noamaanMulla-03/transformers-issues huggingface dataset:
🐛 Inconsistencies between BartTokenizer and BartTokenizerFast
Author: astariul
Pull request: no

# 🐛 Bug

## Description

It's possible to use the argument `add_prefix_space` with `BartTokenizer` :

```
from transformers import BartTokenizer

t = BartTokenizer.from_pretrained("facebook/bart-large")
x = t("This is an example.", add_prefix_space=True)
```

But when doing the same with `BartTokenizerFast` :
```
from transformers import BartTokenizerFast

t = BartTokenizerFast.from_pretrained("facebook/bart-large")
x = t("This is an example.", add_prefix_space=True)
```

It throws the following error :

```
ValueError: Keyword arguments {'add_prefix_space': True} not recognized.
```

## To reproduce

[Colab notebook](https://colab.research.google.com/drive/1f0W2llsJfVIkXsYk0XK1C3oiy2xSqYOx?usp=sharing)

## Work-around

It seems working if the argument is specified in the constructor :
```
from transformers import BartTokenizerFast

t = BartTokenizerFast.from_pretrained("facebook/bart-large", add_prefix_space=True)
x = t("This is an example.")
```

@sshleifer 

Comments:
Seems like this issue is for all fast tokenizers, this [line](https://github.com/huggingface/transformers/blob/master/src/transformers/tokenization_utils_fast.py#L312) directly raises that error when kwargs are passed

Can I close? Seems like your workaround is solid @Colanim 

If it's the expected behavior, sure go ahead ^^

I opened because I thought `Tokenizer` and `TokenizerFast` were expected to have the same behaviors.

Fair. I think there is a medium-term plan to deprecate `add_prefix_space`, so at the moment it is left inconsistent and in the future it will be deleted from both.
XLNet PLM Readme
Author: LysandreJik
Pull request: yes

Add information on XLNet and its PLM objective in the language-modeling README.

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6121?src=pr&el=h1) Report
> Merging [#6121](https://codecov.io/gh/huggingface/transformers/pull/6121?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/92f8ce2ed65f23f91795ce6eafb8cce1e226cd38&el=desc) will **decrease** coverage by `0.73%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/6121/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/6121?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #6121      +/-   ##
==========================================
- Coverage   78.51%   77.77%   -0.74%     
==========================================
  Files         146      146              
  Lines       26326    26326              
==========================================
- Hits        20669    20476     -193     
- Misses       5657     5850     +193     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6121?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/6121/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.38% <0.00%> (-73.39%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6121/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.21% <0.00%> (+0.25%)` | :arrow_up: |
| [src/transformers/modeling\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6121/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `82.31% <0.00%> (+1.28%)` | :arrow_up: |
| [src/transformers/tokenization\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6121/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `84.09% <0.00%> (+12.87%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6121/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `95.18% <0.00%> (+74.91%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6121?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/6121?src=pr&el=footer). Last update [92f8ce2...f465894](https://codecov.io/gh/huggingface/transformers/pull/6121?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Bug in language_modeling.py calling tokenizer.num_special_tokens_to_add
Author: frarito
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.0.2
- Platform: Linux-4.4.0-1081-aws-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.6.0+cu101 (True)
- Tensorflow version (GPU?): 2.1.0 (True)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no

### Who can help
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.
 tokenizers: @mfuntowicz
 -->

## Information

Model I am using GPT-2

The class TextDataset call tokenizer.num_special_tokens_to_add(pair=False) but the correct argument is called is_pair. I assume the bugfix corresponds to transformers repo.

## To reproduce

https://github.com/huggingface/transformers/blob/e49393c3617e877f0370f7bad7c7e823808c5bfb/src/transformers/data/datasets/language_modeling.py#L27

https://github.com/huggingface/tokenizers/blob/master/bindings/python/tokenizers/implementations/base_tokenizer.py#L20


I'm using transformers 3.0.2 and tokenizers 0.8.1rc1 (try to update but says its incompatible)

<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->


Comments:
I was using a wrong approch, it works if I train the tokenizer, save de params, and load into a FastTokenizer impl
[WIP] Proposal for TF model outputs
Author: sgugger
Pull request: yes

This picks up on the work @thomwolf did on #5740 to have self-documented outputs in TensorFlow that are compatible with the AutoGraph system.
`TFModelOuput` subclasses `OrderedDict` while still being a dataclass, with some tweaks in the `post_init`:
- only the not-None attributes are set as values for the dictionary because tensorflow refuses None as outputs.
- a `TFModelOutput` can be instantiated with the regular keyword arguments but also with an iterator passed as the first argument (as a dict would) like @thomwolf suggested in #5740, with a fix to make sure the first input is not a tensor (because tensors are iterables).

This breaks two things for the TensorFlow side of the library:
1. when unpacking `outputs`, a slice needs to be used, otherwise the keys of the dictionary are returned, not the values:
```
loss, logits = outputs
```
will fail, it needs to be changed to
```
loss, logits = outputs[:2]
```
2. when loading and saving a model using `SavedModel`, the subclass is lost and the output becomes a regular dictionary (see the change in `test_keras_save_load`).

Apart from those, these model outputs are fully backward compatible (you can index with an int or a slice and get the same behavior as before).

If this is accepted, I would strongly recommend using the same base class for PyTorch model outputs, which would imply the breaking change number 1 but would have the added benefit of:
1. fixing the problem with `DataParallel`
2. have consistent outputs between TF and PyTorch.

Comments:
Sadly changing the `__iter__` function does not work as it's used inside TensorFlow (specifically in `tensorflow/python/util/nest.py`).

Ok closing this prototype now that we have a way forward (see [the forum](https://discuss.huggingface.co/t/new-model-output-types/195/8)).
seq2seq/finetune.py can take config train_params through command line
Author: sshleifer
Pull request: no

- this might belong in lightning_base
- check how/if trainer does it.

Desired API:
```bash
python finetune.py --encoder_layerdrop 0.1 --decoder_layerdrop 0.1 --dropout 0.1 --attention_dropout 0.1
```

Comments:
@stas00 this might be up your alley.

Added to my todo queue - thank you, @sshleifer

https://github.com/huggingface/transformers/pull/6149
process stuck at LineByLineTextDataset. training not starting
Author: arvikumar83
Pull request: no

# ❓ Questions & Help

I am using below python code.
BASE_MODEL  = "/data/nlp/bert-base-uncased"
CACHE_DIR  = "/data/nlp/cache"

model       = AutoModelWithLMHead.from_pretrained(BASE_MODEL,cache_dir=CACHE_DIR)
t_tokenizer = ByteLevelBPETokenizer()
t_tokenizer.train(files=paths, vocab_size=52_000, min_frequency=2, special_tokens=[
    "
",
    "<pad>",
    "
",
    "<unk>",
    "<mask>",
])

new_vocab = t_tokenizer.get_vocab()

tokenizer = BertTokenizerFast.from_pretrained(BASE_MODEL)
num_added_toks = tokenizer.add_tokens(list(new_vocab.keys()))
model.resize_token_embeddings(len(tokenizer))
dataset = LineByLineTextDataset(tokenizer=tokenizer,file_path=DATA_FILE,block_size=64)


it works fine for small files but for file > 600 MB the process gets stuck at dataset = LineByLineTextDataset(tokenizer=tokenizer,file_path=DATA_FILE,block_size=64)


Comments:
Hi, this is because it's tokenizing the entire dataset in a single thread, so it's bound to be a bit slow. This class caches the result though, so you will only have to do this step once!
tensorflow转为pytorch的两个文件在哪里？
Author: ChrisChaw
Pull request: no

![image](https://user-images.githubusercontent.com/41299010/88131997-e31b9480-cc10-11ea-9966-f63a1b425878.png)
大佬您好：
请问这两个文件在哪里？discriminator.json和model.bin

Comments:
If I understand correctly and you're asking what/where are those two files:

- `discriminator.json` is the configuration file for the model you want to convert
- `model.bin` is the location where the converted checkpoint will be saved.
Test on a new string of gpt2 fine tuned
Author: lalitkishorevyas
Pull request: no

I fine tuned GPT2 on my own dataset now I have fine tuned model how can I test it on new string??


GPT-2/GPT and causal language modeling
The following example fine-tunes GPT-2 on WikiText-2. We're using the raw WikiText-2 (no tokens were replaced before the tokenization). The loss here is that of causal language modeling.

```
export TRAIN_FILE=/path/to/dataset/wiki.train.raw
export TEST_FILE=/path/to/dataset/wiki.test.raw

python run_language_modeling.py \
    --output_dir=output \
    --model_type=gpt2 \
    --model_name_or_path=gpt2 \
    --do_train \
    --train_data_file=$TRAIN_FILE \
    --do_eval \
    --eval_data_file=$TEST_FILE
```

Comments:
I have these files generated
<img width="1389" alt="Screenshot 2020-07-22 at 12 39 19 AM" src="https://user-images.githubusercontent.com/33617789/88096141-d1f06a80-cbb3-11ea-8468-9284fb074bef.png">


can you please provide a code snippet

Not sure what you mean by test, do you want to generate using the model or calculate loss and perplexity for the test data ?

For generation you can use the `.generate` method. This [blog post ](https://huggingface.co/blog/how-to-generate) explains generate very well.

got it thanks :)

Closing this as the issue is solved. Feel free to re-open if you still face issues.
text classification reuse without classifier
Author: YuBeomGon
Pull request: no

thanks in advance.
I want to train first more data, it mans more label.
(its like pretraining)

after that I choose some label only, and train again.

But error happened during below code

tokenizer = RobertaTokenizer.from_pretrained(pretrained_path, do_lower_case=False)
model = RobertaForSequenceClassification.from_pretrained(pretrained_path, num_labels=10)

error message is like below.
Error(s) in loading state_dict for RobertaForSequenceClassification:
	size mismatch for classifier.out_proj.weight: copying a param with shape torch.Size([19, 768]) from checkpoint, the shape in current model is torch.Size([10, 768]).
	size mismatch for classifier.out_proj.bias: copying a param with shape torch.Size([19]) from checkpoint, the shape in current model is torch.Size([10]).

how can I do it??

Comments:
Hi! This doesn't currently work, because it's trying to instantiate a classification layer with 10 labels, while the checkpoint's classification layer has 19 labels. 

What you want is to keep the base layers, but ignore the classification layers. In order to do so, you can load your checkpoint in a base `RobertaModel`. This will only load the base model. You can then save that model to a checkpoint, and load that checkpoint from a `RobertaForSequenceClassification` model.

Here's how to do this:

```py
from transformers import RobertaForSequenceClassification, RobertaConfig, RobertaModel

model = RobertaModel.from_pretrained(pretrained_path)
model.save_pretrained(f"{pretrained_path}-base-model")

config = RobertaConfig(num_labels=10)
model = RobertaForSequenceClassification.from_pretrained(f"{pretrained_path}-base-model", config=config)
```

You should see the output:

```
Some weights of RobertaForSequenceClassification were not initialized from the model checkpoint at here-base-model and are newly initialized: ['classifier.dense.weight', 'classifier.out_proj.bias', 'classifier.out_proj.weight', 'classifier.dense.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
```

This means that it has correctly loaded the entire base model, and has randomly initialized the classifier weights. Hope that helps!
cannot import name 'TFElectraModel' from 'transformers'
Author: lijinfeng0713
Pull request: no
Labels: name: wontfix

# 🐛 Bug

hi, thanks for your nice tool for NLP.
However, when I use transformers on MacOs to load Electra model I get an import error 

> ImportError: cannot import name 'TFElectraModel' from 'transformers'

How can I fix this issue?


Comments:
Hello !

Which version of the lib do you use?

Hello!

I think it's a problem with your GPU rather than from transformers. Check your TensorFlow whether "Failed to load the native TensorFlow runtime." appears once it is imported.

That's probably because you don't have `tensorflow>=2.0` installed while you're trying to load a TensorFlow model.

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.
Actually the extra_id are from 0-99 and not from 1-100
Author: orena1
Pull request: yes

```
a = tokenizer.encode("we got a <extra_id_99>", return_tensors='pt',add_special_tokens=True)
print(a)
>tensor([[   62,   530,     3,     9, 32000]])
a = tokenizer.encode("we got a <extra_id_100>", return_tensors='pt',add_special_tokens=True)
print(a)
>tensor([[   62,   530,     3,     9,     3,     2, 25666,   834,    23,    26,
           834,  2915,  3155]])
```

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5967?src=pr&el=h1) Report
> Merging [#5967](https://codecov.io/gh/huggingface/transformers/pull/5967?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ae67b2439fb15954bfd8f0fdf521cf1a650bafb9&el=desc) will **not change** coverage.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5967/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5967?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #5967   +/-   ##
=======================================
  Coverage   78.51%   78.51%           
=======================================
  Files         146      146           
  Lines       26214    26214           
=======================================
  Hits        20581    20581           
  Misses       5633     5633           
```



------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5967?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/5967?src=pr&el=footer). Last update [ae67b24...e8e003f](https://codecov.io/gh/huggingface/transformers/pull/5967?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Hi @patrickvonplaten, can you have a look?

Thansk @orena1 !

pinging @patrickvonplaten for notification
add another e.g. to avoid confusion
Author: orena1
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6055?src=pr&el=h1) Report
> Merging [#6055](https://codecov.io/gh/huggingface/transformers/pull/6055?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b9b11795cfdce7bb8dd8a01ec5efa602589a78b2&el=desc) will **increase** coverage by `0.11%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/6055/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/6055?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #6055      +/-   ##
==========================================
+ Coverage   78.26%   78.37%   +0.11%     
==========================================
  Files         146      146              
  Lines       26253    26253              
==========================================
+ Hits        20546    20576      +30     
+ Misses       5707     5677      -30     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6055?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_pytorch\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6055/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9weXRvcmNoX3V0aWxzLnB5) | `89.30% <ø> (ø)` | |
| [src/transformers/modeling\_tf\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6055/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.98% <0.00%> (-49.38%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6055/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `85.96% <0.00%> (+2.00%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6055/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/6055?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/6055?src=pr&el=footer). Last update [b9b1179...7264c50](https://codecov.io/gh/huggingface/transformers/pull/6055?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
question-answering examples bug in pipelines document
Author: sakares
Pull request: no
Labels: name: wontfix

Regarding
https://github.com/huggingface/transformers/blob/96f57c9ccb6363623005fb3f05166dfd7acb3f53/src/transformers/pipelines.py#L1739

it will cause a reproducible bug:

```python
from transformers import pipeline
nlp_qa = pipeline('question-answering', model='distilbert-base-cased-distilled-squad', tokenizer='bert-base-cased')
nlp_qa(context='Hugging Face is a French company based in New-York.', question='Where is based Hugging Face ?')

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/my_name/Library/Python/3.7/lib/python/site-packages/transformers/pipelines.py", line 1188, in __call__
    start, end = self.model(**fw_args)
  File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
TypeError: forward() got an unexpected keyword argument 'token_type_ids'
```

but it should use `tokenizer='distilbert-base-cased'`

```python
from transformers import pipeline
nlp_qa = pipeline('question-answering', model='distilbert-base-cased-distilled-squad', tokenizer='distilbert-base-cased')
nlp_qa(context='Hugging Face is a French company based in New-York.', question='Where is based Hugging Face ?')

{'score': 0.9632966867654424, 'start': 42, 'end': 50, 'answer': 'New-York.'}
```

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.
Fix FlauBERT GPU test
Author: LysandreJik
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6142?src=pr&el=h1) Report
> Merging [#6142](https://codecov.io/gh/huggingface/transformers/pull/6142?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/54f9fbeff822ec0547fd23d0338654456925f6b7&el=desc) will **decrease** coverage by `0.03%`.
> The diff coverage is `100.00%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/6142/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/6142?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #6142      +/-   ##
==========================================
- Coverage   78.35%   78.32%   -0.04%     
==========================================
  Files         146      146              
  Lines       26403    26403              
==========================================
- Hits        20689    20679      -10     
- Misses       5714     5724      +10     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6142?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/6142/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19mbGF1YmVydC5weQ==) | `86.61% <100.00%> (ø)` | |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6142/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.95% <0.00%> (-2.26%)` | :arrow_down: |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6142/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `82.20% <0.00%> (-0.29%)` | :arrow_down: |

------

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