html_url stringlengths 51 51 | comments stringlengths 67 24.7k | title stringlengths 6 280 | body stringlengths 51 36.2k | comment_length int64 16 1.45k | text stringlengths 190 38.3k | embeddings list |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/2185 | So to answer my initial question, I was just doing something stupid as I was not re-giving the `preprocessing_num_workers` arguments when launching the distributed training (and it was then set to `None`). I initially thought the hash was computed only with the `tokenize_function` but it's all arguments. Thanks @lhoest... | .map() and distributed training | Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_path=my_path)
[...]
def tokeni... | 51 | .map() and distributed training
Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_pa... | [
-0.25376176834106445,
-0.22071696817874908,
0.11777669191360474,
0.07457458972930908,
0.21161656081676483,
-0.10975947976112366,
0.5170727372169495,
0.010205188766121864,
0.280156672000885,
0.023762941360473633,
0.1822473704814911,
0.34344932436943054,
-0.22906403243541718,
-0.585545003414... |
https://github.com/huggingface/datasets/issues/2185 | This cache process isn't really consistent. I just changed `per_device_train_batch_size` of training script and now it rebuilding the dataset cache!!!! Why? | .map() and distributed training | Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_path=my_path)
[...]
def tokeni... | 21 | .map() and distributed training
Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_pa... | [
-0.25376176834106445,
-0.22071696817874908,
0.11777669191360474,
0.07457458972930908,
0.21161656081676483,
-0.10975947976112366,
0.5170727372169495,
0.010205188766121864,
0.280156672000885,
0.023762941360473633,
0.1822473704814911,
0.34344932436943054,
-0.22906403243541718,
-0.585545003414... |
https://github.com/huggingface/datasets/issues/2185 | Hi ! A `map` function is recomputed if the code changes or if any of the variables it uses changes. Can you check that your function doesn't use `per_device_train_batch_size` or any variable that contains `per_device_train_batch_size` ? | .map() and distributed training | Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_path=my_path)
[...]
def tokeni... | 36 | .map() and distributed training
Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_pa... | [
-0.25376176834106445,
-0.22071696817874908,
0.11777669191360474,
0.07457458972930908,
0.21161656081676483,
-0.10975947976112366,
0.5170727372169495,
0.010205188766121864,
0.280156672000885,
0.023762941360473633,
0.1822473704814911,
0.34344932436943054,
-0.22906403243541718,
-0.585545003414... |
https://github.com/huggingface/datasets/issues/2185 | My code is actually a transformer's example for training t5, I modified a bit:
https://github.com/puraminy/transformers/blob/4b40877132eedb566043f83de8f1d29a84d71430/examples/flax/language-modeling/run_t5_mlm_flax.py#L614
No, it doesn't use `per_device_train_batch_size`. I remember it worked for several times and... | .map() and distributed training | Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_path=my_path)
[...]
def tokeni... | 94 | .map() and distributed training
Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_pa... | [
-0.25376176834106445,
-0.22071696817874908,
0.11777669191360474,
0.07457458972930908,
0.21161656081676483,
-0.10975947976112366,
0.5170727372169495,
0.010205188766121864,
0.280156672000885,
0.023762941360473633,
0.1822473704814911,
0.34344932436943054,
-0.22906403243541718,
-0.585545003414... |
https://github.com/huggingface/datasets/issues/2181 | Hi ! Can you try to increase the block size ? For example
```python
block_size_10MB = 10<<20
load_dataset("json", ..., block_size=block_size_10MB)
```
The block size corresponds to how much bytes to process at a time from the input stream.
This will determine multi-threading granularity as well as the size of ind... | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 64 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | Hi @lhoestq! Thank you for your prompt reply.
I have experimented with (10<<20, 10<<28, 10<<30, 10<<33, 10<<34), since my machine has 192G of memory, but it's either the above-mentioned error or processed killed because of OOM.
Could you give me a bit of background on why block size needs to be exactly calibrated?
... | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 66 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | We're using the JSON loader of pyarrow. It parses the file chunk by chunk to load the dataset.
This issue happens when there's no delimiter in one chunk of data. For json line, the delimiter is the end of line.
So with a big value for chunk_size this should have worked unless you have one extremely long line in your ... | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 95 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | I'm using `pyarrow==3.0.0` with `datasets==1.5.0`.
Your point totally makes sense. I will check if my jsonl file contains an extremely long file and let you know.
Here are some different error messages that I got when tweaking `block_size`. I also suspect that this is related to the pyarrow... but I guess it wou... | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 137 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | I am getting the same error. When I tweak the block_size, I also find:
`OverflowError: value too large to convert to int32_t`
and
`pyarrow.lib.ArrowInvalid: Exceeded maximum rows`
| Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 27 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | I made more tests. I used a smaller dataset and I was getting the same error, which means that it was not necessarily linked to the dataset size. To make both my smaller and larger datasets work, I got rid of lists with the json file. I had the following data format:
```python
[
{'key': "a", 'value': ['one', 'two'... | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 120 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | Thanks @hwijeen for reporting and thanks @jpilaul for pointing this out.
Indeed, those are different JSON-like formats:
- the first one is the **standard JSON** format: all the file content is JSON-valid, thus all content is either a JSON object (between curly brackets `{...}`) or a JSON array (between square brack... | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 104 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2181 | Thanks @albertvillanova for your explanation, it is helpful to know (maybe add to docs?)!
However, the problem I described above happened when I was dealing with jsonl files 😿
Although I did not thoroughly inspect, I suspect the cause was the one extremely long document in my case. | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | 48 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries)
Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as ... | [
0.016557134687900543,
0.012686491012573242,
-0.007510840892791748,
0.340938001871109,
0.16045337915420532,
-0.2647136151790619,
0.1936325877904892,
0.585946798324585,
-0.1621612310409546,
-0.08150680363178253,
0.165473073720932,
0.1441625952720642,
-0.015083150938153267,
0.0145618394017219... |
https://github.com/huggingface/datasets/issues/2176 | Hi @nelson-liu!
Here is what I do to convert a string to class label:
```python
from datasets import load_dataset, features
dset = load_dataset(...)
col_name = "the string column name"
class_names = dset.unique(col_name)
class_feature = features.ClassLabel(names=sorted(class_names))
dset = dset.map(lam... | Converting a Value to a ClassLabel | Hi!
In the docs for `cast`, it's noted that `For non-trivial conversion, e.g. string <-> ClassLabel you should use map() to update the Dataset.`
Would it be possible to have an example that demonstrates such a string <-> ClassLabel conversion using `map`? Thanks! | 50 | Converting a Value to a ClassLabel
Hi!
In the docs for `cast`, it's noted that `For non-trivial conversion, e.g. string <-> ClassLabel you should use map() to update the Dataset.`
Would it be possible to have an example that demonstrates such a string <-> ClassLabel conversion using `map`? Thanks!
Hi @nelson... | [
-0.025565512478351593,
-0.1936044991016388,
0.05003340542316437,
0.059382788836956024,
0.6273636817932129,
0.21152476966381073,
0.28297609090805054,
0.0898774266242981,
0.07599520683288574,
-0.0568673238158226,
0.10290469974279404,
0.6814893484115601,
-0.033919401466846466,
0.1158330217003... |
https://github.com/huggingface/datasets/issues/2176 | Hi! You can use `Dataset.class_encode_column` for this. And in the next release of `datasets` (this feature is only available on `master`), you'll also be able to use `cast` to do the conversion.
An example of conversion via `cast`:
```python
from datasets import Dataset, Features, ClassLabel
d = Dataset.from_d... | Converting a Value to a ClassLabel | Hi!
In the docs for `cast`, it's noted that `For non-trivial conversion, e.g. string <-> ClassLabel you should use map() to update the Dataset.`
Would it be possible to have an example that demonstrates such a string <-> ClassLabel conversion using `map`? Thanks! | 57 | Converting a Value to a ClassLabel
Hi!
In the docs for `cast`, it's noted that `For non-trivial conversion, e.g. string <-> ClassLabel you should use map() to update the Dataset.`
Would it be possible to have an example that demonstrates such a string <-> ClassLabel conversion using `map`? Thanks!
Hi! You ca... | [
-0.10248276591300964,
-0.013445153832435608,
0.05103107914328575,
0.030189117416739464,
0.5588472485542297,
0.22223274409770966,
0.3362889885902405,
0.14872369170188904,
0.0411529541015625,
0.03893574699759483,
0.09335137903690338,
0.755332887172699,
-0.06846639513969421,
0.213006064295768... |
https://github.com/huggingface/datasets/issues/2175 | Actually, I found the answer [here](https://github.com/facebookresearch/faiss/wiki/FAQ#what-does-it-mean-when-a-search-returns--1-ids).
So we have to do some modifications to the code for instances where the index doesn't retrieve any IDs. | dataset.search_batch() function outputs all -1 indices sometime. | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | 25 | dataset.search_batch() function outputs all -1 indices sometime.
I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingf... | [
0.011297456920146942,
-0.3721056878566742,
-0.10199876129627228,
0.019268635660409927,
0.2021874636411667,
-0.09668777883052826,
0.2803097367286682,
0.2968437671661377,
0.13914161920547485,
0.42091265320777893,
-0.23242929577827454,
-0.24345383048057556,
0.10583297908306122,
-0.03389798104... |
https://github.com/huggingface/datasets/issues/2175 | @lhoestq @patrickvonplaten
I also found another short bug in the retrieval part. Especially, when retrieving documents. If Faiss returns the -1 as the index, the retriever will always use the last element in the dataset.
please check [def get_doc_dicts function](https://github.com/huggingface/transformers/blo... | dataset.search_batch() function outputs all -1 indices sometime. | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | 52 | dataset.search_batch() function outputs all -1 indices sometime.
I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingf... | [
0.015852071344852448,
-0.28069156408309937,
-0.06329288333654404,
0.08496485650539398,
0.08535462617874146,
-0.10384604334831238,
0.2369082272052765,
0.3023102283477783,
0.10523360967636108,
0.34376060962677,
-0.25177356600761414,
-0.21534359455108643,
0.16499078273773193,
-0.2617834210395... |
https://github.com/huggingface/datasets/issues/2175 | Hi !
No it happens sometimes to return -1, especially if your dataset is small.
If your dataset is big enough it shouldn't happen in my experience.
Ideally we should ignore all the -1 that are returned. It should be possible to change that in RAG's code | dataset.search_batch() function outputs all -1 indices sometime. | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | 47 | dataset.search_batch() function outputs all -1 indices sometime.
I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingf... | [
-0.019722647964954376,
-0.4322834014892578,
-0.08124154806137085,
0.04783058166503906,
0.21979759633541107,
-0.09081800282001495,
0.31157323718070984,
0.2803555428981781,
0.13101203739643097,
0.4431150555610657,
-0.25051605701446533,
-0.15310955047607422,
0.09101849049329758,
-0.0791351646... |
https://github.com/huggingface/datasets/issues/2175 | I also checked with some indexes it returns more -1s. Specially with IVF
when nprobr is very low. It doesn't happen when using HNSW though. But at
the moment if it happens, dataset will always return the last element.
Maybe we should change it to repeat the most last valid retrieved doc id.
What do you think?
On Wed, ... | dataset.search_batch() function outputs all -1 indices sometime. | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | 150 | dataset.search_batch() function outputs all -1 indices sometime.
I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingf... | [
-0.03521934151649475,
-0.3799372613430023,
-0.047816477715969086,
0.042572420090436935,
0.15346068143844604,
-0.08229726552963257,
0.29746100306510925,
0.35949432849884033,
0.15454953908920288,
0.40005624294281006,
-0.2719641923904419,
-0.13553066551685333,
0.18018467724323273,
-0.11624775... |
https://github.com/huggingface/datasets/issues/2175 | That would be an easy way to workaround this issue. Feel free to open a PR on `transformers` and ping me ! :) | dataset.search_batch() function outputs all -1 indices sometime. | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | 23 | dataset.search_batch() function outputs all -1 indices sometime.
I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingf... | [
-0.02550823986530304,
-0.43428853154182434,
-0.06778895854949951,
0.07370935380458832,
0.2557210922241211,
-0.0868850126862526,
0.3684980273246765,
0.2831260859966278,
0.07728279381990433,
0.4528712034225464,
-0.2223183810710907,
-0.19843067228794098,
0.044837672263383865,
-0.0636604577302... |
https://github.com/huggingface/datasets/issues/2175 | Sure. Will push everything together with RAG end to end. :) thanks a lot.
On Wed, Apr 7, 2021, 21:16 Quentin Lhoest ***@***.***> wrote:
> That would be an easy way to workaround this issue. Feel free to open a PR
> on transformers and ping me ! :)
>
> —
> You are receiving this because you authored the thread.
> Rep... | dataset.search_batch() function outputs all -1 indices sometime. | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | 82 | dataset.search_batch() function outputs all -1 indices sometime.
I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingf... | [
-0.028313197195529938,
-0.4459782540798187,
-0.062118321657180786,
0.10841438174247742,
0.29210591316223145,
-0.07177896797657013,
0.3549715578556061,
0.30725154280662537,
0.09947578608989716,
0.4373636841773987,
-0.2883692979812622,
-0.1778714507818222,
0.04758746549487114,
-0.04054675251... |
https://github.com/huggingface/datasets/issues/2170 | It seems that this can be fixed from user's end by including a `date` argument, like this:
`dataset = datasets.load_dataset('wikipedia', '20200501.en', date='20210420')`
You can get available dates from [here](https://dumps.wikimedia.org/enwiki/).
This is not a proper fix however as all the files will still ha... | Wikipedia historic dumps are deleted but hf/datasets hardcodes dump date | Wikimedia does not keep all historical dumps. For example, as of today https://dumps.wikimedia.org/kowiki/ only provides
```
20201220/ 02-Feb-2021 01:36 -
20210101/ 21-Feb-2021 01:26 -
20210120/ ... | 48 | Wikipedia historic dumps are deleted but hf/datasets hardcodes dump date
Wikimedia does not keep all historical dumps. For example, as of today https://dumps.wikimedia.org/kowiki/ only provides
```
20201220/ 02-Feb-2021 01:36 -
20210101/ ... | [
-0.0480472594499588,
0.3399820327758789,
-0.02219211496412754,
0.03158023953437805,
-0.319379061460495,
0.15651266276836395,
0.3078281581401825,
0.5392643213272095,
0.17642201483249664,
0.1010853499174118,
-0.07535645365715027,
0.07239808142185211,
0.20245154201984406,
-0.2449927181005478,... |
https://github.com/huggingface/datasets/issues/2166 | Hi @vyraun ! The test references for CommonGen are not publicly available: you can reach out to the original dataset authors if you would like to ask for them, but we will not be releasing them as part of GEM (March 31st was the release date for the test set inputs, references are incidentally released for some of the ... | Regarding Test Sets for the GEM datasets | @yjernite Hi, are the test sets for the GEM datasets scheduled to be [added soon](https://gem-benchmark.com/shared_task)?
e.g.
```
from datasets import load_dataset
DATASET_NAME="common_gen"
data = load_dataset("gem", DATASET_NAME)
```
The test set doesn't have the target or references.
```
data['test... | 71 | Regarding Test Sets for the GEM datasets
@yjernite Hi, are the test sets for the GEM datasets scheduled to be [added soon](https://gem-benchmark.com/shared_task)?
e.g.
```
from datasets import load_dataset
DATASET_NAME="common_gen"
data = load_dataset("gem", DATASET_NAME)
```
The test set doesn't have t... | [
-0.3199136555194855,
-0.096124567091465,
-0.19731591641902924,
0.184435173869133,
-0.09196016192436218,
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0.28373169898986816,
0.39402616024017334,
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-0.01612532138824463,
0.1892586052417755,
0.2699717879295349,
-0.3344813287258148,
0.1294024437665939... |
https://github.com/huggingface/datasets/issues/2165 | Hi,
a HF dataset can be converted to a Torch Dataset with a simple wrapper as follows:
```python
from torch.utils.data import Dataset
class HFDataset(Dataset):
def __init__(self, dset):
self.dset = dset
def __getitem__(self, idx):
return self.dset[idx]
def __len__(self):
... | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 124 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.2578478157520294,
-0.265220582485199,
0.09229046106338501,
0.33822372555732727,
0.19224417209625244,
0.22271470725536346,
-0.030272886157035828,
0.3457019031047821,
-0.15135788917541504,
-0.1886630654335022,
-0.34864747524261475,
0.32489922642707825,
-0.19426943361759186,
-0.14205345511... |
https://github.com/huggingface/datasets/issues/2165 | Interesting ! Thanks for sharing this @mariosasko . I like the idea
This looks like something we should add IMO | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 20 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.2704313397407532,
-0.3552313446998596,
0.05783388763666153,
0.32740268111228943,
0.13080231845378876,
0.2287474125623703,
-0.07467102259397507,
0.3752877414226532,
-0.15198197960853577,
-0.24214082956314087,
-0.3885171413421631,
0.3905748724937439,
-0.24195587635040283,
0.01590691506862... |
https://github.com/huggingface/datasets/issues/2165 | @mariosasko
Thx for your code!
It perfectly works with a small modification for HF NLP dataset:
```
original_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds = HFDataset(train_ds['train']) # needs splitting
``` | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 28 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.22635605931282043,
-0.3335737884044647,
0.07031472772359848,
0.3271583914756775,
0.13317592442035675,
0.19714421033859253,
-0.06429543346166611,
0.373365193605423,
-0.1391187161207199,
-0.26625722646713257,
-0.3984829783439636,
0.3849843442440033,
-0.1794499009847641,
-0.009580746293067... |
https://github.com/huggingface/datasets/issues/2165 | @lhoestq Sadly, from Python 3.7 onwards `torch.utils.data.Dataset` doesn't support the virtual subclass mechanism due to `typing.Generic` type no longer having `abc.ABCMeta` as its metaclass.
With that in mind, another option is to remove a direct type check (`isinstance(dataset, torch.utils.data.Dataset)`) in `deep... | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 108 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.19205765426158905,
-0.2704026997089386,
0.09888152033090591,
0.32321783900260925,
0.2382788211107254,
0.18831759691238403,
-0.045659858733415604,
0.3633684515953064,
-0.1526026874780655,
-0.22917599976062775,
-0.2917281985282898,
0.39241936802864075,
-0.2503361105918884,
-0.153775274753... |
https://github.com/huggingface/datasets/issues/2165 | That makes sense ! Feel free to open an issue on their repo and discuss this idea | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 17 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.2620018422603607,
-0.30597782135009766,
0.04827328026294708,
0.33868923783302307,
0.11748895794153214,
0.22666683793067932,
-0.09718681871891022,
0.3648380935192108,
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-0.21851928532123566,
-0.34978699684143066,
0.3944832682609558,
-0.25215867161750793,
-0.0014386177... |
https://github.com/huggingface/datasets/issues/2165 | @y-rokutan Hi, now if you install `deepspeed` from master (this feature will be available in the next official release), the code should work without subclassing. Let us know if you still have any issues. | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 34 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.2635490596294403,
-0.3762310743331909,
0.0858725979924202,
0.3691847324371338,
0.18167556822299957,
0.3435538411140442,
-0.05182437598705292,
0.4010276794433594,
-0.1650426983833313,
-0.2584496736526489,
-0.35081374645233154,
0.32045674324035645,
-0.24456435441970825,
0.0142729654908180... |
https://github.com/huggingface/datasets/issues/2165 | Worth mentioning that any function that expects a `torch..Dataset` (like `torch..DataLoader`) will fail a mypy-esque typecheck if a `datasets.Dataset` is passed, even though it implements the interface correctly (I think). The virtual subclass idea was a good one- I wonder if there's another workaround given the Generi... | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | 96 | How to convert datasets.arrow_dataset.Dataset to torch.utils.data.Dataset
Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_a... | [
-0.2078215479850769,
-0.23314878344535828,
0.13846804201602936,
0.27257946133613586,
0.26682642102241516,
0.1537621021270752,
-0.003108251839876175,
0.324068158864975,
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-0.22039930522441864,
-0.35762113332748413,
0.3906596302986145,
-0.2636040151119232,
0.1052081957459... |
https://github.com/huggingface/datasets/issues/2162 | This looks like an issue with the cc100 dataset itself but not sure
Did you try loading cc100 on your machine ? | visualization for cc100 is broken | Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
| 22 | visualization for cc100 is broken
Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
This looks like an issue with the cc100 dataset itself but not sure
Did you try loading cc100 on your machine ? | [
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-0.20044399797916412,
-0.0850355252623558,
0.12931983172893524,
0.2095070779323578,
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0.16415388882160187,
0.1368134468793869,
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0.42319005727767944,
-0.05236532539129257,
0.23769980669021606,
0.1289268434047699,
0.4269976019859... |
https://github.com/huggingface/datasets/issues/2162 | Hi
loading works fine, but the viewer only is broken
thanks
On Wed, Apr 7, 2021 at 12:17 PM Quentin Lhoest ***@***.***>
wrote:
> This looks like an issue with the cc100 dataset itself but not sure
> Did you try loading cc100 on your machine ?
>
> —
> You are receiving this because you authored the thread.
> Reply to ... | visualization for cc100 is broken | Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
| 80 | visualization for cc100 is broken
Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
Hi
loading works fine, but the viewer only is broken
thanks
On Wed, Apr 7, 2021 at 12:17 PM Quentin Lhoest ***@***.***>
wrote:
> This looks like an issue with ... | [
-0.4892333745956421,
-0.257188081741333,
-0.01544002816081047,
0.16780707240104675,
0.22792302072048187,
0.036741748452186584,
0.14369556307792664,
0.0804586112499237,
-0.03847810626029968,
0.318007230758667,
-0.14256533980369568,
0.24562811851501465,
0.1419418752193451,
0.4538699686527252... |
https://github.com/huggingface/datasets/issues/2162 | Hi! This visualization tool is deprecated now. The viewer at https://huggingface.co/datasets/cc100 works fine, so I'm closing this issue. | visualization for cc100 is broken | Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
| 18 | visualization for cc100 is broken
Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
Hi! This visualization tool is deprecated now. The viewer at https://huggingface.co/datasets/cc100 works fine, so I'm closing this issue. | [
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0.07837793231010437,
0.380234897136688... |
https://github.com/huggingface/datasets/issues/2161 | oh, great, really awesome feature to have, thank you very much for the great, fabulous work | any possibility to download part of large datasets only? | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | 16 | any possibility to download part of large datasets only?
Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks
oh, great, really awesome feature to ha... | [
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0.36386546492... |
https://github.com/huggingface/datasets/issues/2161 | We'll work on dataset streaming soon. This should allow you to only load the examples you need ;) | any possibility to download part of large datasets only? | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | 18 | any possibility to download part of large datasets only?
Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks
We'll work on dataset streaming soon. T... | [
-0.4160081148147583,
-0.42279955744743347,
-0.09121212363243103,
0.2210889458656311,
0.11789171397686005,
0.2086140215396881,
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0.37463781237602234,
0.10753156244754791,
0.31373339891433716,
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-0.22648471593856812,
-0.09712019562721252,
0.36238446831... |
https://github.com/huggingface/datasets/issues/2161 | thanks a lot Quentin, this would be really really a great feature to have
On Wed, Apr 7, 2021 at 12:14 PM Quentin Lhoest ***@***.***>
wrote:
> We'll work on dataset streaming soon. This should allow you to only load
> the examples you need ;)
>
> —
> You are receiving this because you authored the thread.
> Reply to ... | any possibility to download part of large datasets only? | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | 79 | any possibility to download part of large datasets only?
Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks
thanks a lot Quentin, this would be rea... | [
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-0.09591162949800491,
0.45779180526733... |
https://github.com/huggingface/datasets/issues/2161 | Is streaming completed? On the 1.8.0 docs it is mentioned (https://huggingface.co/docs/datasets/dataset_streaming.html), but when following the example I get the following error:
```
>>> dataset2 = load_dataset("amazon_us_reviews", "Pet_Products_v1_00", split='train', streaming=True)
----------------------------... | any possibility to download part of large datasets only? | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | 123 | any possibility to download part of large datasets only?
Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks
Is streaming completed? On the 1.8.0 do... | [
-0.4476090967655182,
-0.38850757479667664,
0.009524676948785782,
0.3701239228248596,
0.10674449056386948,
0.19297009706497192,
-0.03403514623641968,
0.5148774981498718,
0.08198730647563934,
0.23246882855892181,
-0.4534539580345154,
-0.1990632712841034,
-0.17841632664203644,
0.4000228047370... |
https://github.com/huggingface/datasets/issues/2161 | Hi ! Streaming is available on `master` only right now. We'll make a new release 1.9.0 on Monday :) | any possibility to download part of large datasets only? | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | 19 | any possibility to download part of large datasets only?
Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks
Hi ! Streaming is available on `master`... | [
-0.4722629189491272,
-0.42555660009384155,
-0.11318694800138474,
0.1344197392463684,
0.08804640918970108,
0.1738647073507309,
-0.35428911447525024,
0.3757149577140808,
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0.32865628600120544,
-0.4129244089126587,
-0.22793138027191162,
-0.14858108758926392,
0.379370719194... |
https://github.com/huggingface/datasets/issues/2160 | Hi.
I cannot always reproduce this issue, and on later runs I did not see it so far. Sometimes also I set 8 processes but I see less being showed, is this normal, here only 5 are shown for 8 being set, thanks
```
#3: 11%|███████████████▊ ... | data_args.preprocessing_num_workers almost freezes | Hi @lhoestq
I am running this code from huggingface transformers https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py
to speed up tokenization, since I am running on multiple datasets, I am using data_args.preprocessing_num_workers = 4 with opus100 corpus but this moves ... | 71 | data_args.preprocessing_num_workers almost freezes
Hi @lhoestq
I am running this code from huggingface transformers https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py
to speed up tokenization, since I am running on multiple datasets, I am using data_args.preprocessi... | [
-0.2514107823371887,
-0.24791930615901947,
-0.16687631607055664,
0.06956711411476135,
0.12973305583000183,
-0.1807379573583603,
0.4334706664085388,
0.0990598201751709,
-0.3538163900375366,
0.244042307138443,
0.06387810409069061,
0.2399454414844513,
0.09411627054214478,
-0.13301880657672882... |
https://github.com/huggingface/datasets/issues/2158 | Thanks for reporting !
The viewer doesn't have all the dependencies of the datasets. We may add openpyxl to be able to show this dataset properly | viewer "fake_news_english" error | When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa: requires this pandas optional depe... | 26 | viewer "fake_news_english" error
When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa:... | [
-0.1493435651063919,
-0.18128108978271484,
0.033643342554569244,
0.34163257479667664,
0.2343088686466217,
0.286343514919281,
-0.015794996172189713,
0.22440749406814575,
0.16542795300483704,
0.07346713542938232,
-0.22257071733474731,
-0.12595105171203613,
-0.0306419488042593,
0.328609496355... |
https://github.com/huggingface/datasets/issues/2158 | This viewer tool is deprecated now and the new viewer at https://huggingface.co/datasets/fake_news_english works fine, so I'm closing this issue | viewer "fake_news_english" error | When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa: requires this pandas optional depe... | 19 | viewer "fake_news_english" error
When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa:... | [
-0.16355252265930176,
-0.12276989966630936,
0.05639158934354782,
0.27710992097854614,
0.24810928106307983,
0.2900732159614563,
0.029497873038053513,
0.24294915795326233,
0.13204830884933472,
0.10402482748031616,
-0.2412911057472229,
-0.1428900957107544,
0.035482048988342285,
0.299944579601... |
https://github.com/huggingface/datasets/issues/2153 | Nice question which helped me a lot! I have wasted a lot of time to the `DatasetDict` creation from a csv file. Hope the document of this module add some simple examples. | load_dataset ignoring features | First of all, I'm sorry if it is a repeated issue or the changes are already in master, I searched and I didn't find anything.
I'm using datasets 1.5.0
As you can see, when I load the dataset, the C... | 32 | load_dataset ignoring features
First of all, I'm sorry if it is a repeated issue or the changes are already in master, I searched and I didn't find anything.
I'm using datasets 1.5.0
As you can se... | [
-0.08561435341835022,
-0.030492186546325684,
0.012940295040607452,
0.2842152714729309,
0.4256819486618042,
0.25316500663757324,
0.6406396627426147,
-0.053947705775499344,
0.223464235663414,
0.05332423746585846,
0.15431979298591614,
0.3363249897956848,
-0.11442296206951141,
0.45993509888648... |
https://github.com/huggingface/datasets/issues/2148 | Hi @marrodion.
Thanks for pointing this out. It would be great to incorporate this metric-specific enhancement.
Another possibility would be to require the user to input the scheme as a string `mode="strict", scheme="IOB2"` and then dynamically import the corresponding module using Python `importlib`:
```python... | Add configurable options to `seqeval` metric | Right now `load_metric("seqeval")` only works in the default mode of evaluation (equivalent to conll evaluation).
However, seqeval library [supports](https://github.com/chakki-works/seqeval#support-features) different evaluation schemes (IOB1, IOB2, etc.), which can be plugged in just by supporting additional kwargs... | 61 | Add configurable options to `seqeval` metric
Right now `load_metric("seqeval")` only works in the default mode of evaluation (equivalent to conll evaluation).
However, seqeval library [supports](https://github.com/chakki-works/seqeval#support-features) different evaluation schemes (IOB1, IOB2, etc.), which can be ... | [
-0.44041430950164795,
0.1902090609073639,
-0.0845155119895935,
-0.1625579297542572,
0.07494725286960602,
-0.16458258032798767,
0.14902152121067047,
0.2498323619365692,
-0.08360826224088669,
0.3530941605567932,
-0.4670090079307556,
0.24865524470806122,
-0.032320279628038406,
0.2693849802017... |
https://github.com/huggingface/datasets/issues/2146 | Hi ! In the arrow file we store all the integers as uint8.
So your arrow file should weigh around `height x width x n_channels x n_images` bytes.
What feature type do your TFDS dataset have ?
If it uses a `tfds.features.Image` type, then what is stored is the encoded data (as png or jpg for example). Since these... | Dataset file size on disk is very large with 3D Array | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": ""... | 114 | Dataset file size on disk is very large with 3D Array
Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.j... | [
-0.14527370035648346,
-0.11326291412115097,
-0.15441793203353882,
0.4201558828353882,
0.21356363594532013,
0.11391296982765198,
0.5066811442375183,
0.2730788290500641,
0.020523034036159515,
0.035847704857587814,
-0.19370460510253906,
0.08741555362939835,
-0.16945859789848328,
0.31504392623... |
https://github.com/huggingface/datasets/issues/2146 | Thanks for the prompt response. You're right about the encoding, I have the `tfds.features.Image` feature type you mentioned.
However, as described in the `dataset_info.json`, my dataset is made of 1479 (224x224x3) images. 1479 x 224 x 224 x 3 = 222630912 bytes which is far from the actual size 520803408 bytes.
An... | Dataset file size on disk is very large with 3D Array | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": ""... | 62 | Dataset file size on disk is very large with 3D Array
Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.j... | [
-0.14527370035648346,
-0.11326291412115097,
-0.15441793203353882,
0.4201558828353882,
0.21356363594532013,
0.11391296982765198,
0.5066811442375183,
0.2730788290500641,
0.020523034036159515,
0.035847704857587814,
-0.19370460510253906,
0.08741555362939835,
-0.16945859789848328,
0.31504392623... |
https://github.com/huggingface/datasets/issues/2146 | @lhoestq I changed the data structure so I have a 2D Array feature type instead of a 3D Array by grouping the two last dimensions ( a 224x672 2D Array instead of a 224x224x3 3D Array). The file size is now 223973964 bytes, nearly half the previous size! Which is around of what I would expect.
I found similar behavio... | Dataset file size on disk is very large with 3D Array | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": ""... | 77 | Dataset file size on disk is very large with 3D Array
Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.j... | [
-0.14527370035648346,
-0.11326291412115097,
-0.15441793203353882,
0.4201558828353882,
0.21356363594532013,
0.11391296982765198,
0.5066811442375183,
0.2730788290500641,
0.020523034036159515,
0.035847704857587814,
-0.19370460510253906,
0.08741555362939835,
-0.16945859789848328,
0.31504392623... |
https://github.com/huggingface/datasets/issues/2146 | Interesting !
This may be because of the offsets that are stored with the array data.
Currently the offsets are stored even if the `shape` of the arrays is fixed. This was needed because of some issues with pyarrow a few months ago. I think these issues have been addressed now, so we can probably try to remove them... | Dataset file size on disk is very large with 3D Array | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": ""... | 80 | Dataset file size on disk is very large with 3D Array
Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.j... | [
-0.14527370035648346,
-0.11326291412115097,
-0.15441793203353882,
0.4201558828353882,
0.21356363594532013,
0.11391296982765198,
0.5066811442375183,
0.2730788290500641,
0.020523034036159515,
0.035847704857587814,
-0.19370460510253906,
0.08741555362939835,
-0.16945859789848328,
0.31504392623... |
https://github.com/huggingface/datasets/issues/2146 | Yeah for sure, can you be a bit more specific about where the offset is stored in the code base ? And any reference to pyarrow issues if you have some. I would be very interested in contributing to `datasets` by trying to fix this issue. | Dataset file size on disk is very large with 3D Array | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": ""... | 46 | Dataset file size on disk is very large with 3D Array
Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.j... | [
-0.14527370035648346,
-0.11326291412115097,
-0.15441793203353882,
0.4201558828353882,
0.21356363594532013,
0.11391296982765198,
0.5066811442375183,
0.2730788290500641,
0.020523034036159515,
0.035847704857587814,
-0.19370460510253906,
0.08741555362939835,
-0.16945859789848328,
0.31504392623... |
https://github.com/huggingface/datasets/issues/2146 | Pyarrow has two types of lists: variable length lists and fixed size lists.
Currently we store the ArrayXD data as variable length lists. They take more disk space because they must store both actual data and offsets.
In the `datasets` code this is done here:
https://github.com/huggingface/nlp/blob/dbac87c8a083f80... | Dataset file size on disk is very large with 3D Array | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": ""... | 75 | Dataset file size on disk is very large with 3D Array
Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.j... | [
-0.14527370035648346,
-0.11326291412115097,
-0.15441793203353882,
0.4201558828353882,
0.21356363594532013,
0.11391296982765198,
0.5066811442375183,
0.2730788290500641,
0.020523034036159515,
0.035847704857587814,
-0.19370460510253906,
0.08741555362939835,
-0.16945859789848328,
0.31504392623... |
https://github.com/huggingface/datasets/issues/2144 | That's how I loaded the dataset
```python
from datasets import load_dataset
ds = load_dataset('wikipedia', '20200501.en', cache_dir='/usr/local/workspace/NAS_NLP/cache')
``` | Loading wikipedia 20200501.en throws pyarrow related error | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | 17 | Loading wikipedia 20200501.en throws pyarrow related error
**Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, to... | [
-0.10415421426296234,
0.35264623165130615,
0.03405791521072388,
0.3633102476596832,
0.27457743883132935,
0.180207759141922,
0.2762240171432495,
0.4623250365257263,
-0.04348841309547424,
-0.11378446221351624,
0.024737529456615448,
0.23602193593978882,
0.1520678699016571,
-0.1178016588091850... |
https://github.com/huggingface/datasets/issues/2144 | Hi ! It looks like the arrow file in the folder
`/usr/local/workspace/NAS_NLP/cache/wikipedia/20200501.en/1.0.0/50aa706aa417bb77d910ad61211cc672c0ef3e0f224225a5e0a18277ade8b931` is corrupted.
Can you take a look and check that it's 18.3GB ?
If not, then maybe you need to redownload it:
```python
from datasets ... | Loading wikipedia 20200501.en throws pyarrow related error | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | 46 | Loading wikipedia 20200501.en throws pyarrow related error
**Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, to... | [
-0.10415421426296234,
0.35264623165130615,
0.03405791521072388,
0.3633102476596832,
0.27457743883132935,
0.180207759141922,
0.2762240171432495,
0.4623250365257263,
-0.04348841309547424,
-0.11378446221351624,
0.024737529456615448,
0.23602193593978882,
0.1520678699016571,
-0.1178016588091850... |
https://github.com/huggingface/datasets/issues/2144 | > Hi ! It looks like the arrow file in the folder
> `/usr/local/workspace/NAS_NLP/cache/wikipedia/20200501.en/1.0.0/50aa706aa417bb77d910ad61211cc672c0ef3e0f224225a5e0a18277ade8b931` is corrupted.
>
> Can you take a look and check that it's 18.3GB ?
>
> If not, then maybe you need to redownload it:
>
> ```pyth... | Loading wikipedia 20200501.en throws pyarrow related error | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | 113 | Loading wikipedia 20200501.en throws pyarrow related error
**Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, to... | [
-0.10415421426296234,
0.35264623165130615,
0.03405791521072388,
0.3633102476596832,
0.27457743883132935,
0.180207759141922,
0.2762240171432495,
0.4623250365257263,
-0.04348841309547424,
-0.11378446221351624,
0.024737529456615448,
0.23602193593978882,
0.1520678699016571,
-0.1178016588091850... |
https://github.com/huggingface/datasets/issues/2144 | I just tried on my side and got no issues.
When downloading the dataset again, did it crash at 10.7GB as well ? | Loading wikipedia 20200501.en throws pyarrow related error | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | 23 | Loading wikipedia 20200501.en throws pyarrow related error
**Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, to... | [
-0.10415421426296234,
0.35264623165130615,
0.03405791521072388,
0.3633102476596832,
0.27457743883132935,
0.180207759141922,
0.2762240171432495,
0.4623250365257263,
-0.04348841309547424,
-0.11378446221351624,
0.024737529456615448,
0.23602193593978882,
0.1520678699016571,
-0.1178016588091850... |
https://github.com/huggingface/datasets/issues/2144 | > I just tried on my side and got no issues.
> When downloading the dataset again, did it crash at 10.7GB as well ?
Yes i have tried it multiple times on different machines. I am wondering if you could share the screenshot of your dependency versions and i will try to make them the same as yours? | Loading wikipedia 20200501.en throws pyarrow related error | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | 59 | Loading wikipedia 20200501.en throws pyarrow related error
**Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, to... | [
-0.10415421426296234,
0.35264623165130615,
0.03405791521072388,
0.3633102476596832,
0.27457743883132935,
0.180207759141922,
0.2762240171432495,
0.4623250365257263,
-0.04348841309547424,
-0.11378446221351624,
0.024737529456615448,
0.23602193593978882,
0.1520678699016571,
-0.1178016588091850... |
https://github.com/huggingface/datasets/issues/2144 | I tried using `datasets` from `master` on macos with python 3.7.2
I also have `requests==2.23.0` and `tqdm==4.45.0`. | Loading wikipedia 20200501.en throws pyarrow related error | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | 17 | Loading wikipedia 20200501.en throws pyarrow related error
**Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, to... | [
-0.10415421426296234,
0.35264623165130615,
0.03405791521072388,
0.3633102476596832,
0.27457743883132935,
0.180207759141922,
0.2762240171432495,
0.4623250365257263,
-0.04348841309547424,
-0.11378446221351624,
0.024737529456615448,
0.23602193593978882,
0.1520678699016571,
-0.1178016588091850... |
https://github.com/huggingface/datasets/issues/2139 | Hi !
I think this has been fixed recently on `master`.
Can you try again by installing `datasets` from `master` ?
```
pip install git+https://github.com/huggingface/datasets.git
``` | TypeError when using save_to_disk in a dataset loaded with ReadInstruction split | Hi,
Loading a dataset with `load_dataset` using a split defined via `ReadInstruction` and then saving it to disk results in the following error: `TypeError: Object of type ReadInstruction is not JSON serializable`.
Here is the minimal reproducible example:
```python
from datasets import load_dataset
from dat... | 26 | TypeError when using save_to_disk in a dataset loaded with ReadInstruction split
Hi,
Loading a dataset with `load_dataset` using a split defined via `ReadInstruction` and then saving it to disk results in the following error: `TypeError: Object of type ReadInstruction is not JSON serializable`.
Here is the mini... | [
-0.13170656561851501,
0.21055968105793,
0.04380504786968231,
0.3900923728942871,
0.3082844913005829,
0.2542073726654053,
0.4115677773952484,
0.2183053195476532,
0.15596655011177063,
0.0927034467458725,
-0.18100298941135406,
0.38218191266059875,
-0.1831883192062378,
0.4692060947418213,
-0... |
https://github.com/huggingface/datasets/issues/2135 | Hi ! Indeed only the languages of the `translate-train` data are included...
I can't find a link to download the english train set on https://github.com/facebookresearch/MLQA though, do you know where we can download it ? | en language data from MLQA dataset is missing | Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue. | 35 | en language data from MLQA dataset is missing
Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue.
Hi ! Indeed only the languages of the `translate-train` data are included...
I can't find a link to ... | [
-0.0344623401761055,
0.20468354225158691,
-0.22718721628189087,
0.2308054268360138,
0.05782332643866539,
0.29979294538497925,
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0.1264658272266388,
0.19589266180992126,
-0.1498143970966339,
0.06739096343517303,
0.48139512538909... |
https://github.com/huggingface/datasets/issues/2135 | Hi @lhoestq
thank you very much for coming back to me, now I see, you are right, in the link you sent I see split of {split}-context-{context_language}-question-{question_language}.json with context_language=question_language=en, TFDS most probably has extracted english ones from these files as en language files, bu... | en language data from MLQA dataset is missing | Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue. | 57 | en language data from MLQA dataset is missing
Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue.
Hi @lhoestq
thank you very much for coming back to me, now I see, you are right, in the link you se... | [
-0.04081963747739792,
-0.0362207293510437,
-0.17737697064876556,
0.3228131830692291,
0.1323034167289734,
0.2861718535423279,
0.09528365731239319,
0.10732778161764145,
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0.11953598260879517,
0.09481590241193771,
0.051393039524555206,
0.16803935170173645,
0.52390271425247... |
https://github.com/huggingface/datasets/issues/2135 | I close the ticket, since I do not see any en existing, they have trained on "SQuAD V1.1" instead. Thanks. | en language data from MLQA dataset is missing | Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue. | 20 | en language data from MLQA dataset is missing
Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue.
I close the ticket, since I do not see any en existing, they have trained on "SQuAD V1.1" instead. Th... | [
-0.06140514090657234,
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-0.1854836791753769,
0.08395898342132568,
0.1434617042541504,
0.2676544487476349,
0.1858891248703003,
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0.14829465746879578,
0.22839897871017456,
0.19727559387683868,
0.1776249259710312,
0.3383446335792... |
https://github.com/huggingface/datasets/issues/2134 | Hi !
Indeed `save_to_disk` doesn't call pickle anymore. Though the `OverflowError` can still appear for in-memory datasets bigger than 4GB. This happens when doing this for example:
```python
import pyarrow as pa
import pickle
arr = pa.array([0] * ((4 * 8 << 30) // 64))
table = pa.Table.from_arrays([a], names=[... | Saving large in-memory datasets with save_to_disk crashes because of pickling | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | 134 | Saving large in-memory datasets with save_to_disk crashes because of pickling
Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively fa... | [
-0.31688857078552246,
0.09959536790847778,
0.11977994441986084,
0.3708880543708801,
0.25212326645851135,
0.0021296292543411255,
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0.46396830677986145,
0.19055691361427307,
0.09646549820899963,
0.08088315278291702,
0.5146647691726685,
-0.39890947937965393,
0.290598809719... |
https://github.com/huggingface/datasets/issues/2134 | Hi!
So I've managed to created a minimum working (well technically crashing) example for the multiprocessing case, I create a huge list of zeros, like in your example, and then I try to .map(None, num_proc=2) over it, which then crashes, here's the code:
```python
from datasets import Dataset
if __name__ == '_... | Saving large in-memory datasets with save_to_disk crashes because of pickling | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | 832 | Saving large in-memory datasets with save_to_disk crashes because of pickling
Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively fa... | [
-0.31688857078552246,
0.09959536790847778,
0.11977994441986084,
0.3708880543708801,
0.25212326645851135,
0.0021296292543411255,
-0.28349757194519043,
0.46396830677986145,
0.19055691361427307,
0.09646549820899963,
0.08088315278291702,
0.5146647691726685,
-0.39890947937965393,
0.290598809719... |
https://github.com/huggingface/datasets/issues/2134 | I just merged a fix #2150 that allows to pickle tables bigger than 4GiB
Feel free to try it on the `master` branch ! | Saving large in-memory datasets with save_to_disk crashes because of pickling | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | 24 | Saving large in-memory datasets with save_to_disk crashes because of pickling
Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively fa... | [
-0.31688857078552246,
0.09959536790847778,
0.11977994441986084,
0.3708880543708801,
0.25212326645851135,
0.0021296292543411255,
-0.28349757194519043,
0.46396830677986145,
0.19055691361427307,
0.09646549820899963,
0.08088315278291702,
0.5146647691726685,
-0.39890947937965393,
0.290598809719... |
https://github.com/huggingface/datasets/issues/2134 | awesome! I started getting this error as well when I tried to tokenize with a longer sequence length | Saving large in-memory datasets with save_to_disk crashes because of pickling | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | 18 | Saving large in-memory datasets with save_to_disk crashes because of pickling
Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively fa... | [
-0.31688857078552246,
0.09959536790847778,
0.11977994441986084,
0.3708880543708801,
0.25212326645851135,
0.0021296292543411255,
-0.28349757194519043,
0.46396830677986145,
0.19055691361427307,
0.09646549820899963,
0.08088315278291702,
0.5146647691726685,
-0.39890947937965393,
0.290598809719... |
https://github.com/huggingface/datasets/issues/2134 | @prokopCerny does this fix work for you? I found that with the latest master, my container with 500GB RAM starts crashing when I try to map a large dataset using `num_proc`.
@lhoestq would it be possible to implement some logic to keep the individual cache files small (say below 100mb)? I find this helps with loadin... | Saving large in-memory datasets with save_to_disk crashes because of pickling | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | 84 | Saving large in-memory datasets with save_to_disk crashes because of pickling
Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively fa... | [
-0.31688857078552246,
0.09959536790847778,
0.11977994441986084,
0.3708880543708801,
0.25212326645851135,
0.0021296292543411255,
-0.28349757194519043,
0.46396830677986145,
0.19055691361427307,
0.09646549820899963,
0.08088315278291702,
0.5146647691726685,
-0.39890947937965393,
0.290598809719... |
https://github.com/huggingface/datasets/issues/2134 | Closing since the original issue was fixed in #2150
Feel free to reopen if you are still experiencing it.
For the other problems, please open separate issues | Saving large in-memory datasets with save_to_disk crashes because of pickling | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | 27 | Saving large in-memory datasets with save_to_disk crashes because of pickling
Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively fa... | [
-0.31688857078552246,
0.09959536790847778,
0.11977994441986084,
0.3708880543708801,
0.25212326645851135,
0.0021296292543411255,
-0.28349757194519043,
0.46396830677986145,
0.19055691361427307,
0.09646549820899963,
0.08088315278291702,
0.5146647691726685,
-0.39890947937965393,
0.290598809719... |
https://github.com/huggingface/datasets/issues/2133 | If you print those questions, you get readable texts:
```python
>>> questions = [
... "\u0645\u062a\u0649 \u0628\u062f\u0627\u062a \u0627\u0644\u0645\u062c\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 \u0641\u064a \u0646\u0648\u062a\u0631\u062f\u0627\u0645 \u0628\u0627\u0644\u0646\u0634\u0631?",
... | bug in mlqa dataset | Hi
Looking into MLQA dataset for langauge "ar":
```
"question": [
"\u0645\u062a\u0649 \u0628\u062f\u0627\u062a \u0627\u0644\u0645\u062c\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 \u0641\u064a \u0646\u0648\u062a\u0631\u062f\u0627\u0645 \u0628\u0627\u0644\u0646\u0634\u0631?",
"\u0643\u0... | 111 | bug in mlqa dataset
Hi
Looking into MLQA dataset for langauge "ar":
```
"question": [
"\u0645\u062a\u0649 \u0628\u062f\u0627\u062a \u0627\u0644\u0645\u062c\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 \u0641\u064a \u0646\u0648\u062a\u0631\u062f\u0627\u0645 \u0628\u0627\u0644\u0646\u0634\u... | [
-0.11585284769535065,
-0.23156818747520447,
-0.2734040319919586,
0.21121220290660858,
0.3321489989757538,
0.07119500637054443,
0.35246899724006653,
0.12133811414241791,
-0.32277214527130127,
0.22545401751995087,
0.06188713014125824,
0.2817643880844116,
0.25186243653297424,
0.25612089037895... |
https://github.com/huggingface/datasets/issues/2133 | Hi @dorost1234.
In Python 3, strings are sequences of Unicode _code points_. Unicode is a specification that maps all characters (and emoji symbols) with its unique representation in terms of code points. That is what you see: Unicode code points (represented by a \u escaped sequence of 16-bit hex values).
Charac... | bug in mlqa dataset | Hi
Looking into MLQA dataset for langauge "ar":
```
"question": [
"\u0645\u062a\u0649 \u0628\u062f\u0627\u062a \u0627\u0644\u0645\u062c\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 \u0641\u064a \u0646\u0648\u062a\u0631\u062f\u0627\u0645 \u0628\u0627\u0644\u0646\u0634\u0631?",
"\u0643\u0... | 121 | bug in mlqa dataset
Hi
Looking into MLQA dataset for langauge "ar":
```
"question": [
"\u0645\u062a\u0649 \u0628\u062f\u0627\u062a \u0627\u0644\u0645\u062c\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 \u0641\u064a \u0646\u0648\u062a\u0631\u062f\u0627\u0645 \u0628\u0627\u0644\u0646\u0634\u... | [
-0.11585284769535065,
-0.23156818747520447,
-0.2734040319919586,
0.21121220290660858,
0.3321489989757538,
0.07119500637054443,
0.35246899724006653,
0.12133811414241791,
-0.32277214527130127,
0.22545401751995087,
0.06188713014125824,
0.2817643880844116,
0.25186243653297424,
0.25612089037895... |
https://github.com/huggingface/datasets/issues/2132 | You can filter the languages this way:
```python
tydiqa_en = tydiqa_dataset.filter(lambda x: x["language"] == "english")
```
Otherwise maybe we can have one configuration per language ?
What do you think of this for example ?
```python
load_dataset("tydiqa", "primary_task.en")
``` | TydiQA dataset is mixed and is not split per language | Hi @lhoestq
Currently TydiQA is mixed and user can only access the whole training set of all languages:
https://www.tensorflow.org/datasets/catalog/tydi_qa
for using this dataset, one need to train/evaluate in each separate language, and having them mixed, makes it hard to use this dataset. This is much convenien... | 39 | TydiQA dataset is mixed and is not split per language
Hi @lhoestq
Currently TydiQA is mixed and user can only access the whole training set of all languages:
https://www.tensorflow.org/datasets/catalog/tydi_qa
for using this dataset, one need to train/evaluate in each separate language, and having them mixed, ... | [
-0.2592064440250397,
-0.23528867959976196,
-0.2044115662574768,
0.26654568314552307,
0.2771569490432739,
-0.025829121470451355,
0.34125906229019165,
0.3332076072692871,
-0.15149827301502228,
0.07768166810274124,
-0.3343154788017273,
-0.046271685510873795,
-0.016753308475017548,
0.421419411... |
https://github.com/huggingface/datasets/issues/2132 | Hi
thank you very much for the great response, this will be really wonderful
to have one configuration per language, as one need the dataset in majority
of case per language for cross-lingual evaluations.
This becomes also then more close to TFDS format, which is separated per
language https://www.tensorflow.org/datase... | TydiQA dataset is mixed and is not split per language | Hi @lhoestq
Currently TydiQA is mixed and user can only access the whole training set of all languages:
https://www.tensorflow.org/datasets/catalog/tydi_qa
for using this dataset, one need to train/evaluate in each separate language, and having them mixed, makes it hard to use this dataset. This is much convenien... | 145 | TydiQA dataset is mixed and is not split per language
Hi @lhoestq
Currently TydiQA is mixed and user can only access the whole training set of all languages:
https://www.tensorflow.org/datasets/catalog/tydi_qa
for using this dataset, one need to train/evaluate in each separate language, and having them mixed, ... | [
-0.3552144765853882,
-0.23230423033237457,
-0.18655997514724731,
0.24706220626831055,
0.30515509843826294,
-0.0820615217089653,
0.38258427381515503,
0.3362084627151489,
-0.1914513260126114,
0.13157783448696136,
-0.46057143807411194,
-0.0628385841846466,
0.06377007067203522,
0.4531883597373... |
https://github.com/huggingface/datasets/issues/2131 | Hi ! Thanks for reporting
I was able to reproduce this issue. This was caused by missing split infos if a worker reloads the cache of the other worker.
I just opened https://github.com/huggingface/datasets/pull/2137 to fix this issue | When training with Multi-Node Multi-GPU the worker 2 has TypeError: 'NoneType' object | version: 1.5.0
met a very strange error, I am training large scale language model, and need train on 2 machines(workers).
And sometimes I will get this error `TypeError: 'NoneType' object is not iterable`
This is traceback
```
71 | | Traceback (most recent call last):
-- | -- | --
72 | | File "run_gpt.py"... | 37 | When training with Multi-Node Multi-GPU the worker 2 has TypeError: 'NoneType' object
version: 1.5.0
met a very strange error, I am training large scale language model, and need train on 2 machines(workers).
And sometimes I will get this error `TypeError: 'NoneType' object is not iterable`
This is traceback
```
... | [
-0.18060989677906036,
-0.44680917263031006,
0.01292361319065094,
0.549514651298523,
0.11248518526554108,
-0.00913412868976593,
0.5815144777297974,
0.29670143127441406,
0.11292458325624466,
0.23671123385429382,
0.33802881836891174,
0.01737622544169426,
-0.11621546745300293,
0.16757316887378... |
https://github.com/huggingface/datasets/issues/2130 | Here please find TFDS format of this dataset: https://www.tensorflow.org/datasets/catalog/wikiann
where there is a span column, this is really necessary to be able to use the data, and I appreciate your help @lhoestq | wikiann dataset is missing columns | Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq | 32 | wikiann dataset is missing columns
Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq
Here please find TFDS format of this dataset: https://www.tensorflow.org/d... | [
0.0038929209113121033,
-0.43879351019859314,
-0.09474526345729828,
0.2763385772705078,
0.31972891092300415,
0.18333914875984192,
0.3208167850971222,
0.08076183497905731,
0.053126491606235504,
0.2570089101791382,
0.010992992669343948,
-0.2380870282649994,
0.07031045854091644,
0.420583039522... |
https://github.com/huggingface/datasets/issues/2130 | Hi !
Apparently you can get the spans from the NER tags using `tags_to_spans` defined here:
https://github.com/tensorflow/datasets/blob/c7096bd38e86ed240b8b2c11ecab9893715a7d55/tensorflow_datasets/text/wikiann/wikiann.py#L81-L126
It would be nice to include the `spans` field in this dataset as in TFDS. This coul... | wikiann dataset is missing columns | Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq | 61 | wikiann dataset is missing columns
Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq
Hi !
Apparently you can get the spans from the NER tags using `tags_to_sp... | [
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https://github.com/huggingface/datasets/issues/2130 | Hi @lhoestq
thank you very much for the help, it would be very nice to have it included, here is the full code, one need to also convert tags to string first:
```
import datasets
from datasets import load_dataset
def tags_to_spans(tags):
"""Convert tags to spans."""
spans = set()
span_start = 0
s... | wikiann dataset is missing columns | Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq | 402 | wikiann dataset is missing columns
Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq
Hi @lhoestq
thank you very much for the help, it would be very nice to h... | [
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https://github.com/huggingface/datasets/issues/2130 | Cool ! Let me give you some context:
#### Contribution guide
You can find the contribution guide here:
https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md
It explains how to set up your dev environment in a few steps.
#### Dataset loading
Each Dataset is defined by a Table that have ma... | wikiann dataset is missing columns | Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq | 208 | wikiann dataset is missing columns
Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq
Cool ! Let me give you some context:
#### Contribution guide
You can... | [
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https://github.com/huggingface/datasets/issues/2129 | Hi !
We're not using `TextDatasetForNextSentencePrediction` in `datasets`.
Although you can probably use the `TextDatasetForNextSentencePrediction.create_examples_from_document` on a dataset to prepare it for next sentence prediction. | How to train BERT model with next sentence prediction? | Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
| 25 | How to train BERT model with next sentence prediction?
Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
Hi !
We're not using `TextDatasetForNex... | [
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0.049372486770153046,
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0.06175394... |
https://github.com/huggingface/datasets/issues/2129 | Thanks.
Do you mean that `TextDatasetForNextSentencePrediction.create_exapmles_from_document` can be applied to dataset object other than `TextDatasetForNextSentencePrediction` e.g. a `Dataset` object which is loaded by `datasets.load_dataset`? | How to train BERT model with next sentence prediction? | Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
| 24 | How to train BERT model with next sentence prediction?
Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
Thanks.
Do you mean that `TextDataset... | [
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https://github.com/huggingface/datasets/issues/2129 | It would probably require a bit of tweaking, but you can apply it to a dataset, yes.
This should give you a new dataset with sentence pairs you can train a model on.
You can find the documentation about dataset processing here:
https://huggingface.co/docs/datasets/processing.html#processing-data-with-map | How to train BERT model with next sentence prediction? | Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
| 43 | How to train BERT model with next sentence prediction?
Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
It would probably require a bit of tweak... | [
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0.173675343... |
https://github.com/huggingface/datasets/issues/2128 | Hi
Good catch ! Thanks for reporting
If you are interested in contributing, feel free to open a PR to fix this :) | Dialogue action slot name and value are reversed in MultiWoZ 2.2 | Hi @yjernite, thank you for adding MultiWoZ 2.2 in the huggingface datasets platform. It is beneficial!
I spot an error that the order of Dialogue action slot names and values are reversed.
https://github.com/huggingface/datasets/blob/649b2c469779bc4221e1b6969aa2496d63eb5953/datasets/multi_woz_v22/multi_woz_v22.p... | 23 | Dialogue action slot name and value are reversed in MultiWoZ 2.2
Hi @yjernite, thank you for adding MultiWoZ 2.2 in the huggingface datasets platform. It is beneficial!
I spot an error that the order of Dialogue action slot names and values are reversed.
https://github.com/huggingface/datasets/blob/649b2c469779... | [
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https://github.com/huggingface/datasets/issues/2123 | Hi,
sadly I can't replicate the problem on my Windows machine. Try to update the library to the newest version with:
```bash
pip install git+https://github.com/huggingface/datasets
``` | Problem downloading GEM wiki_auto_asset_turk dataset | @yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_dataset
#dataset = load_dataset('gem', 'web_nlg_en')
d... | 26 | Problem downloading GEM wiki_auto_asset_turk dataset
@yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_d... | [
-0.081687793135643,
-0.028080090880393982,
-0.046475812792778015,
0.4495638608932495,
0.28069621324539185,
0.11595873534679413,
0.3161948323249817,
0.17786088585853577,
0.24703970551490784,
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0.17666411399841309,
0.17229768633842468,
0.11423475295305252,
-0.003352977335... |
https://github.com/huggingface/datasets/issues/2123 | Is there an error message ?
What stacktrace do you get if you interrupt the execution of the program while downloading ? | Problem downloading GEM wiki_auto_asset_turk dataset | @yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_dataset
#dataset = load_dataset('gem', 'web_nlg_en')
d... | 22 | Problem downloading GEM wiki_auto_asset_turk dataset
@yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_d... | [
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0.01423916220664978,
-0.08156000077724457,
0.43999430537223816,
0.2992449104785919,
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0.37947332859039307,
0.14778798818588257,
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0.2344706654548645,
0.14406706392765045,
0.10741294920444489,
-0.02187690511345... |
https://github.com/huggingface/datasets/issues/2123 | Sorry for the long time since my last comment, I tried again and don't seem to have the problem anymore, thanks for your support! | Problem downloading GEM wiki_auto_asset_turk dataset | @yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_dataset
#dataset = load_dataset('gem', 'web_nlg_en')
d... | 24 | Problem downloading GEM wiki_auto_asset_turk dataset
@yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_d... | [
-0.06903538107872009,
-0.009997949004173279,
-0.07155099511146545,
0.4162677228450775,
0.2822790741920471,
0.12228898704051971,
0.3851534128189087,
0.21341703832149506,
0.23347051441669464,
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0.24285061657428741,
0.16283458471298218,
0.1382036805152893,
-0.0105032771825... |
https://github.com/huggingface/datasets/issues/2123 | Great ! I'm closing the issue then. Feel free to re-open if you experience this issue again | Problem downloading GEM wiki_auto_asset_turk dataset | @yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_dataset
#dataset = load_dataset('gem', 'web_nlg_en')
d... | 17 | Problem downloading GEM wiki_auto_asset_turk dataset
@yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_d... | [
-0.06359098851680756,
0.005495920777320862,
-0.0699881762266159,
0.3975270092487335,
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0.40512004494667053,
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https://github.com/huggingface/datasets/issues/2116 | Hi,
the `_data` attribute is missing due to `MyDataset.__init__` not calling the parent `__init__`. However, I don't think it's a good idea to subclass the `datasets.Dataset` class (e.g. it's kind of dangerous to override `datasets.Dataset.__getitem__`). Instead, it's better to follow the "association over inheritan... | Creating custom dataset results in error while calling the map() function | calling `map()` of `datasets` library results into an error while defining a Custom dataset.
Reproducible example:
```
import datasets
class MyDataset(datasets.Dataset):
def __init__(self, sentences):
"Initialization"
self.samples = sentences
def __len__(self):
"Denotes the ... | 75 | Creating custom dataset results in error while calling the map() function
calling `map()` of `datasets` library results into an error while defining a Custom dataset.
Reproducible example:
```
import datasets
class MyDataset(datasets.Dataset):
def __init__(self, sentences):
"Initialization"
... | [
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https://github.com/huggingface/datasets/issues/2106 | Hi ! Thanks for reporting
By looking at the raw `news-commentary-v14.en-kk.tsv` file, it looks like there are at least 17 lines with this issue.
Moreover these issues are not always the same:
- L97 is only `kk` text and must be appended at the end of the `kk` text of the **next** line
- L2897 is only `kk` text an... | WMT19 Dataset for Kazakh-English is not formatted correctly | In addition to the bug of languages being switched from Issue @415, there are incorrect translations in the dataset because the English-Kazakh translations have a one off formatting error.
The News Commentary v14 parallel data set for kk-en from http://www.statmt.org/wmt19/translation-task.html has a bug here:
> ... | 144 | WMT19 Dataset for Kazakh-English is not formatted correctly
In addition to the bug of languages being switched from Issue @415, there are incorrect translations in the dataset because the English-Kazakh translations have a one off formatting error.
The News Commentary v14 parallel data set for kk-en from http://ww... | [
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0.52284198999404... |
https://github.com/huggingface/datasets/issues/2105 | Hello @kyleclo! Currently, we are getting the data from your bucket, so if you remove it the HF script won't work anymore :)
Until you solve things on your end, @lhoestq suggested we just return a warning message when people try to load that dataset from HF. What would you like it to say? | Request to remove S2ORC dataset | Hi! I was wondering if it's possible to remove [S2ORC](https://huggingface.co/datasets/s2orc) from hosting on Huggingface's platform? Unfortunately, there are some legal considerations about how we make this data available. Happy to add back to Huggingface's platform once we work out those hurdles! Thanks! | 54 | Request to remove S2ORC dataset
Hi! I was wondering if it's possible to remove [S2ORC](https://huggingface.co/datasets/s2orc) from hosting on Huggingface's platform? Unfortunately, there are some legal considerations about how we make this data available. Happy to add back to Huggingface's platform once we work ou... | [
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0.367079138... |
https://github.com/huggingface/datasets/issues/2105 | Hi @kyleclo, as of today, you have not removed your bucket data yet, and therefore HuggingFace can download it from there.
Is it OK? Are you planning to eventually delete it? Thank you. | Request to remove S2ORC dataset | Hi! I was wondering if it's possible to remove [S2ORC](https://huggingface.co/datasets/s2orc) from hosting on Huggingface's platform? Unfortunately, there are some legal considerations about how we make this data available. Happy to add back to Huggingface's platform once we work out those hurdles! Thanks! | 33 | Request to remove S2ORC dataset
Hi! I was wondering if it's possible to remove [S2ORC](https://huggingface.co/datasets/s2orc) from hosting on Huggingface's platform? Unfortunately, there are some legal considerations about how we make this data available. Happy to add back to Huggingface's platform once we work ou... | [
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0.30720466... |
https://github.com/huggingface/datasets/issues/2105 | Hi! Sorry I missed @yjernite 's previous message, thanks for responding!
Is there an option where we can keep our data in our bucket, but the HF script no longer pulls data from it? | Request to remove S2ORC dataset | Hi! I was wondering if it's possible to remove [S2ORC](https://huggingface.co/datasets/s2orc) from hosting on Huggingface's platform? Unfortunately, there are some legal considerations about how we make this data available. Happy to add back to Huggingface's platform once we work out those hurdles! Thanks! | 34 | Request to remove S2ORC dataset
Hi! I was wondering if it's possible to remove [S2ORC](https://huggingface.co/datasets/s2orc) from hosting on Huggingface's platform? Unfortunately, there are some legal considerations about how we make this data available. Happy to add back to Huggingface's platform once we work ou... | [
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0.45722690224... |
https://github.com/huggingface/datasets/issues/2104 | Hi ! `wiki_movies` was added in `datasets==1.2.0`. However it looks like you have `datasets==1.1.2`.
To use `wiki_movies`, please update `datasets` with
```
pip install --upgrade datasets
``` | Trouble loading wiki_movies | Hello,
I am trying to load_dataset("wiki_movies") and it gives me this error -
`FileNotFoundError: Couldn't find file locally at wiki_movies/wiki_movies.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/wiki_movies/wiki_movies.py or https://s3.amazonaws.com/datasets.huggingfa... | 27 | Trouble loading wiki_movies
Hello,
I am trying to load_dataset("wiki_movies") and it gives me this error -
`FileNotFoundError: Couldn't find file locally at wiki_movies/wiki_movies.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/wiki_movies/wiki_movies.py or https://s3.am... | [
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0.28917625546455383,
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0.1652410477399826,
0.29042527079582214,
0.16233518719673157,
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0.03987026959657669,
0.03908208757638931,
0.00956938415... |
https://github.com/huggingface/datasets/issues/2104 | Thanks a lot! That solved it and I was able to upload a model trained on it as well :) | Trouble loading wiki_movies | Hello,
I am trying to load_dataset("wiki_movies") and it gives me this error -
`FileNotFoundError: Couldn't find file locally at wiki_movies/wiki_movies.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/wiki_movies/wiki_movies.py or https://s3.amazonaws.com/datasets.huggingfa... | 20 | Trouble loading wiki_movies
Hello,
I am trying to load_dataset("wiki_movies") and it gives me this error -
`FileNotFoundError: Couldn't find file locally at wiki_movies/wiki_movies.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/wiki_movies/wiki_movies.py or https://s3.am... | [
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0.007302682846784592,
0.40262937545776367,
0.32103368639945984,
0.20782625675201416,
0.24287956953048706,
0.2546977400779724,
0.15914638340473175,
-0.12933996319770813,
-0.08096623420715332,
-0.06365779787302017,
-0.017483439296483994,
0.03714574... |
https://github.com/huggingface/datasets/issues/2103 | Thanks for reporting :)
Maybe we can concatenate fields only if they are different.
Currently this is done here:
https://github.com/huggingface/nlp/blob/349ac4398a3bcae6356f14c5754483383a60e8a4/src/datasets/info.py#L180-L196
This can be a good first contribution to the library.
Please comment if you'd like t... | citation, homepage, and license fields of `dataset_info.json` are duplicated many times | This happens after a `map` operation when `num_proc` is set to `>1`. I tested this by cleaning up the json before running the `map` op on the dataset so it's unlikely it's coming from an earlier concatenation.
Example result:
```
"citation": "@ONLINE {wikidump,\n author = {Wikimedia Foundation},\n title = {... | 43 | citation, homepage, and license fields of `dataset_info.json` are duplicated many times
This happens after a `map` operation when `num_proc` is set to `>1`. I tested this by cleaning up the json before running the `map` op on the dataset so it's unlikely it's coming from an earlier concatenation.
Example result:
... | [
0.1381230354309082,
0.013645857572555542,
-0.06308336555957794,
0.3942776918411255,
-0.00548089575022459,
0.07270902395248413,
0.22892561554908752,
0.3846517503261566,
-0.06935514509677887,
0.04314134269952774,
0.07733903080224991,
0.6607300639152527,
0.48346051573753357,
-0.11136777698993... |
https://github.com/huggingface/datasets/issues/2099 | Hi !
Can you share more information about the features of your dataset ? You can get them by printing `my_dataset.features`
Can you also share the code of your `map` function ? | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 32 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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https://github.com/huggingface/datasets/issues/2099 | It is actually just the tokenized `wikipedia` dataset with `input_ids`, `attention_mask`, etc, with one extra column which is a list of integers. The `text` column is removed during tokenization.
```
def add_len_and_seq(example):
end_idx = example['input_ids'].index(SEP)
example['actual_len'] = end_idx-1
... | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 51 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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https://github.com/huggingface/datasets/issues/2099 | Is `PAD_ID` a python integer ? You need all the integers in `example['seq']` to have the same type.
Does this work if you remove the `np.uint8` and use python integers instead ? | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 32 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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... |
https://github.com/huggingface/datasets/issues/2099 | yup I casted it to `np.uint8` outside the function where it was defined. It was originally using python integers. | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 19 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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https://github.com/huggingface/datasets/issues/2099 | Strangely, even when I manually created `np.arrays` of specific `dtypes`, the types in the final `dataset_info.json` that gets written are still `int64`.
Update: I tried creating lists of `int8`s and got the same result. | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 34 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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https://github.com/huggingface/datasets/issues/2099 | Yes this is a known issue: #625
We're working on making the precision kept for numpy :)
To specify the precision of the integers, currently one needs to specify the output features with `.map(..., features=output_features)` | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 35 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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https://github.com/huggingface/datasets/issues/2099 | Do you know what step is taking forever in the code ?
What happens if you interrupt the execution of the dataset loading ? | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 24 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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-0.0854378268122673,
... |
https://github.com/huggingface/datasets/issues/2099 | After a synchronous discussion, we found that the cache file sizes have an enormous effect on the loading speed: smaller cache files result in faster load times. `num_proc` controls the number of cache files that are being written and is inversely proportional to the individual file size. In other words, increase `num_... | load_from_disk takes a long time to load local dataset | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helpin... | 66 | load_from_disk takes a long time to load local dataset
I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.u... | [
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https://github.com/huggingface/datasets/issues/2096 | Hello. I've been looking for information about German Conll2003 and found your question. Official site (https://www.clips.uantwerpen.be/conll2003/ner/) mentions that organizers provide only annotation. German texts (ECI Multilingual Text Corpus) are not freely available and can be ordered from the Linguistic Data Conso... | CoNLL 2003 dataset not including German | Hello, thanks for all the work on developing and maintaining this amazing platform, which I am enjoying working with!
I was wondering if there is a reason why the German CoNLL 2003 dataset is not included in the [repository](https://github.com/huggingface/datasets/tree/master/datasets/conll2003), since a copy of it ... | 48 | CoNLL 2003 dataset not including German
Hello, thanks for all the work on developing and maintaining this amazing platform, which I am enjoying working with!
I was wondering if there is a reason why the German CoNLL 2003 dataset is not included in the [repository](https://github.com/huggingface/datasets/tree/maste... | [
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https://github.com/huggingface/datasets/issues/2092 | Hi ! We plan to add streaming features in the future.
This should allow to load a dataset instantaneously without generating the arrow table. The trade-off is that accessing examples from a streaming dataset must be done in an iterative way, and with an additional (but hopefully minor) overhead.
What do you think a... | How to disable making arrow tables in load_dataset ? | Is there a way to disable the construction of arrow tables, or to make them on the fly as the dataset is being used ? | 84 | How to disable making arrow tables in load_dataset ?
Is there a way to disable the construction of arrow tables, or to make them on the fly as the dataset is being used ?
Hi ! We plan to add streaming features in the future.
This should allow to load a dataset instantaneously without generating the arrow table. ... | [
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https://github.com/huggingface/datasets/issues/2092 | People mainly want this feature either because it takes too much time too make arrow tables, or they occupy too much memory on the disk. I think both the problem can be solved if we provide arrow tables themselves on datasets hub. Can we do this currently @lhoestq ?
| How to disable making arrow tables in load_dataset ? | Is there a way to disable the construction of arrow tables, or to make them on the fly as the dataset is being used ? | 49 | How to disable making arrow tables in load_dataset ?
Is there a way to disable the construction of arrow tables, or to make them on the fly as the dataset is being used ?
People mainly want this feature either because it takes too much time too make arrow tables, or they occupy too much memory on the disk. I think ... | [
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