 328, in __del__ self.release(force=True) File "/usr/local/lib/python3.9/site-packages/datasets/utils/filelock.py", line 303, in release with self._thread_lock: AttributeError: 'UnixFileLock' object has no attribute '_thread_lock' Extracting data files: 0%| | 0/4 [00:00<?, ?it/s] ``` Can you help me please? ## Environment info - `datasets` version: 2.4.0 - Platform: macOS-12.5.1-x86_64-i386-64bit - Python version: 3.9.5 - PyArrow version: 9.0.0 - Pandas version: 1.2.4

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I_kwDODunzps5R9ii1

Can't create a dataset with `float16` features

open

CONTRIBUTOR

## Describe the bug I can't create a dataset with `float16` features. I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same exact error. The bug seems to arise from `datasets` casting the values to `double` and then `pyarrow` doesn't know how to convert those back to `float16`... does that sound right? Is there a way to bypass this since it's not necessary in the `numpy` and `torch` cases? Thanks! ## Steps to reproduce the bug All of the following raise the following error with the same exact (as far as I can tell) traceback: ```python ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float ``` ```python from datasets import Dataset, Features, Value Dataset.from_dict({"x": [0.0, 1.0, 2.0]}, features=Features(x=Value("float16"))) import numpy as np Dataset.from_dict({"x": np.arange(3, dtype=np.float16)}, features=Features(x=Value("float16"))) import torch Dataset.from_dict({"x": torch.arange(3).to(torch.float16)}, features=Features(x=Value("float16"))) ``` ## Expected results A dataset with `float16` features is successfully created. ## Actual results ```python --------------------------------------------------------------------------- ArrowNotImplementedError Traceback (most recent call last) Cell In [14], line 1 ----> 1 Dataset.from_dict({"x": [1.0, 2.0, 3.0]}, features=Features(x=Value("float16"))) File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/arrow_dataset.py:870, in Dataset.from_dict(cls, mapping, features, info, split) 865 mapping = features.encode_batch(mapping) 866 mapping = { 867 col: OptimizedTypedSequence(data, type=features[col] if features is not None else None, col=col) 868 for col, data in mapping.items() 869 } --> 870 pa_table = InMemoryTable.from_pydict(mapping=mapping) 871 if info.features is None: 872 info.features = Features({col: ts.get_inferred_type() for col, ts in mapping.items()}) File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:750, in InMemoryTable.from_pydict(cls, *args, **kwargs) 734 @classmethod 735 def from_pydict(cls, *args, **kwargs): 736 """ 737 Construct a Table from Arrow arrays or columns 738 (...) 748 :class:`datasets.table.Table`: 749 """ --> 750 return cls(pa.Table.from_pydict(*args, **kwargs)) File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/table.pxi:3648, in pyarrow.lib.Table.from_pydict() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/table.pxi:5174, in pyarrow.lib._from_pydict() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:343, in pyarrow.lib.asarray() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:231, in pyarrow.lib.array() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py:197, in TypedSequence.__arrow_array__(self, type) 192 # otherwise we can finally use the user's type 193 elif type is not None: 194 # We use cast_array_to_feature to support casting to custom types like Audio and Image 195 # Also, when trying type "string", we don't want to convert integers or floats to "string". 196 # We only do it if trying_type is False - since this is what the user asks for. --> 197 out = cast_array_to_feature(out, type, allow_number_to_str=not self.trying_type) 198 return out 199 except (TypeError, pa.lib.ArrowInvalid) as e: # handle type errors and overflows File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1683, in _wrap_for_chunked_arrays.<locals>.wrapper(array, *args, **kwargs) 1681 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) 1682 else: -> 1683 return func(array, *args, **kwargs) File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1853, in cast_array_to_feature(array, feature, allow_number_to_str) 1851 return array_cast(array, get_nested_type(feature), allow_number_to_str=allow_number_to_str) 1852 elif not isinstance(feature, (Sequence, dict, list, tuple)): -> 1853 return array_cast(array, feature(), allow_number_to_str=allow_number_to_str) 1854 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}") File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1683, in _wrap_for_chunked_arrays.<locals>.wrapper(array, *args, **kwargs) 1681 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) 1682 else: -> 1683 return func(array, *args, **kwargs) File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1762, in array_cast(array, pa_type, allow_number_to_str) 1760 if pa.types.is_null(pa_type) and not pa.types.is_null(array.type): 1761 raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}") -> 1762 return array.cast(pa_type) 1763 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}") File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:919, in pyarrow.lib.Array.cast() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/compute.py:389, in cast(arr, target_type, safe, options) 387 else: 388 options = CastOptions.safe(target_type) --> 389 return call_function("cast", [arr], options) File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/_compute.pyx:560, in pyarrow._compute.call_function() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/_compute.pyx:355, in pyarrow._compute.Function.call() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/error.pxi:144, in pyarrow.lib.pyarrow_internal_check_status() File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/error.pxi:121, in pyarrow.lib.check_status() ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float ``` ## Environment info - `datasets` version: 2.4.0 - Platform: macOS-12.5.1-arm64-arm-64bit - Python version: 3.9.13 - PyArrow version: 9.0.0 - Pandas version: 1.4.4

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I_kwDODunzps5R8tJz

Make `pyarrow` optional

closed

NONE

**Is your feature request related to a problem? Please describe.** Is `pyarrow` really needed for every dataset? **Describe the solution you'd like** It is made optional. **Describe alternatives you've considered** Likely, no.

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PR_kwDODunzps4_CouM

Fix missing tags in dataset cards

closed

MEMBER

Fix missing tags in dataset cards: - amazon_us_reviews - art - discofuse - indic_glue - ubuntu_dialogs_corpus This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task. Related to: - #4833 - #4891 - #4896 - #4908 - #4921 - #4931

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PR_kwDODunzps4_Axnh

Update IndicGLUE download links

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I_kwDODunzps5R1b1t

Providing dataset size

open

NONE

**Is your feature request related to a problem? Please describe.** Especially for big datasets like [LAION](https://huggingface.co/datasets/laion/laion2B-en/), it's hard to know exactly the downloaded size (because there are many files and you don't have their exact size when downloaded). **Describe the solution you'd like** Auto-populating the downloaded dataset size on the dataset page would be really useful, including that of each split (when there are some). **Describe alternatives you've considered** People should be adding this to dataset cards, but I don't think that is systematically the case :slightly_smiling_face: **Additional context** Mentioned to @lhoestq

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I_kwDODunzps5Ry_pO

Hope to adapt Python3.9 as soon as possible

open

NONE

**Is your feature request related to a problem? Please describe.** A clear and concise description of what the problem is. **Describe the solution you'd like** A clear and concise description of what you want to happen. **Describe alternatives you've considered** A clear and concise description of any alternative solutions or features you've considered. **Additional context** Add any other context about the feature request here.

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PR_kwDODunzps4-4NXX

Add `fn_kwargs` param to `IterableDataset.map`

closed

COLLABORATOR

Add the `fn_kwargs` parameter to `IterableDataset.map`. ("Resolves" https://discuss.huggingface.co/t/how-to-use-large-image-text-datasets-in-hugging-face-hub-without-downloading-for-free/22780/3)

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PR_kwDODunzps4-4Iri

[GH->HF] Part 2: Remove all dataset scripts from github

closed

MEMBER

Now that all the datasets live on the Hub we can remove the /datasets directory that contains all the dataset scripts of this repository - [x] Needs https://github.com/huggingface/datasets/pull/4973 to be merged first - [x] and PR to be enabled on the Hub for non-namespaced datasets

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PR_kwDODunzps4-33JW

[GH->HF] Load datasets from the Hub

closed

MEMBER

Currently datasets with no namespace (e.g. squad, glue) are loaded from github. In this PR I changed this logic to use the Hugging Face Hub instead. This is the first step in removing all the dataset scripts in this repository related to discussions in https://github.com/huggingface/datasets/pull/4059 (I should have continued from this PR actually)

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PR_kwDODunzps4-3VVF

Fix map batched with torch output

closed

MEMBER

Reported in https://discuss.huggingface.co/t/typeerror-when-applying-map-after-set-format-type-torch/23067/2 Currently it fails if one uses batched `map` and the map function returns a torch tensor. I fixed it for torch, tf, jax and pandas series.

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PR_kwDODunzps4-zk3g

Preserve non-`input_colums` in `Dataset.map` if `input_columns` are specified

closed

COLLABORATOR

Currently, if the `input_columns` list in `Dataset.map` is specified, the columns not in that list are dropped after the `map` transform. This makes the behavior inconsistent with `IterableDataset.map`. (It seems this issue was introduced by mistake in https://github.com/huggingface/datasets/pull/2246) Fix https://github.com/huggingface/datasets/issues/4858

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PR_kwDODunzps4-wkY2

Support streaming nli_tr dataset

closed

MEMBER

Support streaming nli_tr dataset. This PR removes legacy `codecs.open` and replaces it with `open` that supports passing encoding. Fix #3186.

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PR_kwDODunzps4-wPOk

Fix data URL and metadata of vivos dataset

closed

MEMBER

After contacting the authors of the VIVOS dataset to report that their data server is down, we have received a reply from Hieu-Thi Luong that their data is now hosted on Zenodo: https://doi.org/10.5281/zenodo.7068130 This PR updates their data URL and some metadata (homepage, citation and license). Fix #4936.

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PR_kwDODunzps4-wKkw

Support streaming compguesswhat dataset

closed

MEMBER

Support streaming `compguesswhat` dataset. Fix #3191.

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PR_kwDODunzps4-vbS-

Strip "/" in local dataset path to avoid empty dataset name error

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I_kwDODunzps5RlBwK

[Apple M1] MemoryError: Cannot allocate write+execute memory for ffi.callback()

closed

NONE

## Describe the bug I'm trying to run `cast_column("audio", Audio())` on Apple M1 Pro, but it seems that it doesn't work. ## Steps to reproduce the bug ```python import datasets dataset = load_dataset("csv", data_files="./train.csv")["train"] dataset = dataset.map(lambda x: {"audio": str(DATA_DIR / "audio" / x["audio"])}) dataset = dataset.cast_column("audio", Audio()) dataset[0] ``` ## Expected results ``` {'audio': {'bytes': None, 'path': '/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav'}, 'english_transcription': 'I would like to set up a joint account with my partner', 'intent_class': 11, 'lang_id': 4, 'path': '/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav', 'transcription': 'I would like to set up a joint account with my partner'} ``` ## Actual results ````--------------------------------------------------------------------------- MemoryError Traceback (most recent call last) Input In [6], in <cell line: 1>() ----> 1 dataset[0] File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/arrow_dataset.py:2165, in Dataset.__getitem__(self, key) 2163 def __getitem__(self, key): # noqa: F811 2164 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools).""" -> 2165 return self._getitem( 2166 key, 2167 ) File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/arrow_dataset.py:2150, in Dataset._getitem(self, key, decoded, **kwargs) 2148 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs) 2149 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None) -> 2150 formatted_output = format_table( 2151 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns 2152 ) 2153 return formatted_output File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:532, in format_table(table, key, formatter, format_columns, output_all_columns) 530 python_formatter = PythonFormatter(features=None) 531 if format_columns is None: --> 532 return formatter(pa_table, query_type=query_type) 533 elif query_type == "column": 534 if key in format_columns: File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type) 279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]: 280 if query_type == "row": --> 281 return self.format_row(pa_table) 282 elif query_type == "column": 283 return self.format_column(pa_table) File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:312, in PythonFormatter.format_row(self, pa_table) 310 row = self.python_arrow_extractor().extract_row(pa_table) 311 if self.decoded: --> 312 row = self.python_features_decoder.decode_row(row) 313 return row File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:221, in PythonFeaturesDecoder.decode_row(self, row) 220 def decode_row(self, row: dict) -> dict: --> 221 return self.features.decode_example(row) if self.features else row File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1647, in Features.decode_example(self, example, token_per_repo_id) 1634 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None): 1635 """Decode example with custom feature decoding. 1636 1637 Args: (...) 1644 :obj:`dict[str, Any]` 1645 """ -> 1647 return { 1648 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id) 1649 if self._column_requires_decoding[column_name] 1650 else value 1651 for column_name, (feature, value) in zip_dict( 1652 {key: value for key, value in self.items() if key in example}, example 1653 ) 1654 } File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1648, in <dictcomp>(.0) 1634 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None): 1635 """Decode example with custom feature decoding. 1636 1637 Args: (...) 1644 :obj:`dict[str, Any]` 1645 """ 1647 return { -> 1648 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id) 1649 if self._column_requires_decoding[column_name] 1650 else value 1651 for column_name, (feature, value) in zip_dict( 1652 {key: value for key, value in self.items() if key in example}, example 1653 ) 1654 } File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1260, in decode_nested_example(schema, obj, token_per_repo_id) 1257 # Object with special decoding: 1258 elif isinstance(schema, (Audio, Image)): 1259 # we pass the token to read and decode files from private repositories in streaming mode -> 1260 return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None 1261 return obj File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/audio.py:156, in Audio.decode_example(self, value, token_per_repo_id) 154 array, sampling_rate = self._decode_non_mp3_file_like(file) 155 else: --> 156 array, sampling_rate = self._decode_non_mp3_path_like(path, token_per_repo_id=token_per_repo_id) 157 return {"path": path, "array": array, "sampling_rate": sampling_rate} File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/audio.py:257, in Audio._decode_non_mp3_path_like(self, path, format, token_per_repo_id) 254 use_auth_token = None 256 with xopen(path, "rb", use_auth_token=use_auth_token) as f: --> 257 array, sampling_rate = librosa.load(f, sr=self.sampling_rate, mono=self.mono) 258 return array, sampling_rate File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/util/decorators.py:88, in deprecate_positional_args.<locals>._inner_deprecate_positional_args.<locals>.inner_f(*args, **kwargs) 86 extra_args = len(args) - len(all_args) 87 if extra_args <= 0: ---> 88 return f(*args, **kwargs) 90 # extra_args > 0 91 args_msg = [ 92 "{}={}".format(name, arg) 93 for name, arg in zip(kwonly_args[:extra_args], args[-extra_args:]) 94 ] File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/core/audio.py:164, in load(path, sr, mono, offset, duration, dtype, res_type) 161 else: 162 # Otherwise try soundfile first, and then fall back if necessary 163 try: --> 164 y, sr_native = __soundfile_load(path, offset, duration, dtype) 166 except RuntimeError as exc: 167 # If soundfile failed, try audioread instead 168 if isinstance(path, (str, pathlib.PurePath)): File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/core/audio.py:195, in __soundfile_load(path, offset, duration, dtype) 192 context = path 193 else: 194 # Otherwise, create the soundfile object --> 195 context = sf.SoundFile(path) 197 with context as sf_desc: 198 sr_native = sf_desc.samplerate File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:629, in SoundFile.__init__(self, file, mode, samplerate, channels, subtype, endian, format, closefd) 626 self._mode = mode 627 self._info = _create_info_struct(file, mode, samplerate, channels, 628 format, subtype, endian) --> 629 self._file = self._open(file, mode_int, closefd) 630 if set(mode).issuperset('r+') and self.seekable(): 631 # Move write position to 0 (like in Python file objects) 632 self.seek(0) File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:1179, in SoundFile._open(self, file, mode_int, closefd) 1177 file_ptr = _snd.sf_open_fd(file, mode_int, self._info, closefd) 1178 elif _has_virtual_io_attrs(file, mode_int): -> 1179 file_ptr = _snd.sf_open_virtual(self._init_virtual_io(file), 1180 mode_int, self._info, _ffi.NULL) 1181 else: 1182 raise TypeError("Invalid file: {0!r}".format(self.name)) File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:1197, in SoundFile._init_virtual_io(self, file) 1194 def _init_virtual_io(self, file): 1195 """Initialize callback functions for sf_open_virtual().""" 1196 @_ffi.callback("sf_vio_get_filelen") -> 1197 def vio_get_filelen(user_data): 1198 curr = file.tell() 1199 file.seek(0, SEEK_END) MemoryError: Cannot allocate write+execute memory for ffi.callback(). You might be running on a system that prevents this. For more information, see https://cffi.readthedocs.io/en/latest/using.html#callbacks ``` ## Environment info - `datasets` version: 2.4.0 - Platform: macOS-12.5.1-arm64-arm-64bit - Python version: 3.8.13 - PyArrow version: 9.0.0 - Pandas version: 1.4.4

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I_kwDODunzps5Rk3Fq

Column of arrays (2D+) are using unreasonably high memory

open

CONTRIBUTOR

## Describe the bug When trying to store `Array2D, Array3D, etc` as column values in a dataset, accessing that column (or creating depending on how you create it, see code below) will cause more than 10 fold of memory usage. ## Steps to reproduce the bug ```python from datasets import Dataset, Features, Array2D, Array3D import numpy as np column_name = "a" array_shape = (64, 64, 3) data = np.random.random((10000,) + array_shape) dataset = Dataset.from_dict({column_name: data}, features=Features({column_name: Array3D(shape=array_shape, dtype="float64")})) ``` the code above will use about 10Gb of RAM while constructing the `dataset` object. The code below will use roughly the same amount of memory (and time) when trying to actually access the data itself of that column. ```python from datasets import Dataset import numpy as np column_name = "a" array_shape = (64, 64, 3) data = np.random.random((10000,) + array_shape) dataset = Dataset.from_dict({column_name: data}) dataset[column_name] ``` ## Expected results Some memory overhead, but not like as it is now and certainly not an overhead of such runtime that is currently happening. ## Actual results Enormous memory- and runtime overhead. ## Environment info - `datasets` version: 2.3.2 - Platform: macOS-12.5.1-arm64-arm-64bit - Python version: 3.8.13 - PyArrow version: 9.0.0 - Pandas version: 1.4.4

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I_kwDODunzps5RjRfk

Dataset without script does not support regular JSON data file

closed

MEMBER

### Link https://huggingface.co/datasets/julien-c/label-studio-my-dogs ### Description <img width="1115" alt="image" src="https://user-images.githubusercontent.com/326577/189422048-7e9c390f-bea7-4521-a232-43f049ccbd1f.png"> ### Owner Yes

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PR_kwDODunzps4-sh-o

Update setup.py

closed

NONE

exclude broken version of fsspec. See the [related issue](https://github.com/huggingface/datasets/issues/4961)

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I_kwDODunzps5Ri-qB

fsspec 2022.8.2 breaks xopen in streaming mode

closed

NONE

## Describe the bug When fsspec 2022.8.2 is installed in your environment, xopen will prematurely close files, making streaming mode inoperable. ## Steps to reproduce the bug ```python import datasets data = datasets.load_dataset('MLCommons/ml_spoken_words', 'id_wav', split='train', streaming=True) ``` ## Expected results Dataset should load as iterator. ## Actual results ``` [/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs) 1737 # Return iterable dataset in case of streaming 1738 if streaming: -> 1739 return builder_instance.as_streaming_dataset(split=split) 1740 1741 # Some datasets are already processed on the HF google storage [/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in as_streaming_dataset(self, split, base_path) 1023 ) 1024 self._check_manual_download(dl_manager) -> 1025 splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)} 1026 # By default, return all splits 1027 if split is None: [~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in _split_generators(self, dl_manager) 182 name=datasets.Split.TRAIN, 183 gen_kwargs={ --> 184 "audio_archives": [download_audio(split="train", lang=lang) for lang in self.config.languages], 185 "local_audio_archives_paths": [download_extract_audio(split="train", lang=lang) for lang in 186 self.config.languages] if not dl_manager.is_streaming else None, [~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in <listcomp>(.0) 182 name=datasets.Split.TRAIN, 183 gen_kwargs={ --> 184 "audio_archives": [download_audio(split="train", lang=lang) for lang in self.config.languages], 185 "local_audio_archives_paths": [download_extract_audio(split="train", lang=lang) for lang in 186 self.config.languages] if not dl_manager.is_streaming else None, [~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in _download_audio_archives(dl_manager, lang, format, split) 267 # for streaming case 268 def _download_audio_archives(dl_manager, lang, format, split): --> 269 archives_paths = _download_audio_archives_paths(dl_manager, lang, format, split) 270 return [dl_manager.iter_archive(archive_path) for archive_path in archives_paths] [~/.cache/huggingface/modules/datasets_modules/datasets/MLCommons--ml_spoken_words/321ea853cf0a05abb7a2d7efea900692a3d8622af65a2f3ce98adb7800a5d57b/ml_spoken_words.py](https://localhost:8080/#) in _download_audio_archives_paths(dl_manager, lang, format, split) 251 n_files_path = dl_manager.download(n_files_url) 252 --> 253 with open(n_files_path, "r", encoding="utf-8") as file: 254 n_files = int(file.read().strip()) # the file contains a number of archives 255 ValueError: I/O operation on closed file. ``` ## Environment info - `datasets` version: 2.4.0 - Platform: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic - Python version: 3.7.13 - PyArrow version: 6.0.1 - Pandas version: 1.3.5

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I_kwDODunzps5Rio9X

BioASQ AttributeError: 'BuilderConfig' object has no attribute 'schema'

open

NONE

## Describe the bug I am trying to load a dataset from drive and running into an error. ## Steps to reproduce the bug ```python data_dir = "/Users/dlituiev/repos/datasets/bioasq/BioASQ-training9b" bioasq_task_b = load_dataset("aps/bioasq_task_b", data_dir=data_dir) ``` ## Actual results `AttributeError: 'BuilderConfig' object has no attribute 'schema'` <details> ``` Using custom data configuration default-a1ca3e05be5abf2f --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Input In [8], in <cell line: 2>() 1 data_dir = "/Users/dlituiev/repos/datasets/bioasq/BioASQ-training9b" ----> 2 bioasq_task_b = load_dataset("aps/bioasq_task_b", data_dir=data_dir) File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/load.py:1723, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs) 1720 ignore_verifications = ignore_verifications or save_infos 1722 # Create a dataset builder -> 1723 builder_instance = load_dataset_builder( 1724 path=path, 1725 name=name, 1726 data_dir=data_dir, 1727 data_files=data_files, 1728 cache_dir=cache_dir, 1729 features=features, 1730 download_config=download_config, 1731 download_mode=download_mode, 1732 revision=revision, 1733 use_auth_token=use_auth_token, 1734 **config_kwargs, 1735 ) 1737 # Return iterable dataset in case of streaming 1738 if streaming: File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/load.py:1526, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs) 1523 raise ValueError(error_msg) 1525 # Instantiate the dataset builder -> 1526 builder_instance: DatasetBuilder = builder_cls( 1527 cache_dir=cache_dir, 1528 config_name=config_name, 1529 data_dir=data_dir, 1530 data_files=data_files, 1531 hash=hash, 1532 features=features, 1533 use_auth_token=use_auth_token, 1534 **builder_kwargs, 1535 **config_kwargs, 1536 ) 1538 return builder_instance File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/builder.py:1154, in GeneratorBasedBuilder.__init__(self, writer_batch_size, *args, **kwargs) 1153 def __init__(self, *args, writer_batch_size=None, **kwargs): -> 1154 super().__init__(*args, **kwargs) 1155 # Batch size used by the ArrowWriter 1156 # It defines the number of samples that are kept in memory before writing them 1157 # and also the length of the arrow chunks 1158 # None means that the ArrowWriter will use its default value 1159 self._writer_batch_size = writer_batch_size or self.DEFAULT_WRITER_BATCH_SIZE File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/builder.py:307, in DatasetBuilder.__init__(self, cache_dir, config_name, hash, base_path, info, features, use_auth_token, repo_id, data_files, data_dir, name, **config_kwargs) 305 if info is None: 306 info = self.get_exported_dataset_info() --> 307 info.update(self._info()) 308 info.builder_name = self.name 309 info.config_name = self.config.name File ~/.cache/huggingface/modules/datasets_modules/datasets/aps--bioasq_task_b/3d54b1213f7e8001eef755af92877f9efa44161ee83c2a70d5d649defa95759e/bioasq_task_b.py:477, in BioasqTaskBDataset._info(self) 474 def _info(self): 475 476 # BioASQ Task B source schema --> 477 if self.config.schema == "source": 478 features = datasets.Features( 479 { 480 "id": datasets.Value("string"), (...) 504 } 505 ) 506 # simplified schema for QA tasks AttributeError: 'BuilderConfig' object has no attribute 'schema' ``` </details> ## Environment info - `datasets` version: 2.4.0 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.10.4 - PyArrow version: 9.0.0 - Pandas version: 1.4.3

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PR_kwDODunzps4-rx6l

Fix data URLs of compguesswhat dataset

closed

MEMBER

After we informed the `compguesswhat` dataset authors about an error with their data URLs, they have updated them: - https://github.com/CompGuessWhat/compguesswhat.github.io/issues/1 This PR updates their data URLs in our loading script. Related to: - #3191