noamaanMulla-03/transformers-issues huggingface dataset:
[Doc] explaining romanian postprocessing for MBART BLEU hacking
Author: sshleifer
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=h1) Report
> Merging [#5943](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ccbf74a685ae24bd1a0ba1325e4e9a9d62bbb2fa&el=desc) will **decrease** coverage by `0.00%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5943/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5943      +/-   ##
==========================================
- Coverage   77.31%   77.31%   -0.01%     
==========================================
  Files         146      146              
  Lines       26214    26214              
==========================================
- Hits        20268    20267       -1     
- Misses       5946     5947       +1     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5943/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `81.19% <0.00%> (-0.30%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=footer). Last update [ccbf74a...163ba92](https://codecov.io/gh/huggingface/transformers/pull/5943?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


@sshleifer just a quick comment on this, from here: https://github.com/pytorch/fairseq/issues/1758#issuecomment-625214318

for EN to RO, there is no point of maximising BLEU by removing diacritics when in real world (WMT human evaluation + SMT Matrix) it is clearly compared with a reference which HAS diacritics. But lot of papers do not do the things right.

That makes sense @vince62s! This is mostly so I can have a link to paste into a github issue when people ask me why their BLEU score is 27 :)
seq2seq: checkpoint callback seems messed up
Author: sshleifer
Pull request: no
Labels: name: Help wanted

![image](https://user-images.githubusercontent.com/6045025/88097457-2967e980-cb66-11ea-85fb-9ea4ae1101e8.png)

^^ lightning checkpoint saved much later than `best_tfmr`

Comments:
wrong thats just the directory. contents make more sense.
[examples/seq2seq]: add --label_smoothing option
Author: sshleifer
Pull request: yes

cc @patil-suraj 
This seems to improve BLEU score by ~2pts!
- also adds --early_stopping_patience command line arg
- fixes MBartDataset src,tgt flipping bug
- adds `--early_stopping_patience` command line arg for PL.
- wandb now looks for shell variable `$WANDB_PROJECT_NAME`

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=h1) Report
> Merging [#5919](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4781afd045b4722e7f28347f1c4f42a56a4550e8&el=desc) will **decrease** coverage by `0.17%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5919/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5919      +/-   ##
==========================================
- Coverage   78.69%   78.51%   -0.18%     
==========================================
  Files         146      146              
  Lines       26214    26214              
==========================================
- Hits        20628    20581      -47     
- Misses       5586     5633      +47     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.02% <0.00%> (-69.52%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.21% <0.00%> (-0.26%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5919/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.79% <0.00%> (+33.89%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=footer). Last update [4781afd...303f0ac](https://codecov.io/gh/huggingface/transformers/pull/5919?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Gunna merge this.
The packed dataset is definitely a win, label smoothing less clear.
TODO: figure out loss function mystery.
seq2seq/run_eval.py can take decoder_start_token_id
Author: sshleifer
Pull request: yes

Also: batch_decode: document kwargs for autocomplete

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=h1) Report
> Merging [#5949](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/95d1962b9c8460b4cec5a88eb9915e8e25f5bc1e&el=desc) will **decrease** coverage by `0.17%`.
> The diff coverage is `50.00%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5949/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5949      +/-   ##
==========================================
- Coverage   78.69%   78.51%   -0.18%     
==========================================
  Files         146      146              
  Lines       26214    26214              
==========================================
- Hits        20628    20581      -47     
- Misses       5586     5633      +47     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/tokenization\_utils\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5949/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.60% <50.00%> (ø)` | |
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5949/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.02% <0.00%> (-69.52%)` | :arrow_down: |
| [src/transformers/generation\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5949/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.82% <0.00%> (-0.29%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5949/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.79% <0.00%> (+33.89%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=footer). Last update [95d1962...450d753](https://codecov.io/gh/huggingface/transformers/pull/5949?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
[CI] self-scheduled runner tests examples/
Author: sshleifer
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=h1) Report
> Merging [#5927](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/4781afd045b4722e7f28347f1c4f42a56a4550e8&el=desc) will **decrease** coverage by `0.09%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5927/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5927      +/-   ##
==========================================
- Coverage   78.69%   78.59%   -0.10%     
==========================================
  Files         146      146              
  Lines       26214    26214              
==========================================
- Hits        20628    20603      -25     
- Misses       5586     5611      +25     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5927/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.02% <0.00%> (-69.52%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5927/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.42% <0.00%> (-29.91%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5927/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `85.96% <0.00%> (-0.51%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5927/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.79% <0.00%> (+33.89%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5927/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `93.36% <0.00%> (+49.37%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=footer). Last update [4781afd...a25be30](https://codecov.io/gh/huggingface/transformers/pull/5927?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Gunna merge this and make sure that it runs!
[CI] Install examples/requirements.txt
Author: sshleifer
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=h1) Report
> Merging [#5956](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/e714412fe6b38346a1f73525b701e030857b2f21&el=desc) will **increase** coverage by `0.01%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5956/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5956      +/-   ##
==========================================
+ Coverage   78.50%   78.51%   +0.01%     
==========================================
  Files         146      146              
  Lines       26214    26214              
==========================================
+ Hits        20578    20581       +3     
+ Misses       5636     5633       -3     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/generation\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5956/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.82% <0.00%> (-0.29%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5956/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.21% <0.00%> (+1.00%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=footer). Last update [e714412...ca424ca](https://codecov.io/gh/huggingface/transformers/pull/5956?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


merging to rerun.
Optimized squad.py multi-threading
Author: birdmw
Pull request: yes
Labels: name: wontfix

If there are few examples, don't bother multi-threading . The base cost of multi-threading in Python is expensive. I can't upload a picture of the call-stack visual profile because of my stupid company firewall, but multi-threading in python depends on serializing each object before sending it off. That process has a 5 second overhead coming from <method 'dump' of '_pickle.Pickler' objects>. Don't take my word for it - test it yourself. This small optimization reduces invocation run-time from 6s down to 1.1s for a single example inference where the len(examples) == 1. This optimization singular but it should be echoed across all pipelines in the Transformers repo.

ps: I also see a lot of lists with appends across the Transformers repository as a whole. This is a big speed suck. Look into using collections.deques more - deques are like lists but are highly optimized for appends.

Good Luck HuggingFace - you guys rock!

Comments:
This was a big performance hiccup for us. We managed to take a `QuestionAnswerAnsweringPipeline` down from 12 seconds to 6 seconds (with CUDA) and then to ~1 second (with the serialization removal optimization).

The code quality check is literally just that one line is too long.

> The code quality check is literally just that one line is too long.

Have a look at the contributing guidelines, in particular step 5. https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests

Doing style and quality checks locally makes sure that your pull request doesn't get that annoying '1 failing' note.

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.


Thank you, this is huge. On a g4dn.xlarge, with distilbert-base-cased-distilled-squad, I get about 60% speedup.
How to batch encode sentences using BertTokenizer?
Author: RayLei
Pull request: no
Labels: name: Core: Tokenization

# ❓ Questions & Help

<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
     new models and benchmarks, and migration questions. For all other questions,
     we direct you to Stack Overflow (SO) where a whole community of PyTorch and
     Tensorflow enthusiast can help you out. Make sure to tag your question with the
     right deep learning framework as well as the huggingface-transformers tag: 
     https://stackoverflow.com/questions/tagged/huggingface-transformers 
     
     If your question wasn't answered after a period of time on Stack Overflow, you
     can always open a question on GitHub. You should then link to the SO question 
     that you posted.
     -->

## Details
<!-- Description of your issue -->
I would like to create a minibatch by encoding multiple sentences using transformers.BertTokenizer. How can I do it? I tried following code.

```
from transformers import BertTokenizer
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')

tokenizer.encode('this is the first sentence')
>>> [2023, 2003, 1996, 2034, 6251]

tokenizer.encode(['this is the first sentence', 'another setence'])
>>> [100, 100] # expecting 7 tokens
```
<!-- You should first ask your question on SO, and only if
     you didn't get an answer ask it here on GitHub. -->
**A link to original question on Stack Overflow**:
https://stackoverflow.com/questions/62669261/how-to-encode-multiple-setence-using-transformers-berttokenizer

Comments:
Hi @RayLei Have a look at this https://huggingface.co/transformers/preprocessing.html
Error on instantiating pipeline.summarizer
Author: amgsharma
Pull request: no
Labels: name: wontfix

# 🐛 Bug

## Information


The problem arises when using:
I'm just testing out the different modules in the package. and following the examples on the [usage page](https://huggingface.co/transformers/usage.html)

## To reproduce

Run the following snippet with the environment set up as. described in the relevant section below
`from transformers import pipeline`
`summarizer = pipeline("summarization")`

<!-->

This is the traceback:
```
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
 in 
----> 1 summarizer = pipeline("summarization")

~/Projects/amlg/playground/venv/lib/python3.7/site-packages/transformers/pipelines.py in pipeline(task, model, config, tokenizer, framework, **kwargs)
   1759         model = model_class.from_pretrained(model, config=config, **model_kwargs)
   1760 
-> 1761     return task_class(model=model, tokenizer=tokenizer, modelcard=modelcard, framework=framework, task=task, **kwargs)

~/Projects/amlg/playground/venv/lib/python3.7/site-packages/transformers/pipelines.py in __init__(self, model, tokenizer, modelcard, framework, task, args_parser, device, binary_output)
    392 
    393         # Update config with task specific parameters
--> 394         task_specific_params = self.model.config.task_specific_params
    395         if task_specific_params is not None and task in task_specific_params:
    396             self.model.config.update(task_specific_params.get(task))

AttributeError: 'NoneType' object has no attribute 'config'
```


## Environment info
- `transformers` version: 2.9.1
- Platform: Darwin-19.3.0-x86_64-i386-64bit
- Python version: 3.7.3
- PyTorch version (GPU?): not installed (NA)
- Tensorflow version (GPU?): 2.1.0 (False)
- Using GPU in script?: Nope
- Using distributed or parallel set-up in script?: Nope


Comments:
I am also facing the same problem

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
Finetuning BERT classifier on a non-GLUE dataset in GLUE format
Author: shauli-ravfogel
Pull request: no
Labels: name: wontfix

# ❓ Questions & Help

<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
     new models and benchmarks, and migration questions. For all other questions,
     we direct you to Stack Overflow (SO) where a whole community of PyTorch and
     Tensorflow enthusiast can help you out. Make sure to tag your question with the
     right deep learning framework as well as the huggingface-transformers tag: 
     https://stackoverflow.com/questions/tagged/huggingface-transformers 
     
     If your question wasn't answered after a period of time on Stack Overflow, you
     can always open a question on GitHub. You should then link to the SO question 
     that you posted.
     -->

## Details
Hello,

I have a dataset of my own, formatted in GLUE format. Is it possible to use the script `run_glue.py` to finetune BERT on this dataset? If that's not possible, is there an alternative script for finetuning a classifier on arbitrary GLUE-formatted dataset?

Thanks!


<!-- You should first ask your question on SO, and only if
     you didn't get an answer ask it here on GitHub. -->



Comments:
The (new) run_glue.py is just a short template of code that you can copy/paste/customize (e.g. to plug your own Dataset), thanks to the [Trainer](https://github.com/huggingface/transformers/blob/master/src/transformers/trainer.py).

Thanks! which class would replace `GlueDataset` in that case? and what argument should I pass instead of `task_name`? and how to set the number of labels, which in `run_glue.py` is defined by `glue_tasks_num_labels`? 

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
convert pytorch_model.pt [pretrained Bert model] to pytorch_model.onnx (ONNX)
Author: pumpkinband
Pull request: no
Labels: name: wontfix

i use this to convert pytorch_model.pt to pytorch_model.onnx

```
from torch.autograd import Variable
import torch.onnx
import torchvision
import torch

dummy_input = Variable(torch.randn(1, 3, 256, 256))
model = torch.load('./pytorch_model.pt')
torch.onnx.export(model, dummy_input, "pytorch_model.onnx")
```

ERROR :- `The expanded size of the tensor (256) must match the existing size (3) at non-singleton dimension 3. Target sizes: [1, 3, 256, 256]. Tensor sizes: [1, 3]`

Are my `dummy_inputs` incorrect ?


Comments:
May be of interest to @mfuntowicz 

Hi @pumpkinband, 

I don't have the exact details of the model you're trying to load, but I'd assume a tensor of shape (1, 3) would make more sense (batch, sequence). 

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
[PretrainedTokenizer] is  <unk> a special token?
Author: sshleifer
Pull request: no
Labels: name: wontfix

name: Core: Tokenization

This confused me a lot as I was trying to add common tests for Marian.


I believe special_tokens_mask [must](
https://github.com/huggingface/transformers/blob/master/tests/test_tokenization_common.py#L445) return 0 for positions with unk_token_id, but `<unk>` is in `SpecialTokensMixin.all_special_ids`.

Relatedly, this [RobertaTokenizer](https://github.com/huggingface/transformers/blob/master/src/transformers/tokenization_roberta.py#L204) code suggests there should be a relationship between `all_special_ids` and `special_token_mask` logic.

Maybe `<unk>` shouldnt be in `SpecialTokensMixin.all_special_ids`?



Comments:
@mfuntowicz @LysandreJik might understand the best!

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
Speed on various cards
Author: Oxi84
Pull request: no
Labels: name: wontfix

This is not a bug, but I wonder if someone know what is the speed difference between different cards.

I now run bert base on 1080.

How much speedup will I get using 1080 ti  and 2080. Which one is faster for Transformers?

I know 2080 ti would be the best but probably the best one I can get would be 1080 ti or 2080.

Comments:
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.