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Add default Audio Loader
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2022-03-18T12:58:55Z
2022-08-22T14:20:46Z
2022-08-22T14:20:46Z
CONTRIBUTOR
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**Is your feature request related to a problem? Please describe.** Writing a custom loading dataset script might be a bit challenging for users. **Describe the solution you'd like** Add default Audio loader (analogous to ImageFolder) for small datasets with standard directory structure. **Describe alternatives you've considered** Create a custom loading script? that's what users doing now.
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Add Audio Folder
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2022-03-18T11:40:09Z
2022-06-15T16:33:19Z
2022-06-15T16:33:19Z
CONTRIBUTOR
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Would resolve #3964 AudioFolder loads a .txt file with transcriptions and creates a dataset with all audiofiles in provided directory that has a transcription (independently of the directory structure) as a single split (train). Can be loaded via: ```python # for local dirs dataset = load_dataset("audiofolder", data_dir="/path/to/folder", transcripts_filename="transcripts.txt") ``` ```python # for local and remote zip archives dataset = load_dataset("audiofolder", data_files="path/to/archive/archive.zip", transcripts_filename="transcripts.txt") ``` default transcriptions filename is `transcripts.txt`. it should have the following structure: ``` audio_id_1 transcription text 1 audio_id_1 transcription text 1 ``` separator is `\t`! --- sorry for first old commits from other branch, don't know how that happened...
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Fix flatten of Sequence feature type
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2022-03-18T11:27:42Z
2022-03-21T14:40:47Z
2022-03-21T14:36:12Z
MEMBER
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The `Sequence` features type is not correctly flattened if it contains a dictionary. This PR fixes this, and I added a test case for this. Close https://github.com/huggingface/datasets/issues/3795
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3,961
Scores from Index at extra positions are not filtered out
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2022-03-18T06:13:23Z
2022-04-12T14:41:58Z
2022-04-12T14:41:58Z
CONTRIBUTOR
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If a FAISS index has fewer records than the requested number of top results (k), then it returns -1 in indices for the additional positions. The get_nearest_examples method only filters out the extra results from the dataset samples. It would be better to filter out extra scores too. Reference: https://github.com/huggingface/datasets/blob/2.0.0/src/datasets/search.py#L693
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Load local dataset error
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2022-03-18T03:32:49Z
2023-08-02T17:12:20Z
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When i used the datasets==1.11.0, it's all right. Util update the latest version, it get the error like this: ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train'], 'validation': ['/ssd/datasets/imagenet/pytorch/val']} >>> ds = load_dataset('nateraw/image-folder', data_files=data_files, cache_dir='./', task='image-classification') [] https://huggingface.co/datasets/nateraw/image-folder/resolve/main/ /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1671, in load_dataset **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1521, in load_dataset_builder **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 1031, in __init__ super().__init__(*args, **kwargs) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 255, in __init__ sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 584, in from_local_or_remote if not isinstance(patterns_for_key, DataFilesList) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 546, in from_local_or_remote data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 196, in resolve_patterns_locally_or_by_urls for path in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions): File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 146, in _resolve_single_pattern_locally raise FileNotFoundError(error_msg) FileNotFoundError: Unable to find '/ssd/datasets/imagenet/pytorch/train' at /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main ``` I need some help to solve the problem, thanks!
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https://api.github.com/repos/huggingface/datasets/issues/3959
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https://github.com/huggingface/datasets/issues/3959
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Medium-sized dataset conversion from pandas causes a crash
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2022-12-12T17:14:06Z
2022-04-20T12:35:37Z
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Hi, I am suffering from the following issue: ## Describe the bug Conversion to arrow dataset from pandas dataframe of a certain size deterministically causes the following crash: ``` File "/home/datasets_crash.py", line 7, in <module> arrow=datasets.Dataset.from_pandas(d) File "/home/.conda/envs/tools/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 783, in from_pandas table = InMemoryTable.from_pandas( File "/home/.conda/envs/tools/lib/python3.9/site-packages/datasets/table.py", line 379, in from_pandas return cls(pa.Table.from_pandas(*args, **kwargs)) File "pyarrow/table.pxi", line 1487, in pyarrow.lib.Table.from_pandas File "pyarrow/table.pxi", line 1532, in pyarrow.lib.Table.from_arrays File "pyarrow/table.pxi", line 1181, in pyarrow.lib.Table.validate File "pyarrow/error.pxi", line 84, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: Column 1: In chunk 0: Invalid: List child array invalid: Invalid: Struct child array #1 has length smaller than expected for struct array (1192457 < 1192458) ``` ## Steps to reproduce the bug I have a dataset made from replicated single example mocking a dict representation of a publication. I copy over this example 140k times and create a pandas frame. I use 'Dataset.from_pandas' and boom ```python # Sample code to reproduce the bug import copy import datasets import pandas # serialized dict is quite long to be realistic representation of a publication content paper_as_dict=eval("{'article_id': '2020-11-05T14:25:05.321Z02bc3286-91b7-486a-9c74-4f457fbc586a', 'sections': [{'section_id': 'body.0', 'paragraphs': [{'sentences': ['11010111001000000011010011110011101110111011000100001010011100101001111010110111101011101111101010101110001111011110111010111', '1101100110110010010101010100110011000111001100100000011100010111010000011100001101111000000011010111001111001010101111110011010010111011000110100110010', '101011011000010100000010011001011011000000110011011110000101001110110000010001100110111100011100110101010010110000101', '1101101110101010101000000010101011111001111000101000110001110100111000100000011001110100110000110100111011001010110011101001001110']}]}, {'section_id': 'body.1', 'paragraphs': [{'sentences': 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'0110110100011001110011001111100010101001011111011001011001101101010010101101110101010100001000100100000111101110001001110111000110011101101010100000101', '0011111010010011011101010110100110000011000011100100101011011001110110001110001111000011010111011000110100111111011101110111000010010000011011010011011100000011101100110110100100000010110101110100110101001100111011101001010111011011110100110101110010011011010001010111110011001000010100010101010010110010010110000100110001000011010011000100101011010100100111010']}]}]}") d=pandas.DataFrame.from_records(copy.deepcopy(paper_as_dict) for _ in range(140_100)) arrow=datasets.Dataset.from_pandas(d) ``` ## Expected results The dataset should be converted without error. ## Actual results Error `pyarrow.lib.ArrowInvalid: Column 1: In chunk 0: Invalid: List child array invalid: Invalid: Struct child array #1 has length smaller than expected for struct array (1192457 < 1192458)` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: datasets==1.18.4 pandas==1.3.5 - Platform: macOS 11.6 or CentOS Linux 7 (Core) - Python version: Python 3.9.7 - PyArrow version: pyarrow==3.0.0
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Update Wikipedia metadata
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2022-03-17T17:50:05Z
2022-03-21T12:26:48Z
2022-03-21T12:26:47Z
MEMBER
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This PR updates: - dataset card - metadata JSON
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Fix xtreme s metrics
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2022-03-17T13:39:04Z
2022-03-18T13:46:19Z
2022-03-18T13:42:16Z
CONTRIBUTOR
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We in fact do need BABEL in xtreme-s
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## Describe the bug Based on [this tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) the provided code should add Elasticsearch index but raised the following error, probably the new Elasticsearch version is not compatible though the tutorial doesn't provide any information about the supporting Elasticsearch version. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import load_dataset squad = load_dataset('squad', split='validation') squad.add_elasticsearch_index("context", host="localhost", port="9200") ``` ## Expected results [Creating an elastic index based on the provided tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) ## Actual results ``` --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-8fb51aa33961> in <module> 1 from datasets import load_dataset 2 squad = load_dataset('squad', split='validation') ----> 3 squad.add_elasticsearch_index("context", host="localhost", port="9200") ~/opt/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 3777 """ 3778 with self.formatted_as(type=None, columns=[column]): -> 3779 super().add_elasticsearch_index( 3780 column=column, 3781 index_name=index_name, ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 587 """ 588 index_name = index_name if index_name is not None else column --> 589 es_index = ElasticSearchIndex( 590 host=host, port=port, es_client=es_client, es_index_name=es_index_name, es_index_config=es_index_config 591 ) ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in __init__(self, host, port, es_client, es_index_name, es_index_config) 123 from elasticsearch import Elasticsearch # noqa: F811 124 --> 125 self.es_client = es_client if es_client is not None else Elasticsearch([{"host": host, "port": str(port)}]) 126 self.es_index_name = ( 127 es_index_name ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/__init__.py in __init__(self, hosts, cloud_id, api_key, basic_auth, bearer_auth, opaque_id, headers, connections_per_node, http_compress, verify_certs, ca_certs, client_cert, client_key, ssl_assert_hostname, ssl_assert_fingerprint, ssl_version, ssl_context, ssl_show_warn, transport_class, request_timeout, node_class, node_pool_class, randomize_nodes_in_pool, node_selector_class, dead_node_backoff_factor, max_dead_node_backoff, serializer, serializers, default_mimetype, max_retries, retry_on_status, retry_on_timeout, sniff_on_start, sniff_before_requests, sniff_on_node_failure, sniff_timeout, min_delay_between_sniffing, sniffed_node_callback, meta_header, timeout, randomize_hosts, host_info_callback, sniffer_timeout, sniff_on_connection_fail, http_auth, maxsize, _transport) 310 311 if _transport is None: --> 312 node_configs = client_node_configs( 313 hosts, 314 cloud_id=cloud_id, ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in client_node_configs(hosts, cloud_id, **kwargs) 99 else: 100 assert hosts is not None --> 101 node_configs = hosts_to_node_configs(hosts) 102 103 # Remove all values which are 'DEFAULT' to avoid overwriting actual defaults. ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in hosts_to_node_configs(hosts) 142 143 elif isinstance(host, Mapping): --> 144 node_configs.append(host_mapping_to_node_config(host)) 145 else: 146 raise ValueError( ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in host_mapping_to_node_config(host) 209 options["path_prefix"] = options.pop("url_prefix") 210 --> 211 return NodeConfig(**options) # type: ignore 212 213 TypeError: __init__() missing 1 required positional argument: 'scheme' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: Mac - Python version: 3.8.0 - PyArrow version: 7.0.0 - ElaticSearch Info: { "name" : "byname", "cluster_name" : "elasticsearch_brew", "cluster_uuid" : "9xkjrltiQIG0J95ciWhqRA", "version" : { "number" : "7.10.2-SNAPSHOT", "build_flavor" : "oss", "build_type" : "tar", "build_hash" : "unknown", "build_date" : "2021-01-16T01:41:27.115673Z", "build_snapshot" : true, "lucene_version" : "8.7.0", "minimum_wire_compatibility_version" : "6.8.0", "minimum_index_compatibility_version" : "6.0.0-beta1" }, "tagline" : "You Know, for Search" }
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Remove unncessary 'pylint disable' message in ReadMe
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2022-04-12T14:28:35Z
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The dataset preview is not available for tdklab/Hebrew_Squad_v1.1 dataset
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2022-04-20T12:39:07Z
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## Dataset viewer issue for 'tdklab/Hebrew_Squad_v1.1' **Link:** https://huggingface.co/api/datasets/tdklab/Hebrew_Squad_v1.1?full=true The dataset preview is not available for this dataset. Am I the one who added this dataset ? Yes
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Add ImageNet Sketch
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2022-05-23T18:05:29Z
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## Adding a Dataset - **Name:** ImageNet Sketch - **Description:** ImageNet-Sketch is a dataset consisting of sketch-like images, that matches the ImageNet classification validation set in categories and scale. - **Paper:** [Learning Robust Global Representations by Penalizing Local Predictive Power](https://arxiv.org/abs/1905.13549) - **Data:** https://github.com/HaohanWang/ImageNet-Sketch - **Motivation:** Allows for evaluating the robustness of vision models. 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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Checksum error for glue sst2, stsb, rte etc datasets
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2022-03-17T07:10:15Z
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## Describe the bug Checksum error for glue sst2, stsb, rte etc datasets ## Steps to reproduce the bug ```python >>> nlp.load_dataset('glue', 'sst2') Downloading and preparing dataset glue/sst2 (download: 7.09 MiB, generated: 4.81 MiB, post-processed: Unknown sizetotal: 11.90 MiB) to Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 73.0/73.0 [00:00<00:00, 18.2kB/s] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Library/Python/3.8/lib/python/site-packages/nlp/load.py", line 548, in load_dataset builder_instance.download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 462, in download_and_prepare self._download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 521, in _download_and_prepare verify_checksums( File "/Library/Python/3.8/lib/python/site-packages/nlp/utils/info_utils.py", line 38, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) nlp.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8'] ``` ## Expected results dataset load should succeed without checksum error. ## Actual results ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Library/Python/3.8/lib/python/site-packages/nlp/load.py", line 548, in load_dataset builder_instance.download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 462, in download_and_prepare self._download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 521, in _download_and_prepare verify_checksums( File "/Library/Python/3.8/lib/python/site-packages/nlp/utils/info_utils.py", line 38, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) nlp.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8'] ``` ## Environment info - `datasets` version: '1.18.3' - Platform: Mac OS - Python version: Python 3.8.9 - PyArrow version: '7.0.0'
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Forked streaming datasets try to `open` data urls rather than use network
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## Describe the bug Building on #3950, if you bypass the pickling problem you still can't use the dataset. Somehow something gets confused and the forked processes try to `open` urls rather than anything else. ## Steps to reproduce the bug ```python from multiprocessing import freeze_support import transformers from transformers import Trainer, AutoModelForCausalLM, TrainingArguments import datasets import torch.utils.data # work around #3950 class TorchIterableDataset(datasets.IterableDataset, torch.utils.data.IterableDataset): pass def _ensure_format(v: datasets.IterableDataset) -> datasets.IterableDataset: return TorchIterableDataset(v._ex_iterable, v.info, v.split, "torch", v._shuffling) if __name__ == '__main__': freeze_support() ds = datasets.load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True) ds = _ensure_format(ds) model = AutoModelForCausalLM.from_pretrained("distilgpt2") Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() ``` ## Expected results I'd expect the dataset to load the url correctly and produce examples. ## Actual results ``` warnings.warn( ***** Running training ***** Num examples = 8000 Num Epochs = 9223372036854775807 Instantaneous batch size per device = 8 Total train batch size (w. parallel, distributed & accumulation) = 8 Gradient Accumulation steps = 1 Total optimization steps = 1000 0%| | 0/1000 [00:00<?, ?it/s]Traceback (most recent call last): File "/Users/dlwh/src/mistral/src/stream_fork_crash.py", line 22, in <module> Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/transformers/trainer.py", line 1339, in train for step, inputs in enumerate(epoch_iterator): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 521, in __next__ data = self._next_data() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1203, in _next_data return self._process_data(data) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1229, in _process_data data.reraise() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/_utils.py", line 434, in reraise raise exception FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0. Original Traceback (most recent call last): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 32, in fetch data.append(next(self.dataset_iter)) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 497, in __iter__ for key, example in self._iter(): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 494, in _iter yield from ex_iterable File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 87, in __iter__ yield from self.generate_examples_fn(**self.kwargs) File "/Users/dlwh/.cache/huggingface/modules/datasets_modules/datasets/oscar/84838bd49d2295f62008383b05620571535451d84545037bb94d6f3501651df2/oscar.py", line 358, in _generate_examples with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f: FileNotFoundError: [Errno 2] No such file or directory: 'https://s3.amazonaws.com/datasets.huggingface.co/oscar/1.0/unshuffled/deduplicated/en/en_part_1.txt.gz' Error in atexit._run_exitfuncs: Traceback (most recent call last): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_fork.py", line 27, in poll pid, sts = os.waitpid(self.pid, flag) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/_utils/signal_handling.py", line 66, in handler _error_if_any_worker_fails() RuntimeError: DataLoader worker (pid 6932) is killed by signal: Terminated: 15. 0%| | 0/1000 [00:02<?, ?it/s] ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: macOS-12.2-arm64-arm-64bit - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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Streaming Datasets don't work with Transformers Trainer when dataloader_num_workers>1
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## Describe the bug Streaming Datasets can't be pickled, so any interaction between them and multiprocessing results in a crash. ## Steps to reproduce the bug ```python import transformers from transformers import Trainer, AutoModelForCausalLM, TrainingArguments import datasets ds = datasets.load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True).with_format("torch") model = AutoModelForCausalLM.from_pretrained("distilgpt2") Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() ``` ## Expected results For this code I'd expect a crash related to not having preprocessed the data, but instead we get a pickling error. ## Actual results ``` 0%| | 0/1000 [00:00<?, ?it/s]Traceback (most recent call last): File "/Users/dlwh/src/mistral/src/stream_fork_crash.py", line 7, in <module> Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/transformers/trainer.py", line 1339, in train for step, inputs in enumerate(epoch_iterator): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 359, in __iter__ return self._get_iterator() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 305, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 918, in __init__ w.start() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/process.py", line 121, in start self._popen = self._Popen(self) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/context.py", line 284, in _Popen return Popen(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_spawn_posix.py", line 32, in __init__ super().__init__(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_fork.py", line 19, in __init__ self._launch(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_spawn_posix.py", line 47, in _launch reduction.dump(process_obj, fp) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/reduction.py", line 60, in dump ForkingPickler(file, protocol).dump(obj) AttributeError: Can't pickle local object 'iterable_dataset.<locals>.TorchIterableDataset' 0%| | 0/1000 [00:00<?, ?it/s] ``` This immediate crash can be fixed by not using a local class to make the `TorchIterableDataset` (Note that you have to do with_format("torch") or you get an exception because the dataset has no len) However, any lambdas etc used as maps will also trigger this crash. A more permanent fix would be to move away from multiprocessing and instead use something like pathos or multiprocessing_on_dill (https://stackoverflow.com/questions/19984152/what-can-multiprocessing-and-dill-do-together) Note that if you bypass this crash you get another crash. (I'll file a separate bug). ## Environment info - `datasets` version: 2.0.0 - Platform: macOS-12.2-arm64-arm-64bit - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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Remove GLEU metric
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2022-03-16T19:35:31Z
2022-04-12T20:43:26Z
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CONTRIBUTOR
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Remove the GLEU metric as it is not actually implemented.
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Google BLEU Metric Card
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2022-03-16T19:27:17Z
2022-03-21T16:04:26Z
2022-03-21T16:04:25Z
CONTRIBUTOR
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Add metric card for Google BLEU (GLEU) metric One thing I noticed while writing this up is that, while this metric was made specifically to be better than BLEU at the sentence level instead of the corpus level, the current implementation only allows the calculation of the corpus-level statistic. I think changing this would be a good thing to put on the to do list for the future.
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BLEU metric card
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2022-03-16T19:20:07Z
2022-03-29T14:59:50Z
2022-03-29T14:54:14Z
CONTRIBUTOR
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Add BLEU metric card
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3,946
Add newline to text dataset builder for controlling universal newlines mode
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2022-03-16T16:11:11Z
2023-09-24T10:10:50Z
2023-09-24T10:10:47Z
MEMBER
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Fix #3804.
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PR_kwDODunzps40ixmc
3,945
Fix comet metric
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2022-03-16T15:56:47Z
2022-03-22T15:10:12Z
2022-03-22T15:05:30Z
MEMBER
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The COMET metric has been broken for a while since big breaking changes happened. We did not catch them in the CI because the slow test mocks the download_model function that was changed. This PR fixes the metric, updates the download_model mock and updates the doctest.
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3,944
Create README.md
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2022-03-16T15:46:26Z
2022-03-17T17:50:54Z
2022-03-17T17:47:05Z
CONTRIBUTOR
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null
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Proposing COMET metric card
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3,943
[Doc] Don't use v for version tags on GitHub
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2022-03-16T15:28:30Z
2022-03-17T11:46:26Z
2022-03-17T11:46:25Z
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This removes the `v` automatically used by `doc-builder` for versions.
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reddit_tifu dataset: Checksums didn't match for dataset source files
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2022-03-16T15:57:43Z
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## Describe the bug When loading the reddit_tifu dataset, it throws the exception "Checksums didn't match for dataset source files" ## Steps to reproduce the bug ```python import datasets from datasets import load_dataset print(datasets.__version__) # load_dataset('billsum') load_dataset('reddit_tifu', 'short') ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: mac os - Python version: Python 3.7.6 - PyArrow version: 3.0.0
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billsum dataset: Checksums didn't match for dataset source files:
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## Describe the bug When loading the `billsum` dataset, it throws the exception "Checksums didn't match for dataset source files" ``` File "virtualenv_projects/codex/lib/python3.7/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://drive.google.com/uc?export=download&id=1g89WgFHMRbr4QrvA0ngh26PY081Nv3lx'] ``` ## Steps to reproduce the bug ```python import datasets from datasets import load_dataset print(datasets.__version__) load_dataset('billsum') ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: mac os - Python version: Python 3.7.6 - PyArrow version: 3.0.0
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Initial CoVAL metric card
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2022-03-19T04:41:32Z
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## Describe the bug The source links of v2.0.0 docs are broken: For exmaple, clicking the source button of this [class](https://huggingface.co/docs/datasets/v2.0.0/en/package_reference/main_classes#datasets.ClassLabel) will direct users to `https://github.com/huggingface/datasets/blob/v2.0.0/src/datasets/features/features.py#L747` here, the `v2.0.0` should be `2.0.0`. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug ``` ## Expected results Redirecting to this link: `https://github.com/huggingface/datasets/blob/2.0.0/src/datasets/features/features.py#L747` ## Actual results Described above. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: - Platform: - Python version: - PyArrow version:
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Avoid info log messages from transformers in FrugalScore metric
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Fix #3928.
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Missing languages in lvwerra/github-code dataset
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2022-03-22T07:09:23Z
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Hi, I'm working with the github-code dataset. First of all, thank you for creating this amazing dataset! I've noticed that two languages are missing from the dataset: TypeScript and Scala. Looks like they're also omitted from the query you used to get the original code. Are there any plans to add them in the future? Thanks!
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To keep backward compatibility when loading using "wikipedia" dataset ID (https://huggingface.co/datasets/wikipedia), we have created the pre-processed data for the same languages we were offering before, but with updated date "20220301": - de - en - fr - frr - it - simple These pre-processed data can be accessed, e.g.: ```python ds = load_dataset("wikipedia", "20220301.frr", split="train") ``` The next step will be to offer the pre-processed data for many other languages, but when loading using "wikimedia/wikipedia": https://huggingface.co/datasets/wikimedia/wikipedia
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Create MAUVE metric card
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2022-03-18T17:38:14Z
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CONTRIBUTOR
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Proposing a MAUVE metric card
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Update README.md
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2022-03-15T20:52:05Z
2022-03-17T17:51:24Z
2022-03-17T17:47:37Z
CONTRIBUTOR
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Fixing missing triple quote
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Create SARI metric card
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2022-03-15T20:37:23Z
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CONTRIBUTOR
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SARI metric card! (do we have an expert in text simplification to validate?.. :sweat_smile: )
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Add align_labels_with_mapping docs
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2022-03-15T19:24:57Z
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MEMBER
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This PR documents the `align_labels_with_mapping` function to ensure predicted labels are aligned with the dataset, or to assign a different mapping of labels to ids (requested by @mariosasko 🎉 ). For this specific code sample, the current dataset has a `mixed` label that the original [dataset](https://huggingface.co/datasets/poem_sentiment#data-fields) didn't. Is there a way to remove this label so it is completely aligned with the original dataset mappings? Otherwise, I'll just leave it as it is.
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Create README.md
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2022-03-15T19:16:59Z
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CONTRIBUTOR
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Creating a README for IndicGLUE cc @mcmillanmajora for fact checking in terms of languages (also, are there any limitations of the dataset or eval metric that I'm not aware of?)
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Load a local dataset twice
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2022-03-15T18:59:26Z
2022-03-16T09:55:09Z
2022-03-16T09:54:06Z
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## Describe the bug Load a local "dataset" composed of two csv files twice. ## Steps to reproduce the bug Put the two joined files in a repository named "Data". Then in python: import datasets as ds ds.load_dataset('Data', data_files = {'file1.csv', 'file2.csv'}) ## Expected results Should give something like (because files have only one data row): Title, clicks Truc et astuce, 123 Machin, 12 ## Actual results Gives Title, clicks Truc et astuce, 123 Machin, 12 Truc et astuce, 123 Machin, 12 ## Environment info [file1.csv](https://github.com/huggingface/datasets/files/8256322/file1.csv) [file2.csv](https://github.com/huggingface/datasets/files/8256323/file2.csv) - `datasets` version: 2.0.0 - Platform: Linux-5.4.0-65-generic-x86_64-with-glibc2.10 - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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Frugal score deprecations
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2022-03-15T18:10:42Z
2022-03-17T08:37:24Z
2022-03-17T08:37:24Z
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## Describe the bug The frugal score returns a really verbose output with warnings that can be easily changed. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets.load import load_metric frugal = load_metric("frugalscore") frugal.compute(predictions=["Do you like spinachis"], references=["Do you like spinach"]) ``` ## Expected results A clear and concise description of the expected results. ``` {'scores': [0.9946]} ``` ## Actual results Specify the actual results or traceback. ``` PyTorch: setting up devices The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-). 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 864.09ba/s] Using amp half precision backend The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: sentence2, sentence1. If sentence2, sentence1 are not expected by `BertForSequenceClassification.forward`, you can safely ignore this message. ***** Running Prediction ***** Num examples = 1 Batch size = 64 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 4644.85it/s] {'scores': [0.9946]} ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.29 - Python version: 3.8.10 - PyArrow version: 7.0.0
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Update main readme
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2022-03-15T18:09:59Z
2022-03-29T10:13:47Z
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The main readme was still focused on text datasets - I extended it by mentioning that we also support image and audio datasets
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2022-03-15T17:00:46Z
2022-03-15T19:27:15Z
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This PR adds some minor maintenance to the docs. The main fix is properly linking to pages in the callouts because some of the links would just redirect to a non-existent section on the same page.
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Fix main_classes docs index
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2022-03-15T16:33:46Z
2022-03-22T13:49:11Z
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Currently the `main_classes` documentation has a wrong index. I believe this comes from issues in the examples of the Translation feature types ![image](https://user-images.githubusercontent.com/42851186/158426345-2ee1ceef-ddf3-4a6f-a93e-d1a8f38a44f5.png)
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Document cases for github datasets
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2022-03-15T15:10:10Z
2022-04-05T18:33:15Z
2022-03-15T15:41:23Z
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In general we recommend adding the new dataset under a username or organization in the Hugging Face Hub at [hf.co/datasets](hf.co/datasets), but users can still add a dataset on github in some cases. I added a paragraph in the documentation to explain in which cases it can make more sense to open a PR on github: - when you need the dataset to be reviewed - when you need long-term maintenance from the HF team - when there’s no clear org name / namespace that you can put the dataset under
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Add methods to IterableDatasetDict
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2022-03-15T14:46:03Z
2022-07-06T15:40:20Z
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Following the new methods added in #3826 and https://github.com/huggingface/datasets/pull/3862 I added several methods to IterableDatasetDict: - map - filter - shuffle - with_format - cast - cast_column - remove_columns - rename_column - rename_columns
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Fix NonMatchingChecksumError in MultiWOZ 2.2 dataset
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2022-03-15T14:36:28Z
2022-03-15T16:07:04Z
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Fix #2957
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Fix NonMatchingChecksumError in CRD3 dataset
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2022-03-15T14:27:14Z
2022-03-15T15:54:27Z
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Fix #3051
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'datasets.features' is not a package
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@albertvillanova python 3.9 os: ubuntu 20.04 In conda environment torch installed by ```/env/bin/pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html``` datasets package is installed by ``` /env/bin/pip install datasets==1.8.0 ``` During runing the code I have this error ``` [6]<stderr>: File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class [6]<stderr>: return super().find_class(mod_name, name) [6]<stderr>:ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package ``` precisely this error appears when torch.load('data_file.pt') ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 607, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 882, in _load result = unpickler.load() File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class return super().find_class(mod_name, name) ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package ``` Why I am getting this error?
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AttributeError: 'DatasetDict' object has no attribute 'features'
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2022-03-17T04:16:14Z
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## Describe the bug Receiving the error when trying to check for Dataset features ## Steps to reproduce the bug from datasets import Dataset dataset = Dataset.from_pandas(df[['id', 'words', 'bboxes', 'ner_tags', 'image_path']]) dataset.features ## Expected results A clear and concise description of the expected results. ## Actual results Getting the following errror AttributeError: 'DatasetDict' object has no attribute 'features' ## Environment info Copy-and-paste the text below in your GitHub issue. - `datasets` version: 1.18.4 - Platform: Linux-4.14.252-131.483.amzn1.x86_64-x86_64-with-glibc2.9 - Python version: 3.6.13 - PyArrow version: 6.0.1
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datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files
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## Describe the bug Can't load the dataset ## Steps to reproduce the bug ```python # Sample code to reproduce the bug ``` from datasets import load_dataset dataset = load_dataset('multi_news') dataset_2=load_dataset("reddit_tifu", "long") ## Actual results raise NonMatchingChecksumError(error_msg + str(bad_urls)) datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF'] ## Environment info - `datasets` version: 1.18.4 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.8.0 - PyArrow version: 6.0.1
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2022-03-17T17:45:39Z
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This follows the same structure as the GLUE metric card, hope that works for everyone :)
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CONTRIBUTOR
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I still have a hesitation regarding the format of inputs -- whether it's a list or a list of lists? -- hopefully @lhoestq will be able to clarify. Also tagging @yjernite for the Limitations section. Happy to hear your thoughts!
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CONTRIBUTOR
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Adding a metric card template, based on ideas and edits from @sashavor and I, as well as from comments from @lhoestq and others (thank you!). All feedback is welcome, but am especially curious about feedback in terms of: - things that should be included but aren't - things that are included but should be changed or removed - the instructions I included, and whether they should be added to, clarified, or deleted altogether
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This PR updates the jobs for all doc-building related things by using the templates introduced on `doc-builder`. By putting those once there, we make sure every repo gets the latest fixes on the doc-building github actions :-) Note: all libraries must share the same docker image for those doc-building jobs. For now, all the one used (`huggingface/transformers-doc-builder`) contains all extra steps of the datasets install for docbuling (mainly libsndfile) but if in the future some additional steps are necessary on top of `pip install -e .[dev]`, this docker image will need to be updated with the extra deps.
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3,913
Deterministic split order in DatasetDict.map
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2022-03-14T17:58:37Z
2023-09-24T09:55:10Z
2022-03-15T10:45:15Z
MEMBER
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The order in which the splits are processed by `map` is not deterministic in `DatasetDict.map`. This can cause caching issues when the processing function is stateful and sensible to the order in which examples are processed Close https://github.com/huggingface/datasets/issues/3847
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add draft of registering function for pandas
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2022-03-14T17:54:29Z
2023-09-24T09:55:01Z
2023-01-24T12:57:10Z
MEMBER
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This PR adds a register function for `pandas`. It allows to directly push `DataFrame` objects to the hub and in return loading datasets on the hub from `DataFrame`. The motivation for this integration is to enable the vast number of `pandas` users to be able to easily push `DataFrames` to the hub. Here is an example: ```python import pandas as pd from datasets import register_pandas register_pandas() # push to hub df = pd.DataFrame.from_dict({"test": [1,2,3]}) df.push_to_hub("my_test") # load from hub df_retrieved = pd.DataFrame.load_from_hub("lvwerra/my_test") ``` It follows a similar philosophy as the `tqdm` [integration](https://github.com/tqdm/tqdm#pandas-integration). Also see [this issue](https://github.com/pandas-dev/pandas/issues/46000) on the `pandas` repository. This is just a rough draft of what such integration could look like but I would like appreciate some feedback on this: is this something you would like to add the library and is this the way to go? cc @lhoestq @albertvillanova @julien-c
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3,911
Create README.md for CER metric
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2022-03-14T16:54:51Z
2022-03-17T17:49:40Z
2022-03-17T17:45:54Z
CONTRIBUTOR
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Initial proposal for a CER metric card cc @patrickvonplaten - wdyt this time around? :smile:
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Fix text loader to split only on universal newlines
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2022-03-14T15:54:58Z
2022-03-15T16:16:11Z
2022-03-15T16:16:09Z
MEMBER
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Currently, `text` loader breaks on a superset of universal newlines, which also contains Unicode line boundaries. See: https://docs.python.org/3/library/stdtypes.html#str.splitlines However, the expected behavior is to get the lines splitted only on universal newlines: "\n", "\r\n" and "\r". See: oscar-corpus/corpus#18 Fix #3729.
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Error loading file audio when downloading the Common Voice dataset directly from the Hub
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2023-03-02T15:31:27Z
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## Describe the bug When loading the Common_Voice dataset, by downloading it directly from the Hugging Face hub, some files can not be opened. ## Steps to reproduce the bug ```python import torch import torchaudio from datasets import load_dataset, load_metric from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor import re test_dataset = load_dataset("common_voice", "it", split="test") #test_dataset = load_dataset('csv', data_files = {'test': '/workspace/Dataset/Common_Voice/cv-corpus80/it/test.csv'}) wer = load_metric("wer") processor = Wav2Vec2Processor.from_pretrained("joorock12/wav2vec2-large-xlsr-italian") model = Wav2Vec2ForCTC.from_pretrained("joorock12/wav2vec2-large-xlsr-italian") model.to("cuda") chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\'\�]' resampler = torchaudio.transforms.Resample(48_000, 16_000) ``` ## Expected results The common voice dataset downloaded and correctly loaded whit the use of the hugging face datasets library. ## Actual results The error is: ```python 0ex [00:00, ?ex/s] --------------------------------------------------------------------------- RuntimeError Traceback (most recent call last) <ipython-input-48-ef87f4129e6e> in <module> 7 return batch 8 ----> 9 test_dataset = test_dataset.map(speech_file_to_array_fn) /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc) 2107 2108 if num_proc is None or num_proc == 1: -> 2109 return self._map_single( 2110 function=function, 2111 with_indices=with_indices, /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs) 516 self: "Dataset" = kwargs.pop("self") 517 # apply actual function --> 518 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 519 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 520 for dataset in datasets: /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs) 483 } 484 # apply actual function --> 485 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 486 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 487 # re-apply format to the output /opt/conda/lib/python3.8/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs) 411 # Call actual function 412 --> 413 out = func(self, *args, **kwargs) 414 415 # Update fingerprint of in-place transforms + update in-place history of transforms /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in _map_single(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only) 2465 if not batched: 2466 for i, example in enumerate(pbar): -> 2467 example = apply_function_on_filtered_inputs(example, i, offset=offset) 2468 if update_data: 2469 if i == 0: /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples, offset) 2372 if with_rank: 2373 additional_args += (rank,) -> 2374 processed_inputs = function(*fn_args, *additional_args, **fn_kwargs) 2375 if update_data is None: 2376 # Check if the function returns updated examples /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in decorated(item, *args, **kwargs) 2067 ) 2068 # Use the LazyDict internally, while mapping the function -> 2069 result = f(decorated_item, *args, **kwargs) 2070 # Return a standard dict 2071 return result.data if isinstance(result, LazyDict) else result <ipython-input-48-ef87f4129e6e> in speech_file_to_array_fn(batch) 3 def speech_file_to_array_fn(batch): 4 batch["sentence"] = re.sub(chars_to_ignore_regex, '', batch["sentence"]).lower() ----> 5 speech_array, sampling_rate = torchaudio.load(batch["path"]) 6 batch["speech"] = resampler(speech_array).squeeze().numpy() 7 return batch /opt/conda/lib/python3.8/site-packages/torchaudio/backend/sox_io_backend.py in load(filepath, frame_offset, num_frames, normalize, channels_first, format) 150 filepath, frame_offset, num_frames, normalize, channels_first, format) 151 filepath = os.fspath(filepath) --> 152 return torch.ops.torchaudio.sox_io_load_audio_file( 153 filepath, frame_offset, num_frames, normalize, channels_first, format) 154 RuntimeError: Error loading audio file: failed to open file common_voice_it_17415776.mp3 ``` ## Environment info - `datasets` version: 1.18.4 - Platform: Linux-5.4.0-x86_64-with-glibc2.10 - Python version: 3.8.5 - PyArrow version: 7.0.0
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Putting "Values from popular papers" as a subsection of "Output values"
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Putting "Values from popular papers" as a subsection of "Output values"
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NonMatchingChecksumError on Spider dataset
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## Describe the bug Failure to generate dataset ```spider``` because of checksums error for dataset source files. ## Steps to reproduce the bug ``` from datasets import load_dataset spider = load_dataset("spider") ``` ## Expected results Checksums should match for files from url ['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0'] ## Actual results ``` >>> load_dataset("spider") load_dataset("spider") Downloading and preparing dataset spider/spider (download: 95.12 MiB, generated: 5.17 MiB, post-processed: Unknown size, total: 100.29 MiB) to /home/user/.cache/huggingface/datasets/spider/spider/1.0.0/79778ebea87c59b19411f1eb3eda317e9dd5f7788a556d837ef25c3ae6e5e8b7... Traceback (most recent call last): File "/home/user/py3_env/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3441, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-5-d4cb54197348>", line 1, in <module> load_dataset("spider") File "/home/user/py3_env/lib/python3.8/site-packages/datasets/load.py", line 1702, in load_dataset builder_instance.download_and_prepare( File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 594, in download_and_prepare self._download_and_prepare( File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 665, in _download_and_prepare verify_checksums( File "/home/user/py3_env/lib/python3.8/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://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0'] ``` ## Environment info datasets version: 1.18.3 Platform: Ubuntu 20 LTS Python version: 3.8.10 PyArrow version: 6.0.1
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Perplexity Metric Card
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2022-03-14T12:39:40Z
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CONTRIBUTOR
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Add Perplexity metric card Note that it is currently still missing the citation, but I plan to add it later today.
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CONLL2003 Dataset not available
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2022-03-13T23:46:15Z
2023-06-28T18:08:16Z
2022-03-17T08:21:32Z
NONE
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## Describe the bug [CONLL2003](https://huggingface.co/datasets/conll2003) Dataset can no longer reach 'https://data.deepai.org/conll2003.zip' ![image](https://user-images.githubusercontent.com/4755430/158084483-ff83631c-5154-4823-892d-577bf1166db0.png) ## Steps to reproduce the bug ```python from datasets import load_dataset datasets = load_dataset("conll2003") ``` ## Expected results Download the conll2003 dataset. ## Actual results Error: `ConnectionError: Couldn't reach https://data.deepai.org/conll2003.zip (error 502)`
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Add Biwi Kinect Head Pose dataset.
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2022-03-13T08:59:21Z
2022-05-31T17:02:19Z
2022-05-31T12:15:58Z
CONTRIBUTOR
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This PR adds the Biwi Kinect Head Pose dataset. Dataset Request : Add Biwi Kinect Head Pose Database [#3822](https://github.com/huggingface/datasets/issues/3822) The Biwi Kinect Head Pose Database is acquired with the Microsoft Kinect sensor, a structured IR light device.It contains 15K images of 20 people with 6 females and 14 males where 4 people were recorded twice. For each frame, there is : - a depth image, (.bin file) - a corresponding rgb image (both 640x480 pixels), - annotation ( present inside a .txt file) The ground truth is the 3D location of the head and its rotation. The dataset structure is as follows : ``` - 01.obj - 01 - frame_00003_depth.bin - frame_00003_pose.txt - frame_00003_rgb.png . . . - 02.obj - 02 - frame_00003_depth.bin - frame_00003_pose.txt - frame_00003_rgb.png . . . ``` Preview of frame_00003_pose.txt : ``` 0.988397 0.0731349 0.133128 -0.0441539 0.976945 -0.208876 -0.145334 0.200575 0.968838 126.665 40.4515 876.198 ``` I have used the following dataset features : ``` features=datasets.Features( { "person_id": datasets.Value("string"), "frame_number": datasets.Value("string"), "depth_image": datasets.Value("string"), "rgb_image": datasets.Image(), "3D_head_center": datasets.Array2D(shape=(3, 3), dtype="float"), "3D_head_rotation": datasets.Value("float"), } ``` I am giving the path to the depth_image here. I need some inputs for the following : 1. For each person, the dataset has the following additional information : ``` For each sequence, the corresponding .obj file represents a head template deformed to match the neutral face of that specific person. [*.obj file] In each folder, two .cal files contain calibration information for the depth and the color camera, e.g., the intrinsic camera matrix of the depth camera and the global rotation and translation to the rgb camera. ``` Wanted to know how we can represent these features ? 2. For _generate_examples , do I parse the directories and fetch the required information ? This would mean reading the .txt file to obtain the "3D_head_center" and "3D_head_rotation" details. We could precompute the features information and have a metadata file and use the metadata file to yield information in _generate_examples ? Wanted your thoughts for the best approach for this ?
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Can't import datasets: partially initialized module 'fsspec' has no attribute 'utils'
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2022-03-12T21:22:03Z
2023-02-09T14:53:49Z
2022-03-22T07:10:41Z
NONE
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## Describe the bug Unable to import datasets ## Steps to reproduce the bug ```python from datasets import Dataset, DatasetDict ``` ## Expected results The import works without errors ## Actual results ``` AttributeError Traceback (most recent call last) <ipython-input-37-c8cfcbe62127> in <module> 11 # from tqdm import tqdm 12 # import torch ---> 13 from datasets import Dataset 14 # from transformers import Trainer, TrainingArguments, AutoModel, AutoTokenizer, AutoModelForMaskedLM, DataCollatorForLanguageModeling 15 # from sentence_transformers import SentenceTransformer ~/.local/lib/python3.8/site-packages/datasets/__init__.py in <module> 31 ) 32 ---> 33 from .arrow_dataset import Dataset, concatenate_datasets 34 from .arrow_reader import ArrowReader, ReadInstruction 35 from .arrow_writer import ArrowWriter ~/.local/lib/python3.8/site-packages/datasets/arrow_dataset.py in <module> 46 ) 47 ---> 48 import fsspec 49 import numpy as np 50 import pandas as pd ~/.local/lib/python3.8/site-packages/fsspec/__init__.py in <module> 10 from . import _version, caching 11 from .callbacks import Callback ---> 12 from .core import get_fs_token_paths, open, open_files, open_local 13 from .exceptions import FSTimeoutError 14 from .mapping import FSMap, get_mapper ~/.local/lib/python3.8/site-packages/fsspec/core.py in <module> 16 caches, 17 ) ---> 18 from .compression import compr 19 from .registry import filesystem, get_filesystem_class 20 from .utils import ( ~/.local/lib/python3.8/site-packages/fsspec/compression.py in <module> 68 69 ---> 70 register_compression("zip", unzip, "zip") 71 register_compression("bz2", BZ2File, "bz2") 72 ~/.local/lib/python3.8/site-packages/fsspec/compression.py in register_compression(name, callback, extensions, force) 44 45 for ext in extensions: ---> 46 if ext in fsspec.utils.compressions and not force: 47 raise ValueError( 48 "Duplicate compression file extension: %s (%s)" % (ext, name) AttributeError: partially initialized module 'fsspec' has no attribute 'utils' (most likely due to a circular import) ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.18.4 - Platform: Jupyter notebook - Python version: 3.8.10 - PyArrow version: 7.0.0
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Dataset viewer issue for IndicParaphrase- the preview doesn't show
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2022-03-12T16:56:05Z
2022-04-12T12:10:50Z
2022-04-12T12:10:49Z
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## Dataset viewer issue for '*IndicParaphrase*' **Link:** *[IndicParaphrase](https://huggingface.co/datasets/ai4bharat/IndicParaphrase/viewer/hi/validation)* *The preview of the dataset doesn't come up. The error on the console is: Status code: 400 Exception: FileNotFoundError Message: [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/hi_IndicParaphrase_v1.0.tar'* Am I the one who added this dataset ? Yes
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Add MetaShift dataset
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2022-03-12T08:44:18Z
2022-04-01T16:59:48Z
2022-04-01T15:16:30Z
CONTRIBUTOR
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This PR adds the MetaShift dataset. Dataset Request : Add MetaShift dataset [#3813](https://github.com/huggingface/datasets/issues/3813) @lhoestq As discussed, - I have copied the preprocessing script and modified it as required to not create new directories and folders and instead yield the images. - I do the preprocessing in _split_generators to get the required data which is then passed to _generate_examples. - Beyond the generated MetaShift dataset, the original preprocess script also generates the meta-graphs for each class, I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#generate-full-metashift) ] - There is a Bonus section, the authors share. I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#bonus-generate-the-metashift-attributes-dataset-subsets-defined-by-subject-attributes) ] - I had a basic test script which downloaded the dataset and tested the basic functionality. Things seems fine. For real data, I performed the following test : ``` RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_metashift ============================================== test session starts =============================================== platform linux -- Python 3.7.11, pytest-7.0.1, pluggy-1.0.0 rootdir: ./datasets plugins: hydra-core-1.1.1, datadir-1.3.1, forked-1.4.0, xdist-2.5.0 collected 1 item tests/test_dataset_common.py . [100%] ========================================= 1 passed in 4821.25s (1:20:21) ========================================= ``` - I couldn't get the dummy dataset. Need some inputs here. Error as follows : ``` Using custom data configuration default Dataset metashift with config None seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file dummy_data/full-candidate-subsets.pkl. for split in generator_splits: UnboundLocalError: local variable 'generator_splits' referenced before assignment ``` To-Do : - [x] Currently I am using the default _SELECTED_CLASSES. I need to use config option here as suggested - [x] Complete fields in the Dataset Card. - [x] Tagging the dataset using the Datasets Tagging app. Need your help and suggestions for improvement. Thank you
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Add exact match metric
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2022-03-11T22:21:40Z
2022-03-21T16:10:03Z
2022-03-21T16:05:35Z
CONTRIBUTOR
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Adding the exact match metric and its metric card. Note: Some of the tests have failed, but I wanted to make a PR anyway so that the rest of the code can be reviewed if anyone has time. I'll look into + work on fixing the failed tests when I'm back online after the weekend
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Create README.md for WER metric
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2022-03-11T19:29:09Z
2022-03-15T17:05:00Z
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CONTRIBUTOR
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Proposing a draft WER metric card, @lhoestq I'm not very certain about "Values from popular papers" -- I don't know ASR very well, what do you think of the examples I found?
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Align tqdm control/cache control with Transformers
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2022-03-11T18:12:22Z
2022-03-14T15:01:10Z
2022-03-14T15:01:08Z
COLLABORATOR
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This PR: * aligns the `tqdm` logic with Transformers (follows https://github.com/huggingface/transformers/pull/15167) by moving the code to `utils/logging.py`, adding `enable_progres_bar`/`disable_progres_bar` and removing `set_progress_bar_enabled` (a note for @lhoestq: I'm not adding `logging.tqdm` to the public namespace in this PR to avoid the situation where `from datasets import *; tqdm` would overshadow the standard `tqdm` * aligns the cache control with the new `tqdm` logic by adding `enable_caching`/`disable_caching` to the public namespace and deprecating `set_caching_enabled` (not fully removing it because it's used more often than `set_progress_bar_enabled` and has a dedicated example in the old docs) Fix #3586
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Missing google file for `multi_news` dataset
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2022-03-11T16:38:10Z
2022-03-15T12:30:23Z
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## Dataset viewer issue for '*multi_news*' **Link:** https://huggingface.co/datasets/multi_news ``` Server error Status code: 400 Exception: FileNotFoundError Message: https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C/multi-news-original/train.src ``` Am I the one who added this dataset ? No
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Fix code examples indentation
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MEMBER
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Some code examples are currently not rendered correctly. I think this is because they are over-indented cc @mariosasko
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PR_kwDODunzps40TzXW
3,894
[docs] make dummy data creation optional
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2022-03-11T16:21:34Z
2022-03-11T17:27:56Z
2022-03-11T17:27:55Z
MEMBER
null
null
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Related to #3507 : dummy data for datasets created on the Hugging Face Hub are optional. We can discuss later to make them optional for datasets in this repository as well
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PR_kwDODunzps40TmxB
3,893
Add default branch for doc building
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2022-03-11T15:24:27Z
2022-03-11T15:34:35Z
2022-03-11T15:34:34Z
CONTRIBUTOR
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Since other libraries use `main` as their default branch and it's now the standard default, you have to specify a different name in the doc config if you're using `master` like datasets (`doc-builder` tries to guess it, but in the job, we have weird checkout of merge commits so it doesn't always manage to get it right). This PR makes sure it will always use master for the dev doc (until you decide to switchto main)
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3,892
Fix CLI test checksums
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2022-03-11T10:04:04Z
2022-03-15T12:28:24Z
2022-03-15T12:28:23Z
MEMBER
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Previous PR: - #3796 introduced a side effect: `datasets-cli test` generates `dataset_infos.json` with `None` checksum values. See: - #3805 This PR introduces a way for `datasets-cli test` to force to record infos, even if `verify_infos=False` Close #3848. CC: @craffel
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3,891
Fix race condition in doc build
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2022-03-10T17:17:10Z
2022-03-10T17:23:00Z
2022-03-10T17:17:30Z
MEMBER
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Following https://github.com/huggingface/datasets/runs/5499386744 it seems that race conditions that create issues when updating the doc. I took the same approach as in `transformers` to fix race conditions
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3,890
Update beans download urls
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2022-03-10T17:16:16Z
2022-03-15T16:47:30Z
2022-03-15T15:26:48Z
COLLABORATOR
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Replace the old URLs with the Hub [URLs](https://huggingface.co/datasets/beans/tree/main/data). Also reported by @stevhliu. Fix #3889
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Cannot load beans dataset (Couldn't reach the dataset)
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NONE
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## Describe the bug The beans dataset is unavailable to download. ## Steps to reproduce the bug ```python from datasets import load_dataset ds = load_dataset('beans') ``` ## Expected results The dataset would be downloaded with no issue. ## Actual results ``` ConnectionError: Couldn't reach https://storage.googleapis.com/ibeans/train.zip (error 403) ``` [It looks like the billing of this project has been disabled because it is associated with a delinquent account.](https://storage.googleapis.com/ibeans/train.zip ) ## Environment info Google Colab
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IterableDataset columns and feature types
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2022-03-10T16:19:12Z
2022-11-29T11:39:24Z
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MEMBER
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Right now, an IterableDataset (e.g. when streaming a dataset) doesn't require to know the list of columns it contains, nor their types: `my_iterable_dataset.features` may be `None` However it's often interesting to know the column types and types. This helps knowing what's inside your dataset without having to manually check a few examples, and this is useful to prepare a processing pipeline or to train models. Here are a few cases that lead to `features` being `None`: 1. when loading a dataset with `load_dataset` on CSV, JSON Lines, etc. files: type inference is only done when iterating over the dataset 2. when calling `map`, because we don't know in advance what's the output of the user's function passed to `map` 3. when calling `rename_columns`, `remove_columns`, etc. because they rely on `map` Things we can consider, for each point above: 1.a infer the type automatically from the first samples on the dataset using prefetching, when the dataset builder doesn't provide the `features` 2.a allow the user to specify the `features` as an argument to `map` (this would be consistent with the non-streaming API) 2.b prefetch the first output value to infer the type 3.a don't rely on `map` directly and reuse the previous `features` and rename/remove the corresponding ones The thing is that prefetching can take a few seconds, while the operations above are instantaneous since no data are downloaded. Therefore I'm not sure whether this solution may be worth it. Maybe prefetching could also be done when explicitly asked by the user cc @mariosasko @albertvillanova
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2022-03-10T15:34:46Z
2022-03-11T15:06:11Z
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This PR adds the following improvements to the `imagefolder` dataset: * skip the extract step for image files (as discussed in https://github.com/huggingface/datasets/pull/2830#discussion_r816817919) * option to drop labels by setting `drop_labels=True` (useful for image pretraining cc @NielsRogge). This is faster than loading a dataset and removing the `label` column because we don't need to iterate over the files to infer class labels.
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Retry HfApi call inside push_to_hub when 504 error
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2022-03-10T13:24:40Z
2022-03-16T09:00:56Z
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MEMBER
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Ass suggested by @lhoestq in #3872, this PR: - Implements a retry function - Retries HfApi call inside `push_to_hub` when 504 error. To be agreed: - max_retries = 2 (at 0.5 and 1 seconds) Fix #3872.
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2022-03-10T11:29:15Z
2022-03-10T14:16:29Z
2022-03-10T14:16:28Z
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Following #3842 some docs were still outdated (with `buffer_size` as the first argument)
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2022-03-10T08:44:20Z
2022-03-10T09:03:40Z
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MEMBER
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Fix #3883.
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3,883
The metric Meteor doesn't work for nltk ==3.6.4
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2022-03-10T09:03:39Z
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## Describe the bug Using the metric Meteor with nltk == 3.6.4 gives a TypeError: TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object ## Steps to reproduce the bug ```python import datasets metric = datasets.load_metric("meteor") predictions = ["hello world"] references = ["hello world"] metric.compute(predictions=predictions, references=references) ``` ## Expected results TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object I think this TypeError exists because input sentences are tokenized into lists of tokens and the str.lower() is applied to this list of tokens. ## Actual results No error but a meteor score ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.18.3 - Platform: linux - Python version: 3.8.12 - PyArrow version: 7.0.0
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Image process doc
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2022-03-15T15:24:16Z
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MEMBER
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This PR is a first draft of how to process image data. It adds: - Load an image dataset with `image` and `path` (adds tip about `decode=False` param to access the path and bytes, thanks to @mariosasko). - Load an image using the `ImageFolder` builder. I know there is an [example](https://huggingface.co/docs/datasets/master/en/loading#image-folders) of this already, but I also wanted to add it here so users don't miss it. This doc seems important for centralizing all of the image-related things so far. Datasets has grown so quickly 🚀 now that I think maybe splitting up the How-to guides by modality may be better since working with vision/audio data is slightly different from what users have seen up until now. This way we can continue to scale the docs to better accommodate vision/audio things. - Add a data augmentation with `set_transform`. There is only 1 example here so far, but we can certainly add more. Todo: - [x] Couldn't figure out why my augmentation function works with `set_transform` but not `map` 🥲. Working with @mariosasko on this!
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How to use Image folder
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Ran this code ``` load_dataset("imagefolder", data_dir="./my-dataset") ``` `https://raw.githubusercontent.com/huggingface/datasets/master/datasets/imagefolder/imagefolder.py` missing ``` --------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) /tmp/ipykernel_33/1648737256.py in <module> ----> 1 load_dataset("imagefolder", data_dir="./my-dataset") /opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, script_version, **config_kwargs) 1684 revision=revision, 1685 use_auth_token=use_auth_token, -> 1686 **config_kwargs, 1687 ) 1688 /opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, script_version, **config_kwargs) 1511 download_config.use_auth_token = use_auth_token 1512 dataset_module = dataset_module_factory( -> 1513 path, revision=revision, download_config=download_config, download_mode=download_mode, data_files=data_files 1514 ) 1515 /opt/conda/lib/python3.7/site-packages/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_files, **download_kwargs) 1200 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. " 1201 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}" -> 1202 ) from None 1203 raise e1 from None 1204 else: FileNotFoundError: Couldn't find a dataset script at /kaggle/working/imagefolder/imagefolder.py or any data file in the same directory. Couldn't find 'imagefolder' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/imagefolder/imagefolder.py ```
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Change the framework switches to the new syntax
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2022-03-15T14:13:28Z
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CONTRIBUTOR
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This PR updates the syntax of the framework-specific code samples. With this new syntax, you'll be able to: - have paragraphs of text be framework-specific instead of just code samples - have support for Flax code samples if you want. This should be merged after https://github.com/huggingface/doc-builder/pull/63 and https://github.com/huggingface/doc-builder/pull/130
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SQuAD v2 metric: create README.md
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2022-03-09T18:47:56Z
2022-03-10T16:48:59Z
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CONTRIBUTOR
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Proposing SQuAD v2 metric card
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PR_kwDODunzps40MOpn
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Update cats_vs_dogs size
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2022-03-09T18:40:56Z
2022-09-30T08:47:43Z
2022-03-10T14:21:23Z
COLLABORATOR
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It seems like 12 new examples have been added to the `cats_vs_dogs`. This PR updates the size in the card and the info file to avoid a verification error (reported by @stevhliu).
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I_kwDODunzps5FY3aH
3,877
Align metadata to DCAT/DCAT-AP
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2022-03-09T16:12:25Z
2022-03-09T16:33:42Z
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NONE
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**Is your feature request related to a problem? Please describe.** Align to DCAT metadata to describe datasets **Describe the solution you'd like** Reuse terms and structure from DCAT in the metadata file, ideally generate a json-ld file dcat compliant **Describe alternatives you've considered** **Additional context** DCAT is a W3C standard extended in Europe with DCAT-AP, an example is data.europa.eu publishing datasets metadata in DCAT-AP
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Fix download_mode in dataset_module_factory
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2022-03-09T14:54:33Z
2022-03-10T08:47:00Z
2022-03-10T08:46:59Z
MEMBER
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Fix `download_mode` value set in `dataset_module_factory`. Before the fix, it was set to `bool` (default to `False`). Also set properly its default value in all public functions.
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Module namespace cleanup for v2.0
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2022-03-09T14:43:07Z
2022-03-11T15:42:06Z
2022-03-11T15:42:05Z
COLLABORATOR
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This is an attempt to make the user-facing `datasets`' submodule namespace cleaner: In particular, this PR does the following: * removes the unused `zip_nested` and `flatten_nest_dict` and their accompanying tests * removes `pyarrow` from the top-level namespace * properly uses `__all__` and the `from <module> import *` syntax to avoid importing the `<module>`'s submodules * cleans up the `utils` namespace * moves the `temp_seed` context manage from `datasets/utils/file_utils.py` to `datasets/utils/py_utils.py`
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add MSE and MAE metrics - V2
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2022-03-09T14:30:16Z
2022-03-09T17:20:42Z
2022-03-09T17:18:20Z
CONTRIBUTOR
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Created a new pull request to resolve unrelated changes in PR caused due to rebasing. Ref Older PR : [#3845](https://github.com/huggingface/datasets/pull/3845) Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608)
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Create SQuAD metric README.md
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2022-03-09T13:47:08Z
2022-03-10T16:45:57Z
2022-03-10T16:45:57Z
CONTRIBUTOR
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Proposal for a metrics card structure (with an example based on the SQuAD metric). @thomwolf @lhoestq @douwekiela @lewtun -- feel free to comment on structure or content (it's an initial draft, so I realize there's stuff missing!).
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HTTP error 504 Server Error: Gateway Time-out
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2022-03-15T16:19:50Z
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I am trying to push a large dataset(450000+) records with the help of `push_to_hub()` While pushing, it gives some error like this. ``` Traceback (most recent call last): File "data_split_speech.py", line 159, in <module> data_new_2.push_to_hub("user-name/dataset-name",private=True) File "/opt/conda/lib/python3.8/site-packages/datasets/dataset_dict.py", line 951, in push_to_hub repo_id, split, uploaded_size, dataset_nbytes = self[split]._push_parquet_shards_to_hub( File "/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 3556, in _push_parquet_shards_to_hub api.upload_file( File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1017, in upload_file raise err File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1008, in upload_file r.raise_for_status() File "/opt/conda/lib/python3.8/site-packages/requests/models.py", line 953, in raise_for_status raise HTTPError(http_error_msg, response=self) requests.exceptions.HTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/user-name/dataset-name/upload/main/data/train2-00041-of-00064.parquet ``` Can anyone help me to resolve this issue.
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add pandas to env command
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2022-03-09T09:48:51Z
2022-03-09T11:21:38Z
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CONTRIBUTOR
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Pandas is a required packages and used quite a bit. I don't see any downside with adding its version to the `datasets-cli env` command.
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Add wikitablequestions dataset
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2022-03-14T11:19:24Z
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Making the Hub the place for datasets in Portuguese
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Let's make Hugging Face Datasets the central hub for datasets in Portuguese :) **Motivation**. Datasets are currently quite scattered and an open-source central point such as the Hugging Face Hub would be ideal to support the growth of the Portuguese speaking community. What are some datasets in Portuguese worth integrating into the Hugging Face hub? Special thanks to @augusnunes for his collaboration on identifying the first ones: - [NILC - USP](http://www.nilc.icmc.usp.br/nilc/index.php/tools-and-resources). Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). cc @osanseviero
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Ignore duplicate keys if `ignore_verifications=True`
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2022-03-08T17:14:56Z
2022-03-09T13:50:45Z
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COLLABORATOR
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Currently, it's impossible to generate a dataset if some keys from `_generate_examples` are duplicated. This PR allows skipping the check for duplicate keys if `ignore_verifications` is set to `True`.
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Update for the rename doc-builder -> hf-doc-utils
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2022-03-08T16:58:25Z
2023-09-24T09:54:44Z
2022-03-08T17:30:45Z
CONTRIBUTOR
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This PR adapts the job to the upcoming change of name of `doc-builder`.
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PR_kwDODunzps40HWcu
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Bring back imgs so that forsk dont get broken
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2022-03-08T16:01:31Z
2022-03-08T17:37:02Z
2022-03-08T17:37:01Z
NONE
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Add logo img
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2022-03-08T15:50:59Z
2023-09-24T09:54:31Z
2022-03-08T16:01:59Z
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Update image dataset tags
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2022-03-08T15:36:32Z
2022-03-08T17:04:47Z
2022-03-08T17:04:46Z
COLLABORATOR
null
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Align the existing image datasets' tags with new tags introduced in #3800.
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