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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 <notifications@github.com>
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... |
https://github.com/huggingface/datasets/issues/878 | Loading Data From S3 Path in Sagemaker | Hi dorlavie,
You can find one solution that i have mentioned above, that can help you.
And there is one more solution also which is downloading files locally
| 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... | 28 | 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 | > Hi dorlavie,
> You can find one solution that i have mentioned above, that can help you.
> And there is one more solution also which is downloading files locally
mahesh1amour, thanks for the fast reply
Unfortunately, in my case I can not read with pandas. The dataset is too big (50GB).
In addition, due to s... | 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... | 68 | 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 | @dorlavie could use `boto3` to download the data to your local machine and then load it with `dataset`
boto3 example [documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/s3-example-download-file.html)
```python
import boto3
s3 = boto3.client('s3')
s3.download_file('BUCKET_NAME', 'OBJEC... | 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... | 46 | 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 @philschmid for the suggestion.
As I mentioned in the previous comment, due to security issues I can not save the data locally.
I need to read it from S3 and process it directly.
I guess that many other people try to train / fit those models on huge datasets (e.g entire Wiki), what is the best practice in t... | 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... | 61 | 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 | If I understand correctly you're not allowed to write data on disk that you downloaded from S3 for example ?
Or is it the use of the `boto3` library that is not allowed in your case ? | 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... | 37 | 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 | @lhoestq yes you are correct.
I am not allowed to save the "raw text" locally - The "raw text" must be saved only on S3.
I am allowed to save the output of any model locally.
It doesn't matter how I do it boto3/pandas/pyarrow, it is forbidden | 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... | 47 | 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 | @dorlavie are you using sagemaker for training too? Then you could use S3 URI, for example `s3://my-bucket/my-training-data` and pass it within the `.fit()` function when you start the sagemaker training job. Sagemaker would then download the data from s3 into the training runtime and you could load it from disk
**s... | 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... | 127 | 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/877 | DataLoader(datasets) become more and more slowly within iterations | Hi ! Thanks for reporting.
Do you have the same slowdown when you iterate through the raw dataset object as well ? (no dataloader)
It would be nice to know whether it comes from the dataloader or not | Hello, when I for loop my dataloader, the loading speed is becoming more and more slowly!
```
dataset = load_from_disk(dataset_path) # around 21,000,000 lines
lineloader = tqdm(DataLoader(dataset, batch_size=1))
for idx, line in enumerate(lineloader):
# do some thing for each line
```
In the begining, th... | 38 | DataLoader(datasets) become more and more slowly within iterations
Hello, when I for loop my dataloader, the loading speed is becoming more and more slowly!
```
dataset = load_from_disk(dataset_path) # around 21,000,000 lines
lineloader = tqdm(DataLoader(dataset, batch_size=1))
for idx, line in enumerate(linel... |
https://github.com/huggingface/datasets/issues/877 | DataLoader(datasets) become more and more slowly within iterations | > Hi ! Thanks for reporting.
> Do you have the same slowdown when you iterate through the raw dataset object as well ? (no dataloader)
> It would be nice to know whether it comes from the dataloader or not
I did not iter data from raw dataset, maybe I will test later. Now I iter all files directly from `open(file)... | Hello, when I for loop my dataloader, the loading speed is becoming more and more slowly!
```
dataset = load_from_disk(dataset_path) # around 21,000,000 lines
lineloader = tqdm(DataLoader(dataset, batch_size=1))
for idx, line in enumerate(lineloader):
# do some thing for each line
```
In the begining, th... | 64 | DataLoader(datasets) become more and more slowly within iterations
Hello, when I for loop my dataloader, the loading speed is becoming more and more slowly!
```
dataset = load_from_disk(dataset_path) # around 21,000,000 lines
lineloader = tqdm(DataLoader(dataset, batch_size=1))
for idx, line in enumerate(linel... |
https://github.com/huggingface/datasets/issues/876 | imdb dataset cannot be loaded | It looks like there was an issue while building the imdb dataset.
Could you provide more information about your OS and the version of python and `datasets` ?
Also could you try again with
```python
dataset = datasets.load_dataset("imdb", split="train", download_mode="force_redownload")
```
to make sure it's no... | Hi
I am trying to load the imdb train dataset
`dataset = datasets.load_dataset("imdb", split="train")`
getting following errors, thanks for your help
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/... | 51 | imdb dataset cannot be loaded
Hi
I am trying to load the imdb train dataset
`dataset = datasets.load_dataset("imdb", split="train")`
getting following errors, thanks for your help
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anacond... |
https://github.com/huggingface/datasets/issues/876 | imdb dataset cannot be loaded | Hi ! I just tried in 1.8.0 and it worked fine. Can you try again ? Maybe the dataset host had some issues that are fixed now | Hi
I am trying to load the imdb train dataset
`dataset = datasets.load_dataset("imdb", split="train")`
getting following errors, thanks for your help
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/... | 27 | imdb dataset cannot be loaded
Hi
I am trying to load the imdb train dataset
`dataset = datasets.load_dataset("imdb", split="train")`
getting following errors, thanks for your help
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anacond... |
https://github.com/huggingface/datasets/issues/873 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error | I see the issue happening again today -
[nltk_data] Downloading package stopwords to /root/nltk_data...
[nltk_data] Package stopwords is already up-to-date!
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/.... | ```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (most recent call last)
<ipython-input-6-2e06a8332652> in <module>()
... | 108 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error
```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (mo... |
https://github.com/huggingface/datasets/issues/873 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error | > atal("Unsupported publisher: %s", publisher) --> 134 files = sorted(os.listdir(top_dir)) 135 136 ret_files = []
>
> NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'
>
> Can someone please ta... | ```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (most recent call last)
<ipython-input-6-2e06a8332652> in <module>()
... | 199 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error
```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (mo... |
https://github.com/huggingface/datasets/issues/873 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error | experience the same problem, ccdv/cnn_dailymail not working either.
Solve this problem by installing datasets library from the master branch:
python -m pip install git+https://github.com/huggingface/datasets.git@master | ```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (most recent call last)
<ipython-input-6-2e06a8332652> in <module>()
... | 24 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error
```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (mo... |
https://github.com/huggingface/datasets/issues/873 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error | > > atal("Unsupported publisher: %s", publisher) --> 134 files = sorted(os.listdir(top_dir)) 135 136 ret_files = []
> > NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'
> > Can someone please take... | ```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (most recent call last)
<ipython-input-6-2e06a8332652> in <module>()
... | 228 | load_dataset('cnn_dalymail', '3.0.0') gives a 'Not a directory' error
```
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0')
```
Stack trace:
```
---------------------------------------------------------------------------
NotADirectoryError Traceback (mo... |
https://github.com/huggingface/datasets/issues/871 | terminate called after throwing an instance of 'google::protobuf::FatalException' | Loading the iwslt2017-en-nl config of iwslt2017 works fine on my side.
Maybe you can open an issue on transformers as well ? And also add more details about your environment (OS, python version, version of transformers and datasets etc.) | Hi
I am using the dataset "iwslt2017-en-nl", and after downloading it I am getting this error when trying to evaluate it on T5-base with seq2seq_trainer.py in the huggingface repo could you assist me please? thanks
100%|█████████████████████████████████████████████████████████████████████████████████████████████... | 39 | terminate called after throwing an instance of 'google::protobuf::FatalException'
Hi
I am using the dataset "iwslt2017-en-nl", and after downloading it I am getting this error when trying to evaluate it on T5-base with seq2seq_trainer.py in the huggingface repo could you assist me please? thanks
100%|█████████... |
https://github.com/huggingface/datasets/issues/871 | terminate called after throwing an instance of 'google::protobuf::FatalException' | closing now, figured out this is because the max length of decoder was set smaller than the input_dimensions. thanks | Hi
I am using the dataset "iwslt2017-en-nl", and after downloading it I am getting this error when trying to evaluate it on T5-base with seq2seq_trainer.py in the huggingface repo could you assist me please? thanks
100%|█████████████████████████████████████████████████████████████████████████████████████████████... | 19 | terminate called after throwing an instance of 'google::protobuf::FatalException'
Hi
I am using the dataset "iwslt2017-en-nl", and after downloading it I am getting this error when trying to evaluate it on T5-base with seq2seq_trainer.py in the huggingface repo could you assist me please? thanks
100%|█████████... |
https://github.com/huggingface/datasets/issues/870 | [Feature Request] Add optional parameter in text loading script to preserve linebreaks | Hi ! Thanks for your message.
Indeed it's a free feature we can add and that can be useful.
If you want to contribute, feel free to open a PR to add it to the text dataset script :) | I'm working on a project about rhyming verse using phonetic poetry and song lyrics, and line breaks are a vital part of the data.
I recently switched over to use the datasets library when my various corpora grew larger than my computer's memory. And so far, it is SO great.
But the first time I processed all of ... | 39 | [Feature Request] Add optional parameter in text loading script to preserve linebreaks
I'm working on a project about rhyming verse using phonetic poetry and song lyrics, and line breaks are a vital part of the data.
I recently switched over to use the datasets library when my various corpora grew larger than my ... |
https://github.com/huggingface/datasets/issues/866 | OSCAR from Inria group | PR is already open here : #348
The only thing remaining is to compute the metadata of each subdataset (one per language + shuffled/unshuffled).
As soon as #863 is merged we can start computing them. This will take a bit of time though | ## Adding a Dataset
- **Name:** *OSCAR* (Open Super-large Crawled ALMAnaCH coRpus), multilingual parsing of Common Crawl (separate crawls for many different languages), [here](https://oscar-corpus.com/).
- **Description:** *OSCAR or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by la... | 43 | OSCAR from Inria group
## Adding a Dataset
- **Name:** *OSCAR* (Open Super-large Crawled ALMAnaCH coRpus), multilingual parsing of Common Crawl (separate crawls for many different languages), [here](https://oscar-corpus.com/).
- **Description:** *OSCAR or Open Super-large Crawled ALMAnaCH coRpus is a huge multiling... |
https://github.com/huggingface/datasets/issues/865 | Have Trouble importing `datasets` | I'm sorry, this was a problem with my environment.
Now that I have identified the cause of environmental dependency, I would like to fix it and try it.
Excuse me for making a noise. | I'm failing to import transformers (v4.0.0-dev), and tracing the cause seems to be failing to import datasets.
I cloned the newest version of datasets (master branch), and do `pip install -e .`.
Then, `import datasets` causes the error below.
```
~/workspace/Clone/datasets/src/datasets/utils/file_utils.py in ... | 34 | Have Trouble importing `datasets`
I'm failing to import transformers (v4.0.0-dev), and tracing the cause seems to be failing to import datasets.
I cloned the newest version of datasets (master branch), and do `pip install -e .`.
Then, `import datasets` causes the error below.
```
~/workspace/Clone/datasets/... |
https://github.com/huggingface/datasets/issues/864 | Unable to download cnn_dailymail dataset | Same here! My kaggle notebook stopped working like yesterday. It's strange because I have fixed version of datasets==1.1.2 | ### Script to reproduce the error
```
from datasets import load_dataset
train_dataset = load_dataset("cnn_dailymail", "3.0.0", split= 'train[:10%')
valid_dataset = load_dataset("cnn_dailymail","3.0.0", split="validation[:5%]")
```
### Error
```
-------------------------------------------------------------... | 18 | Unable to download cnn_dailymail dataset
### Script to reproduce the error
```
from datasets import load_dataset
train_dataset = load_dataset("cnn_dailymail", "3.0.0", split= 'train[:10%')
valid_dataset = load_dataset("cnn_dailymail","3.0.0", split="validation[:5%]")
```
### Error
```
------------------... |
https://github.com/huggingface/datasets/issues/864 | Unable to download cnn_dailymail dataset | I couldn't reproduce unfortunately. I tried
```python
from datasets import load_dataset
load_dataset("cnn_dailymail", "3.0.0", download_mode="force_redownload")
```
and it worked fine on both my env (python 3.7.2) and colab (python 3.6.9)
Maybe there was an issue with the google drive download link of the dat... | ### Script to reproduce the error
```
from datasets import load_dataset
train_dataset = load_dataset("cnn_dailymail", "3.0.0", split= 'train[:10%')
valid_dataset = load_dataset("cnn_dailymail","3.0.0", split="validation[:5%]")
```
### Error
```
-------------------------------------------------------------... | 66 | Unable to download cnn_dailymail dataset
### Script to reproduce the error
```
from datasets import load_dataset
train_dataset = load_dataset("cnn_dailymail", "3.0.0", split= 'train[:10%')
valid_dataset = load_dataset("cnn_dailymail","3.0.0", split="validation[:5%]")
```
### Error
```
------------------... |
https://github.com/huggingface/datasets/issues/864 | Unable to download cnn_dailymail dataset | No, It's working fine now. Very strange. Here are my python and request versions
requests 2.24.0
Python 3.8.2 | ### Script to reproduce the error
```
from datasets import load_dataset
train_dataset = load_dataset("cnn_dailymail", "3.0.0", split= 'train[:10%')
valid_dataset = load_dataset("cnn_dailymail","3.0.0", split="validation[:5%]")
```
### Error
```
-------------------------------------------------------------... | 18 | Unable to download cnn_dailymail dataset
### Script to reproduce the error
```
from datasets import load_dataset
train_dataset = load_dataset("cnn_dailymail", "3.0.0", split= 'train[:10%')
valid_dataset = load_dataset("cnn_dailymail","3.0.0", split="validation[:5%]")
```
### Error
```
------------------... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | The preprocessing tokenizes the input text. Tokenization outputs `input_ids`, `attention_mask`, `token_type_ids` and `special_tokens_mask`. All those are of length`max_seq_length` because of padding. Therefore for each sample it generate 4 *`max_seq_length` integers. Currently they're all saved as int64. This is why th... | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 58 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | First I think we should disable padding in the dataset processing and let the data collator do it.
Then I'm wondering if you need attention_mask and token_type_ids at this point ?
Finally we can also specify the output feature types at this line https://github.com/huggingface/transformers/blob/master/examples/lan... | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 90 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | > First I think we should disable padding in the dataset processing and let the data collator do it.
No, you can't do that on TPUs as dynamic shapes will result in a very slow training. The script can however be tweaked to use the `PaddingDataCollator` with a fixed max length instead of dynamic batching.
For the ... | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 91 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | Oh yes right..
Do you think that a lazy map feature on the `datasets` side could help to avoid storing padded tokenized texts then ? | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 25 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | I think I can do the tweak mentioned above with the data collator as short fix (but fully focused on v4 right now so that will be for later this week, beginning of next week :-) ).
If it doesn't hurt performance to tokenize on the fly, that would clearly be the long-term solution however! | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 55 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | > Hey guys,
>
> I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small ... | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 273 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/861 | Possible Bug: Small training/dataset file creates gigantic output | Hi @NebelAI, we have optimized Datasets' disk usage in the latest release v1.5.
Feel free to update your Datasets version
```shell
pip install -U datasets
```
and see if it better suits your needs. | Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py). It was supposed to be a first test with a small 5 GB r... | 34 | Possible Bug: Small training/dataset file creates gigantic output
Hey guys,
I was trying to create a new bert model from scratch via _huggingface transformers + tokenizers + dataets_ (actually using this example script by your team: https://github.com/huggingface/transformers/blob/master/examples/language-modeling... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | Hi,I also posted it to the forum, but this is a bug, perhaps it needs to be reported here? thanks | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 20 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | It looks like the official OPUS server for WMT16 doesn't provide the data files anymore (503 error).
I searched a bit and couldn't find a mirror except maybe http://nlp.ffzg.hr/resources/corpora/setimes/ (the data are a cleaned version of the original ones though)
Should we consider replacing the old urls with these ... | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 59 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | The data storage is down at the moment. Sorry. Hopefully, it will come back soon. Apologies for the inconvenience ... | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 20 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | Dear great huggingface team, this is not working yet, I really appreciate some temporary fix on this, I need this for my project and this is time sensitive and I will be grateful for your help on this. | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 38 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | We have reached out to the OPUS team which is currently working on making the data available again. Cc @jorgtied | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 20 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | Hi, this is still down, I would be really grateful if you could ping them one more time. thank you so much. | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 22 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | Hi
I am trying with multiple setting of wmt datasets and all failed so far, I need to have at least one dataset working for testing somecodes, and this is really time sensitive, I greatly appreciate letting me know of one translation datasets currently working. thanks | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 46 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/854 | wmt16 does not download | It is still down, unfortunately. I'm sorry for that. It should come up again later today or tomorrow at the latest if no additional complications will happen. | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/... | 27 | wmt16 does not download
Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, tot... |
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | Unfortunately `concatenate_datasets` only supports concatenating the rows, while what you want to achieve is concatenate the columns.
Currently to add more columns to a dataset, one must use `map`.
What you can do is somehting like this:
```python
# suppose you have datasets d1, d2, d3
def add_columns(example, ind... | I want to achieve the following result
| 58 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
Unfortunately `concatenate_datasets` only supports concatenating the rows, while what you want to achieve is concatenate... |
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | That's not really difficult to add, though, no?
I think it can be done without copy.
Maybe let's add it to the roadmap? | I want to achieve the following result
| 23 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
That's not really difficult to add, though, no?
I think it can be done without copy.
Maybe let's add it to the roadmap... |
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | Actually it's doable but requires to update the `Dataset._data_files` schema to support this.
I'm re-opening this since we may want to add this in the future | I want to achieve the following result
| 26 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
Actually it's doable but requires to update the `Dataset._data_files` schema to support this.
I'm re-opening this since... |
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | Hi @lhoestq, I would love to help and add this feature if still needed. My plan is to add an axis variable in the `concatenate_datasets` function in `arrow_dataset.py` and when that is set to 1 concatenate columns instead of rows. | I want to achieve the following result
| 40 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
Hi @lhoestq, I would love to help and add this feature if still needed. My plan is to add an axis variable in the `conca... |
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | Hi ! I would love to see this feature implemented as well :) Thank you for proposing your help !
Here is a few things about the current implementation:
- A dataset object is a wrapper of one `pyarrow.Table` that contains the data
- Pyarrow offers an API that allows to transform Table objects. For example there are... | I want to achieve the following result
| 230 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
Hi ! I would love to see this feature implemented as well :) Thank you for proposing your help !
Here is a few things... |
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