Datasets:

devopsmarc
/

my-issues-dataset

html_url stringlengths 48 51	title stringlengths 5 155	comments stringlengths 63 15.7k	body stringlengths 0 17.7k	comment_length int64 16 949	text stringlengths 164 23.7k
https://github.com/huggingface/datasets/issues/1167	❓ On-the-fly tokenization with datasets, tokenizers, and torch Datasets and Dataloaders	We're working on adding on-the-fly transforms in datasets. Currently the only on-the-fly functions that can be applied are in `set_format` in which we transform the data in either numpy/torch/tf tensors or pandas. For example ```python dataset.set_format("torch") ``` applies `torch.Tensor` to the dataset entries ...	Hi there, I have a question regarding "on-the-fly" tokenization. This question was elicited by reading the "How to train a new language model from scratch using Transformers and Tokenizers" [here](https://huggingface.co/blog/how-to-train). Towards the end there is this sentence: "If your dataset is very large, you c...	63	❓ On-the-fly tokenization with datasets, tokenizers, and torch Datasets and Dataloaders Hi there, I have a question regarding "on-the-fly" tokenization. This question was elicited by reading the "How to train a new language model from scratch using Transformers and Tokenizers" [here](https://huggingface.co/blog/ho...
https://github.com/huggingface/datasets/issues/1110	Using a feature named "_type" fails with certain operations	Thanks for reporting ! Indeed this is a keyword in the library that is used to encode/decode features to a python dictionary that we can save/load to json. We can probably change `_type` to something that is less likely to collide with user feature names. In this case we would want something backward compatible th...	A column named `_type` leads to a `TypeError: unhashable type: 'dict'` for certain operations: ```python from datasets import Dataset, concatenate_datasets ds = Dataset.from_dict({"_type": ["whatever"]}).map() concatenate_datasets([ds]) # or simply Dataset(ds._data) ``` Context: We are using datasets to persi...	74	Using a feature named "_type" fails with certain operations A column named `_type` leads to a `TypeError: unhashable type: 'dict'` for certain operations: ```python from datasets import Dataset, concatenate_datasets ds = Dataset.from_dict({"_type": ["whatever"]}).map() concatenate_datasets([ds]) # or simply D...
https://github.com/huggingface/datasets/issues/1103	Add support to download kaggle datasets	Hey, I think this is great idea. Any plan to integrate kaggle private datasets loading to `datasets`?	We can use API key	17	Add support to download kaggle datasets We can use API key Hey, I think this is great idea. Any plan to integrate kaggle private datasets loading to `datasets`?
https://github.com/huggingface/datasets/issues/1103	Add support to download kaggle datasets	The workflow for downloading a Kaggle dataset and turning it into an HF dataset is pretty simple: ```python !kaggle datasets download -p path ds = load_dataset(path) ``` Native support would make our download logic even more complex, and I don't think this is a good idea considering this particular feature is no...	We can use API key	77	Add support to download kaggle datasets We can use API key The workflow for downloading a Kaggle dataset and turning it into an HF dataset is pretty simple: ```python !kaggle datasets download -p path ds = load_dataset(path) ``` Native support would make our download logic even more complex, and I don't thin...
https://github.com/huggingface/datasets/issues/1064	Not support links with 302 redirect	> Hi ! > This kind of links is now supported by the library since #1316 I updated links in TLC datasets to be the github links in this pull request https://github.com/huggingface/datasets/pull/1737 Everything works now. Thank you.	I have an issue adding this download link https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz it might be because it is not a direct link (it returns 302 and redirects to aws that returns 403 for head requests). ``` r.head("https://github.com/jitkapat/thailitcorpus/releases/downlo...	37	Not support links with 302 redirect I have an issue adding this download link https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz it might be because it is not a direct link (it returns 302 and redirects to aws that returns 403 for head requests). ``` r.head("https://github.com...
https://github.com/huggingface/datasets/issues/1046	Dataset.map() turns tensors into lists?	A solution is to have the tokenizer return a list instead of a tensor, and then use `dataset_tok.set_format(type = 'torch')` to convert that list into a tensor. Still not sure if bug.	I apply `Dataset.map()` to a function that returns a dict of torch tensors (like a tokenizer from the repo transformers). However, in the mapped dataset, these tensors have turned to lists! ```import datasets import torch from datasets import load_dataset ...	32	Dataset.map() turns tensors into lists? I apply `Dataset.map()` to a function that returns a dict of torch tensors (like a tokenizer from the repo transformers). However, in the mapped dataset, these tensors have turned to lists! ```import datasets import torch from datasets import load_dataset ...
https://github.com/huggingface/datasets/issues/1046	Dataset.map() turns tensors into lists?	It is expected behavior, you should set the format to `"torch"` as you mentioned to get pytorch tensors back. By default datasets returns pure python objects.	I apply `Dataset.map()` to a function that returns a dict of torch tensors (like a tokenizer from the repo transformers). However, in the mapped dataset, these tensors have turned to lists! ```import datasets import torch from datasets import load_dataset ...	26	Dataset.map() turns tensors into lists? I apply `Dataset.map()` to a function that returns a dict of torch tensors (like a tokenizer from the repo transformers). However, in the mapped dataset, these tensors have turned to lists! ```import datasets import torch from datasets import load_dataset ...
https://github.com/huggingface/datasets/issues/1004	how large datasets are handled under the hood	This library uses Apache Arrow under the hood to store datasets on disk. The advantage of Apache Arrow is that it allows to memory map the dataset. This allows to load datasets bigger than memory and with almost no RAM usage. It also offers excellent I/O speed. For example when you access one element or one batch ...	Hi I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the hood and you bring in memory when necessary, than...	90	how large datasets are handled under the hood Hi I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the ...
https://github.com/huggingface/datasets/issues/1004	how large datasets are handled under the hood	How can we change how much data is loaded to memory with Arrow? I think that I am having some performance issue with it. When Arrow loads the data from disk it does it in multiprocess? It's almost twice slower training with arrow than in memory. EDIT: My fault! I had not seen the `dataloader_num_workers` in `Traini...	Hi I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the hood and you bring in memory when necessary, than...	68	how large datasets are handled under the hood Hi I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the ...
https://github.com/huggingface/datasets/issues/1004	how large datasets are handled under the hood	> How can we change how much data is loaded to memory with Arrow? I think that I am having some performance issue with it. When Arrow loads the data from disk it does it in multiprocess? It's almost twice slower training with arrow than in memory. Loading arrow data from disk is done with memory-mapping. This allows...	Hi I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the hood and you bring in memory when necessary, than...	192	how large datasets are handled under the hood Hi I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the ...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	Looks like the google drive download failed. I'm getting a `Google Drive - Quota exceeded` error while looking at the downloaded file. We should consider finding a better host than google drive for this dataset imo related : #873 #864	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	40	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	It is working now, thank you. Should I leave this issue open to address the Quota-exceeded error?	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	17	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	I've looked into it and couldn't find a solution. This looks like a Google Drive limitation.. Please try to use other hosts when possible	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	24	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	The original links are google drive links. Would it be feasible for HF to maintain their own servers for this? Also, I think the same issue must also exist with TFDS.	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	31	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	It's possible to host data on our side but we should ask the authors. TFDS has the same issue and doesn't have a solution either afaik. Otherwise you can use the google drive link, but it it's not that convenient because of this quota issue.	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	45	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	Okay. I imagine asking every author who shares their dataset on Google Drive will also be cumbersome.	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	17	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	Not as long as the data is stored on GG drive unfortunately. Maybe we can ask if there's a mirror ? Hi @JafferWilson is there a download link to get cnn dailymail from another host than GG drive ? To give you some context, this library provides tools to download and process datasets. For CNN DailyMail the data a...	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	84	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/996	NotADirectoryError while loading the CNN/Dailymail dataset	Thanks for the link @mrazizi ! Apparently the original authors don't host the dataset themselves ("for legal reasons", source [here](https://github.com/abisee/cnn-dailymail/issues/9)).	Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602... ---------------------------------------...	20	NotADirectoryError while loading the CNN/Dailymail dataset Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642...
https://github.com/huggingface/datasets/issues/993	Problem downloading amazon_reviews_multi	Hi @hfawaz ! This is working fine for me. Is it a repeated occurence? Have you tried from the latest verion?	Thanks for adding the dataset. After trying to load the dataset, I am getting the following error: `ConnectionError: Couldn't reach https://amazon-reviews-ml.s3-us-west-2.amazonaws.com/json/train/dataset_fr_train.json ` I used the following code to load the dataset: `load_dataset( dataset_name, ...	21	Problem downloading amazon_reviews_multi Thanks for adding the dataset. After trying to load the dataset, I am getting the following error: `ConnectionError: Couldn't reach https://amazon-reviews-ml.s3-us-west-2.amazonaws.com/json/train/dataset_fr_train.json ` I used the following code to load the dataset: `l...
https://github.com/huggingface/datasets/issues/988	making sure datasets are not loaded in memory and distributed training of them	my implementation of sharding per TPU core: https://github.com/google-research/ruse/blob/d4dd58a2d8efe0ffb1a9e9e77e3228d6824d3c3c/seq2seq/trainers/t5_trainer.py#L316 my implementation of dataloader for this case https://github.com/google-research/ruse/blob/d4dd58a2d8efe0ffb1a9e9e77e3228d6824d3c3c/seq2seq/tasks/tasks....	Hi I am dealing with large-scale datasets which I need to train distributedly, I used the shard function to divide the dataset across the cores, without any sampler, this does not work for distributed training and does not become any faster than 1 TPU core. 1) how I can make sure data is not loaded in memory 2) in cas...	16	making sure datasets are not loaded in memory and distributed training of them Hi I am dealing with large-scale datasets which I need to train distributedly, I used the shard function to divide the dataset across the cores, without any sampler, this does not work for distributed training and does not become any fast...
https://github.com/huggingface/datasets/issues/988	making sure datasets are not loaded in memory and distributed training of them	Hi! You can use the `assert not bool(dataset.cache_files)` assertion to ensure your data is in memory. And I suggest using `accelerate` for distributed training.	Hi I am dealing with large-scale datasets which I need to train distributedly, I used the shard function to divide the dataset across the cores, without any sampler, this does not work for distributed training and does not become any faster than 1 TPU core. 1) how I can make sure data is not loaded in memory 2) in cas...	24	making sure datasets are not loaded in memory and distributed training of them Hi I am dealing with large-scale datasets which I need to train distributedly, I used the shard function to divide the dataset across the cores, without any sampler, this does not work for distributed training and does not become any fast...
https://github.com/huggingface/datasets/issues/961	sample multiple datasets	here I share my dataloader currently for multiple tasks: https://gist.github.com/rabeehkarimimahabadi/39f9444a4fb6f53dcc4fca5d73bf8195 I need to train my model distributedly with this dataloader, "MultiTasksataloader", currently this does not work in distributed fasion, to save on memory I tried to use iterative d...	Hi I am dealing with multiple datasets, I need to have a dataloader over them with a condition that in each batch data samples are coming from one of the datasets. My main question is: - I need to have a way to sample the datasets first with some weights, lets say 2x dataset1 1x dataset2, could you point me how I c...	109	sample multiple datasets Hi I am dealing with multiple datasets, I need to have a dataloader over them with a condition that in each batch data samples are coming from one of the datasets. My main question is: - I need to have a way to sample the datasets first with some weights, lets say 2x dataset1 1x dataset2...
https://github.com/huggingface/datasets/issues/961	sample multiple datasets	Thanks @rabeehk for sharing. The sampler basically returns a list of integers to sample from each task's dataset. I was wondering how to use it with two `torch.Dataset` of different tasks. Also, do I need to shard across processes while creating an Iterable Dataset?	Hi I am dealing with multiple datasets, I need to have a dataloader over them with a condition that in each batch data samples are coming from one of the datasets. My main question is: - I need to have a way to sample the datasets first with some weights, lets say 2x dataset1 1x dataset2, could you point me how I c...	44	sample multiple datasets Hi I am dealing with multiple datasets, I need to have a dataloader over them with a condition that in each batch data samples are coming from one of the datasets. My main question is: - I need to have a way to sample the datasets first with some weights, lets say 2x dataset1 1x dataset2...
https://github.com/huggingface/datasets/issues/961	sample multiple datasets	We now have `interleave_datasets` in the API that allows you to cycle/sample with probabilities (with various stopping strategies) through a list of datasets. However, more specific behavior should be implemented manually.	Hi I am dealing with multiple datasets, I need to have a dataloader over them with a condition that in each batch data samples are coming from one of the datasets. My main question is: - I need to have a way to sample the datasets first with some weights, lets say 2x dataset1 1x dataset2, could you point me how I c...	31	sample multiple datasets Hi I am dealing with multiple datasets, I need to have a dataloader over them with a condition that in each batch data samples are coming from one of the datasets. My main question is: - I need to have a way to sample the datasets first with some weights, lets say 2x dataset1 1x dataset2...
https://github.com/huggingface/datasets/issues/937	Local machine/cluster Beam Datasets example/tutorial	I tried to make it run once on the SparkRunner but it seems that this runner has some issues when it is run locally. From my experience the DirectRunner is fine though, even if it's clearly not memory efficient. It would be awesome though to make it work locally on a SparkRunner ! Did you manage to make your proce...	Hi, I'm wondering if https://huggingface.co/docs/datasets/beam_dataset.html has an non-GCP or non-Dataflow version example/tutorial? I tried to migrate it to run on DirectRunner and SparkRunner, however, there were way too many runtime errors that I had to fix during the process, and even so I wasn't able to get eit...	62	Local machine/cluster Beam Datasets example/tutorial Hi, I'm wondering if https://huggingface.co/docs/datasets/beam_dataset.html has an non-GCP or non-Dataflow version example/tutorial? I tried to migrate it to run on DirectRunner and SparkRunner, however, there were way too many runtime errors that I had to fix d...
https://github.com/huggingface/datasets/issues/919	wrong length with datasets	Also, I cannot first convert it to torch format, since huggingface seq2seq_trainer codes process the datasets afterwards during datacollector function to make it optimize for TPUs.	Hi I have a MRPC dataset which I convert it to seq2seq format, then this is of this format: `Dataset(features: {'src_texts': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 10) ` I feed it to a dataloader: ``` dataloader = DataLoader( train_dataset, ...	26	wrong length with datasets Hi I have a MRPC dataset which I convert it to seq2seq format, then this is of this format: `Dataset(features: {'src_texts': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 10) ` I feed it to a dataloader: ``` dataloader = DataLoader( ...
https://github.com/huggingface/datasets/issues/915	Shall we change the hashing to encoding to reduce potential replicated cache files?	This is an interesting idea ! Do you have ideas about how to approach the decoding and the normalization ?	Hi there. For now, we are using `xxhash` to hash the transformations to fingerprint and we will save a copy of the processed dataset to disk if there is a new hash value. However, there are some transformations that are idempotent or commutative to each other. I think that encoding the transformation chain as the finge...	20	Shall we change the hashing to encoding to reduce potential replicated cache files? Hi there. For now, we are using `xxhash` to hash the transformations to fingerprint and we will save a copy of the processed dataset to disk if there is a new hash value. However, there are some transformations that are idempotent or ...
https://github.com/huggingface/datasets/issues/915	Shall we change the hashing to encoding to reduce potential replicated cache files?	@lhoestq I think we first need to save the transformation chain to a list in `self._fingerprint`. Then we can - decode all the current saved datasets to see if there is already one that is equivalent to the transformation we need now. - or, calculate all the possible hash value of the current chain for comparison so...	Hi there. For now, we are using `xxhash` to hash the transformations to fingerprint and we will save a copy of the processed dataset to disk if there is a new hash value. However, there are some transformations that are idempotent or commutative to each other. I think that encoding the transformation chain as the finge...	191	Shall we change the hashing to encoding to reduce potential replicated cache files? Hi there. For now, we are using `xxhash` to hash the transformations to fingerprint and we will save a copy of the processed dataset to disk if there is a new hash value. However, there are some transformations that are idempotent or ...
https://github.com/huggingface/datasets/issues/897	Dataset viewer issues	Thanks for reporting ! cc @srush for the empty feature list issue and the encoding issue cc @julien-c maybe we can update the url and just have a redirection from the old url to the new one ?	I was looking through the dataset viewer and I like it a lot. Version numbers, citation information, everything's there! I've spotted a few issues/bugs though: - the URL is still under `nlp`, perhaps an alias for `datasets` can be made - when I remove a feature (and the feature list is empty), I get an error. T...	38	Dataset viewer issues I was looking through the dataset viewer and I like it a lot. Version numbers, citation information, everything's there! I've spotted a few issues/bugs though: - the URL is still under `nlp`, perhaps an alias for `datasets` can be made - when I remove a feature (and the feature list is e...
https://github.com/huggingface/datasets/issues/897	Dataset viewer issues	Ok, I redirected on our side to a new url. ⚠️ @srush: if you update the Streamlit config too to `/datasets/viewer`, let me know because I'll need to change our nginx config at the same time	I was looking through the dataset viewer and I like it a lot. Version numbers, citation information, everything's there! I've spotted a few issues/bugs though: - the URL is still under `nlp`, perhaps an alias for `datasets` can be made - when I remove a feature (and the feature list is empty), I get an error. T...	36	Dataset viewer issues I was looking through the dataset viewer and I like it a lot. Version numbers, citation information, everything's there! I've spotted a few issues/bugs though: - the URL is still under `nlp`, perhaps an alias for `datasets` can be made - when I remove a feature (and the feature list is e...
https://github.com/huggingface/datasets/issues/888	Nested lists are zipped unexpectedly	Yes following the Tensorflow Datasets convention, objects with type `Sequence of a Dict` are actually stored as a `dictionary of lists`. See the [documentation](https://huggingface.co/docs/datasets/features.html?highlight=features) for more details	I might misunderstand something, but I expect that if I define: ```python "top": datasets.features.Sequence({ "middle": datasets.features.Sequence({ "bottom": datasets.Value("int32") }) }) ``` And I then create an example: ```python yield 1, { "top": [{ "middle": [ {"bottom": 1}, ...	27	Nested lists are zipped unexpectedly I might misunderstand something, but I expect that if I define: ```python "top": datasets.features.Sequence({ "middle": datasets.features.Sequence({ "bottom": datasets.Value("int32") }) }) ``` And I then create an example: ```python yield 1, { "top": [{ ...
https://github.com/huggingface/datasets/issues/888	Nested lists are zipped unexpectedly	Thanks. This is a bit (very) confusing, but I guess if its intended, I'll just work with it as if its how my data was originally structured :)	I might misunderstand something, but I expect that if I define: ```python "top": datasets.features.Sequence({ "middle": datasets.features.Sequence({ "bottom": datasets.Value("int32") }) }) ``` And I then create an example: ```python yield 1, { "top": [{ "middle": [ {"bottom": 1}, ...	28	Nested lists are zipped unexpectedly I might misunderstand something, but I expect that if I define: ```python "top": datasets.features.Sequence({ "middle": datasets.features.Sequence({ "bottom": datasets.Value("int32") }) }) ``` And I then create an example: ```python yield 1, { "top": [{ ...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Yes right now `ArrayXD` can only be used as a column feature type, not a subtype. With the current Arrow limitations I don't think we'll be able to make it work as a subtype, however it should be possible to allow dimensions of dynamic sizes (`Array3D(shape=(None, 137, 2), dtype="float32")` for example since the [unde...	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	85	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	> Yes right now ArrayXD can only be used as a column feature type, not a subtype. Meaning it can't be nested under `Sequence`? If so, for now I'll just make it a python list and make it with the nested `Sequence` type you suggested.	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	45	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Yea unfortunately.. That's a current limitation with Arrow ExtensionTypes that can't be used in the default Arrow Array objects. We already have an ExtensionArray that allows us to use them as column types but not for subtypes. Maybe we can extend it, I haven't experimented with that yet	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	48	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Cool So please consider this issue as a feature request for: ``` Array3D(shape=(None, 137, 2), dtype="float32") ``` its a way to represent videos, poses, and other cool sequences	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	28	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	@lhoestq well, so sequence of sequences doesn't work either... ``` pyarrow.lib.ArrowCapacityError: List array cannot contain more than 2147483646 child elements, have 2147483648 ```	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	23	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Working with Arrow can be quite fun sometimes. You can fix this issue by trying to reduce the writer batch size (same trick than the one used to reduce the RAM usage in https://github.com/huggingface/datasets/issues/741). Let me know if it works. I haven't investigated yet on https://github.com/huggingface/dataset...	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	67	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	The batch size fix doesn't work... not for #741 and not for this dataset I'm trying (DGS corpus) Loading the DGS corpus takes 400GB of RAM, which is fine with me as my machine is large enough	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	37	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Not yet, I've been pretty busy with the dataset sprint lately but this is something that's been asked several times already. So I'll definitely work on this as soon as I'm done with the sprint and with the RAM issue you reported.	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	42	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Hi @lhoestq, Any chance you have some updates on the supporting `ArrayXD` as a subtype or support of dynamic sized arrays? e.g.: `datasets.features.Sequence(datasets.features.Array2D(shape=(137, 2), dtype="float32"))` `Array3D(shape=(None, 137, 2), dtype="float32")`	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	29	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Hi ! We haven't worked in this lately and it's not in our very short-term roadmap since it requires a bit a work to make it work with arrow. Though this will definitely be added at one point.	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	38	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	@lhoestq, thanks for the update. I actually tried to modify some piece of code to make it work. Can you please tell if I missing anything here? I think that for vast majority of cases it's enough to make first dimension of the array dynamic i.e. `shape=(None, 100, 100)`. For that, it's enough to modify class [Array...	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	224	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/887	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type>	Thanks for diving into this ! Indeed focusing on making the first dimensions dynamic make total sense (and users could still re-order their dimensions to match this constraint). Your code looks great :) I think it can even be extended to support several dynamic dimensions if we want to. Feel free to open a PR to...	I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, # This defines the different columns of the dataset and ...	164	pyarrow.lib.ArrowNotImplementedError: MakeBuilder: cannot construct builder for type extension<arrow.py_extension_type> I set up a new dataset, with a sequence of arrays (really, I want to have an array of (None, 137, 2), and the first dimension is dynamic) ```python def _info(self): return datasets...
https://github.com/huggingface/datasets/issues/883	Downloading/caching only a part of a datasets' dataset.	I think it would be a very helpful feature, because sometimes one only wants to evaluate models on the dev set, and the whole training data may be many times bigger. This makes the task impossible with limited memory resources.	Hi, I want to use the validation data only (of natural question). I don't want to have the whole dataset cached in my machine, just the dev set. Is this possible? I can't find a way to do it in the docs. Thank you, Sapir	40	Downloading/caching only a part of a datasets' dataset. Hi, I want to use the validation data only (of natural question). I don't want to have the whole dataset cached in my machine, just the dev set. Is this possible? I can't find a way to do it in the docs. Thank you, Sapir I think it would be a very hel...
https://github.com/huggingface/datasets/issues/880	Add SQA	I’ll take this one to test the workflow for the sprint next week cc @yjernite @lhoestq	## Adding a Dataset - Name: SQA (Sequential Question Answering) by Microsoft. - Description: The SQA dataset was created to explore the task of answering sequences of inter-related questions on HTML tables. It has 6,066 sequences with 17,553 questions in total. - Paper: https://www.microsoft.com/en-us/r...	16	Add SQA ## Adding a Dataset - Name: SQA (Sequential Question Answering) by Microsoft. - Description: The SQA dataset was created to explore the task of answering sequences of inter-related questions on HTML tables. It has 6,066 sequences with 17,553 questions in total. - Paper: https://www.microsoft.c...
https://github.com/huggingface/datasets/issues/880	Add SQA	@thomwolf here's a slightly adapted version of the code from the [official Tapas repository](https://github.com/google-research/tapas/blob/master/tapas/utils/interaction_utils.py) that is used to turn the `answer_coordinates` and `answer_texts` columns into true Python lists of tuples/strings: ``` import pandas as ...	## Adding a Dataset - Name: SQA (Sequential Question Answering) by Microsoft. - Description: The SQA dataset was created to explore the task of answering sequences of inter-related questions on HTML tables. It has 6,066 sequences with 17,553 questions in total. - Paper: https://www.microsoft.com/en-us/r...	185	Add SQA ## Adding a Dataset - Name: SQA (Sequential Question Answering) by Microsoft. - Description: The SQA dataset was created to explore the task of answering sequences of inter-related questions on HTML tables. It has 6,066 sequences with 17,553 questions in total. - Paper: https://www.microsoft.c...
https://github.com/huggingface/datasets/issues/879	boolq does not load	Hi ! It runs on my side without issues. I tried ```python from datasets import load_dataset load_dataset("boolq") ``` What version of datasets and tensorflow are your runnning ? Also if you manage to get a minimal reproducible script (on google colab for example) that would be useful.	Hi I am getting these errors trying to load boolq thanks Traceback (most recent call last): File "test.py", line 5, in <module> data = AutoTask().get("boolq").get_dataset("train", n_obs=10) File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42, in get_dataset d...	47	boolq does not load Hi I am getting these errors trying to load boolq thanks Traceback (most recent call last): File "test.py", line 5, in <module> data = AutoTask().get("boolq").get_dataset("train", n_obs=10) File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42...
https://github.com/huggingface/datasets/issues/879	boolq does not load	hey i do the exact same commands. for me it fails i guess might be issues with caching maybe? thanks best rabeeh On Tue, Nov 24, 2020, 10:24 AM Quentin Lhoest <[email protected]> wrote: > Hi ! It runs on my side without issues. I tried > > from datasets import load_datasetload_dataset("boolq") > > What version...	Hi I am getting these errors trying to load boolq thanks Traceback (most recent call last): File "test.py", line 5, in <module> data = AutoTask().get("boolq").get_dataset("train", n_obs=10) File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42, in get_dataset d...	117	boolq does not load Hi I am getting these errors trying to load boolq thanks Traceback (most recent call last): File "test.py", line 5, in <module> data = AutoTask().get("boolq").get_dataset("train", n_obs=10) File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42...
https://github.com/huggingface/datasets/issues/879	boolq does not load	Could you check if it works on the master branch ? You can use `load_dataset("boolq", script_version="master")` to do so. We did some changes recently in boolq to remove the TF dependency and we changed the way the data files are downloaded in https://github.com/huggingface/datasets/pull/881	Hi I am getting these errors trying to load boolq thanks Traceback (most recent call last): File "test.py", line 5, in <module> data = AutoTask().get("boolq").get_dataset("train", n_obs=10) File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42, in get_dataset d...	43	boolq does not load Hi I am getting these errors trying to load boolq thanks Traceback (most recent call last): File "test.py", line 5, in <module> data = AutoTask().get("boolq").get_dataset("train", n_obs=10) File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	> neat feature I dint get these clearly, can you please elaborate like how to work on these	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	18	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	It could maybe work almost out of the box just by using `cached_path` in the text/csv/json scripts, no?	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	18	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	Thanks thomwolf and julien-c I'm still confusion on what you guys said, I have solved the problem as follows: 1. read the csv file using pandas from s3 2. Convert to dictionary key as column name and values as list column data 3. convert it to Dataset using `from datasets import Dataset` `train_dataset ...	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	55	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	We were brainstorming around your use-case. Let's keep the issue open for now, I think this is an interesting question to think about.	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	23	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	> We were brainstorming around your use-case. > > Let's keep the issue open for now, I think this is an interesting question to think about. Sure thomwolf, Thanks for your concern	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	32	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	I agree it would be cool to have that feature. Also that's good to know that pandas supports this. For the moment I'd suggest to first download the files locally as thom suggested and then load the dataset by providing paths to the local files	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	45	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...
https://github.com/huggingface/datasets/issues/878	Loading Data From S3 Path in Sagemaker	Any updates on this issue? I face a similar issue. I have many parquet files in S3 and I would like to train on them. To be honest I even face issues with only getting the last layer embedding out of them.	In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_files["train"] = train_path data_files...	42	Loading Data From S3 Path in Sagemaker In Sagemaker Im tring to load the data set from S3 path as follows `train_path = 's3://xxxxxxxxxx/xxxxxxxxxx/train.csv' valid_path = 's3://xxxxxxxxxx/xxxxxxxxxx/validation.csv' test_path = 's3://xxxxxxxxxx/xxxxxxxxxx/test.csv' data_files = {} data_fi...

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Dataset Summary in English

This customized dataset is made of a corpus of commun Github issues, typically utilized for tracking bugs or features within a repositories. This self-constructed corpus can serve multiple purposes, such as analyzing the time taken to resolve open issues or pull requests, training a classifier to tag issues based on their descriptions (e.g., "bug," "enhancement," "question"), or developing a semantic search engine for finding relevant issues based on user queries.

Résumé de l'ensemble de jeu de données en français

Ce jeu de données personnalisé est constitué d'un corpus de problèmes couramment rencontrés sur GitHub, généralement utilisés pour le suivi des bugs ou des fonctionnalités au sein des repositories. Ce corpus auto construit peut servir à de multiples fins, telles que l'analyse du temps nécessaire pour résoudre les problèmes ouverts ou les demandes d'extraction, l'entraînement d'un classificateur pour étiqueter les problèmes sur la base de leurs descriptions (par exemple, "bug", "amélioration", "question"), ou le développement d'un moteur de recherche sémantique pour trouver des problèmes pertinents sur la base des requêtes de l'utilisateur.