noamaanMulla-03/transformers-issues huggingface dataset:
MbartTokenizer: do not hardcode vocab size
Author: sshleifer
Pull request: yes

language codes should start at the end of the standard vocab. If the standard vocab is smaller, this number is not 250,001.

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5998?src=pr&el=h1) Report
> Merging [#5998](https://codecov.io/gh/huggingface/transformers/pull/5998?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/33d7506ea10ca92886fd1bb3b5306a1a720c58fe&el=desc) will **increase** coverage by `0.00%`.
> The diff coverage is `100.00%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5998/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5998?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #5998   +/-   ##
=======================================
  Coverage   78.48%   78.49%           
=======================================
  Files         146      146           
  Lines       26230    26232    +2     
=======================================
+ Hits        20587    20591    +4     
+ Misses       5643     5641    -2     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5998?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/tokenization\_bart.py](https://codecov.io/gh/huggingface/transformers/pull/5998/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmFydC5weQ==) | `95.58% <100.00%> (+0.13%)` | :arrow_up: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5998/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.71% <0.00%> (+0.50%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5998?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/5998?src=pr&el=footer). Last update [33d7506...39fdead](https://codecov.io/gh/huggingface/transformers/pull/5998?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Transformer-XL: no mems are return when using 'return_tuple'
Author: RafaelWO
Pull request: no

# 🐛 Bug

## Information
The forward pass of the `TransfoXLLMHeadModel` returns no `mems` when using `return_tuple=True`.

Model I am using: Transformer-XL

Language I am using the model on: English

The problem arises when using:
* [x] my own modified scripts: (give details below)


## To reproduce

```Python
from transformers import TransfoXLLMHeadModel, TransfoXLTokenizer

model = TransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
model.train()
tokenizer = TransfoXLTokenizer.from_pretrained("transfo-xl-wt103")

encoded = tokenizer("Max is walking the dog in the streets", return_tensors='pt')
outputs = model(input_ids=encoded['input_ids'], mems=None, labels=encoded['input_ids'], return_tuple=True)
loss, _, mems = outputs

print(loss.size())
print(len(mems))      # should be 18 due to the 18 layers
```
Output:
```
Traceback (most recent call last):
  File "user/script.py", line 10, in <module>
    loss, _, mems = outputs
ValueError: not enough values to unpack (expected 3, got 2)
```


## Expected behavior
Output:
```
torch.Size([1, 7])
18
```

<!-- A clear and concise description of what you would expect to happen. -->

## 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: Windows-10-10.0.18362-SP0
- Python version: 3.6.10
- PyTorch version (GPU?): 1.4.0 (False)
- Tensorflow version (GPU?): 2.1.0 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No


Comments:
Thanks for flagging the issue, the fix is on its way to review.

Oh, I opened a PR for this, but it seems you fixed it yourself. I will close my PR then,
Replace `config.output_hidden_states` parameter with function argument `output_hidden_states`
Author: patrickvonplaten
Pull request: no
Labels: name: wontfix

name: Good First Issue

# 🚀 Feature request

Currently the user has to decide whether the  model should output the hidden states when she/he creates the config of a model: `config.output_hidden_states = True/False`. It would be nice if the user can decide this when calling the models `forward()` / `call()` with a flag `output_hidden_states`. This should be done for all TF and PT models that can output hidden states. 

A very similar recent change was done for the variable `config.output_past` -> see PR:https://github.com/huggingface/transformers/pull/3734 

## Motivation

The user has more flexibility when the hidden states should be output or not.

## Your contribution

If someone feels like contributing to the library, this would be a great first PR. I'm very happy to guide the contributor through the PR!

Comments:
Hi, @patrickvonplaten I want to take up this issue. Can I move forward with it? 

I think this could have side effects for libraries that use `config.output_hidden_states`, so I'm cc'ing @Timoeller and @brandenchan, because this parameter is used in [FARM](https://github.com/deepset-ai/FARM).

> Hi, @patrickvonplaten I want to take up this issue. Can I move forward with it?

That would be great, feel free to open a PR and do a first model. The PR should be very similar to what was done in PR #3734

Hi, @patrickvonplaten as I am new here I might take some time to get acquainted with the codebase and come up with a PR. Is it okay?

Sorry @gaurav-singh1998, I saw this issue was still open so I made a PR for it.

Okay, no issues @drjosephliu I'll find some other good first issues to solve. 

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.
🚀 An advice about changing variable name from "attention_mask" to "adder"
Author: ianliuy
Pull request: no
Labels: name: wontfix

name: Good First Issue

# 🚀 Feature request

<!-- A clear and concise description of the feature proposal.
     Please provide a link to the paper and code in case they exist. -->

## Motivation
I noticed that some users are pretty confused when reading source codes about variable `attention_mask`
like:
[What is the meaning of Attention Mask #205](https://github.com/huggingface/transformers/issues/205)
[Clarifying attention mask #542](https://github.com/huggingface/transformers/issues/542)
And I refer to the origional BERT repository - [google-research/bert](https://github.com/google-research/bert). Compared to the origin, I find in this repo sometimes the concepts of `attention_mask` and `adder` are mixed.

refering original BERT: [./modeling.py#L707](https://github.com/google-research/bert/blob/master/modeling.py#L707)
```python
attention_mask = tf.expand_dims(attention_mask, axis=[1])
adder = (1.0 - tf.cast(attention_mask, tf.float32)) * -10000.0
attention_scores += adder
```

But in this repo: take [src/transformers/modeling_tf_openai.py#L282](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_tf_openai.py#L282) as an example:
```python
attention_mask = attention_mask[:, tf.newaxis, tf.newaxis, :]
attention_mask = tf.cast(attention_mask, tf.float32)
attention_mask = (1.0 - attention_mask) * -10000.0
```
and inside the method `TFAttention._attn()` [src/transformers/modeling_tf_openai.py#L112](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_tf_openai.py#L112):
```python
if attention_mask is not None:
  # Apply the attention mask
  w = w + attention_mask
```
<!-- Please outline the motivation for the proposal. Is your feature request
     related to a problem? e.g., I'm always frustrated when [...]. If this is related
     to another GitHub issue, please link here too. -->

## Your contribution
may be changing its name is way better?
like:
```python
attention_mask = attention_mask[:, tf.newaxis, tf.newaxis, :]
attention_mask = tf.cast(attention_mask, tf.float32)
adder = (1.0 - attention_mask) * -10000.0
```
and then:
```python
if adder is not None:
  # Apply the attention mask
  attention_score = w + adder
```
<!-- Is there any way that you could help, e.g. by submitting a PR?
     Make sure to read the CONTRIBUTING.MD readme:
     https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md -->


Comments:
I agree! Do you want to open a PR about this to change the naming? :-) 
When doing this we just have to be careful to not change the user facing api when doing this -> which means that ideally, we should not rename any function arguments of high level modules like `BertModel.forward()`.

I've created PR #4566 for this issue

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.
Cannot import DPRReader
Author: avacaondata
Pull request: no

# 🐛 Bug

You have DPRReader included in your v3.0.2 documentation, but it's in the Master branch, it's not included in v3.0.2 tag; therefore it crashes and cannot import it. I think it would be convenient to either eliminate that piece of documentation until the models are added in the tag, or update the transformers version with the Master branch.


Comments:
Thanks for flagging, the stable doc was building on a wrong commit hash, hence the DPR models being present.
This is fixed now.
[model_cards] roberta-base-finetuned-yelp-polarity
Author: VictorSanh
Pull request: yes
Labels: name: model card

Model card for [roberta-base-finetuned-yelp-polarity](https://huggingface.co/VictorSanh/roberta-base-finetuned-yelp-polarity).

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6009?src=pr&el=h1) Report
> Merging [#6009](https://codecov.io/gh/huggingface/transformers/pull/6009?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f5b5c5bd7e213dea1645f07902b681f88e3cf954&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/6009/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/6009?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #6009      +/-   ##
==========================================
- Coverage   78.52%   78.51%   -0.01%     
==========================================
  Files         146      146              
  Lines       26252    26252              
==========================================
- Hits        20614    20612       -2     
- Misses       5638     5640       +2     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6009?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6009/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `81.19% <0.00%> (-0.30%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/6009/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.21% <0.00%> (-0.26%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/6009?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/6009?src=pr&el=footer). Last update [f5b5c5b...fed314c](https://codecov.io/gh/huggingface/transformers/pull/6009?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Fix question template
Author: sgugger
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6014?src=pr&el=h1) Report
> Merging [#6014](https://codecov.io/gh/huggingface/transformers/pull/6014?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/a5404052135a455f9b3ada6154dcfbe7c6ac3968&el=desc) will **increase** coverage by `1.32%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/6014/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/6014?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #6014      +/-   ##
==========================================
+ Coverage   77.18%   78.51%   +1.32%     
==========================================
  Files         146      146              
  Lines       26252    26252              
==========================================
+ Hits        20263    20612     +349     
+ Misses       5989     5640     -349     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6014?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/6014/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.02% <0.00%> (-69.52%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6014/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/6014/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.21% <0.00%> (ø)` | |
| [src/transformers/modeling\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6014/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `82.31% <0.00%> (+1.28%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/6014/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `96.77% <0.00%> (+73.38%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/6014/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/6014?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/6014?src=pr&el=footer). Last update [a540405...78af589](https://codecov.io/gh/huggingface/transformers/pull/6014?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Is there a Longformer For Sequence Classification?
Author: Weilin37
Pull request: no
Labels: name: New model

I noticed that Longformer does not have a "LongformerForSequenceClassification". Is there a reason for this and is this something that would be added in the near future?

Comments:
It is [there](https://github.com/huggingface/transformers/blob/24f46ea3f3e5006ca38735306753a846a0823174/src/transformers/modeling_longformer.py#L796). 

You may need to use a source install, I'm not sure it was already there in the last release.

Thanks. It was in the release but it just wasnt in the documentation.
Create README.md
Author: rdenadai
Pull request: yes
Labels: name: model card

README.md for my model

https://huggingface.co/rdenadai/BR_BERTo

Comments:
👍 

Would you like to add example inputs for all models for `pt`? If you do, please open a PR against this file: https://github.com/huggingface/widgets-server/blob/master/DefaultWidget.ts

Thanks:)
Create README.md
Author: mrm8488
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5951?src=pr&el=h1) Report
> Merging [#5951](https://codecov.io/gh/huggingface/transformers/pull/5951?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/95d1962b9c8460b4cec5a88eb9915e8e25f5bc1e&el=desc) will **decrease** coverage by `1.41%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5951/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5951?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5951      +/-   ##
==========================================
- Coverage   78.69%   77.27%   -1.42%     
==========================================
  Files         146      146              
  Lines       26214    26214              
==========================================
- Hits        20628    20258     -370     
- Misses       5586     5956     +370     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5951?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5951/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.38% <0.00%> (-73.39%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5951/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/5951/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.95% <0.00%> (-2.26%)` | :arrow_down: |
| [src/transformers/generation\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5951/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/5951/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/5951/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/5951?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/5951?src=pr&el=footer). Last update [95d1962...89670f7](https://codecov.io/gh/huggingface/transformers/pull/5951?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Update the new model template
Author: sgugger
Pull request: yes

The model template files were old and did not use any of the recent improvements (output attentions, output hidden states, docstrings refactored...)

This PR fixes them and adds a few more instructions.

Tagging @LysandreJik, @patrickvonplaten, @thomwolf and @julien-c : We have to make sure that whenever we make a substantial change that applies to all model, this template is also updated.

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/6019?src=pr&el=h1) Report
> Merging [#6019](https://codecov.io/gh/huggingface/transformers/pull/6019?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/778e635fc900e5afc90e5f8f4ca74b5d5fc2976a&el=desc) will **increase** coverage by `1.37%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/6019/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/6019?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #6019      +/-   ##
==========================================
+ Coverage   77.31%   78.68%   +1.37%     
==========================================
  Files         146      146              
  Lines       26249    26249              
==========================================
+ Hits        20295    20655     +360     
+ Misses       5954     5594     -360     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/6019?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/6019/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.98% <0.00%> (-49.38%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/6019/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `64.90% <0.00%> (-33.90%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/6019/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.53% <0.00%> (+69.51%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/6019/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `96.77% <0.00%> (+73.38%)` | :arrow_up: |

------

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Added the feature to provide a generation prompt for encoder-decoder models.
Author: lukovnikov
Pull request: yes

Added the `decoder_input_ids` argument to `.generate(...)`, which should be used (only) with encoder-decoder models to start generation from some sequence.

Comments:
The code quality check complains about lines being too long in modeling_utils.py.
There are several unchanged places where this is already the case. Should I ignore this?

Also adding @yjernite since we talked about something similar

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.


will re-open after sampling re-factor