noamaanMulla-03/transformers-issues huggingface dataset:
MarianMTModel translate {tgt}-{src}
Author: NonaryR
Pull request: no
Labels: name: marian

Hello! 
It is possible to use `MarianMTModels` for translation from the target language to source, i.e. backward?

Comments:
Nope. Often the reverse model exists, however, e.g. `en-fr` and `fr-en`.

> Nope. Often the reverse model exists, however, e.g. `en-fr` and `fr-en`.

What if reverse model does not exist for my langauge? 

What's your language? 
Maybe it's part of a multilingual group (below) or has been [trained](http://opus.nlpl.eu/Opus-MT/) since we did the conversion?
Otherwise, you're out of luck unfortunately.

```
GROUP_MEMBERS = {
 'ZH': ['cmn', 'cn', 'yue', 'ze_zh', 'zh_cn', 'zh_CN', 'zh_HK', 'zh_tw', 'zh_TW', 'zh_yue', 'zhs', 'zht', 'zh'],
 'ROMANCE': ['fr', 'fr_BE', 'fr_CA', 'fr_FR', 'wa', 'frp', 'oc', 'ca', 'rm', 'lld', 'fur', 'lij', 'lmo', 'es', 'es_AR', 'es_CL', 'es_CO', 'es_CR', 'es_DO', 'es_EC', 'es_ES', 'es_GT', 'es_HN', 'es_MX', 'es_NI', 'es_PA', 'es_PE', 'es_PR', 'es_SV', 'es_UY', 'es_VE', 'pt', 'pt_br', 'pt_BR', 'pt_PT', 'gl', 'lad', 'an', 'mwl', 'it', 'it_IT', 'co', 'nap', 'scn', 'vec', 'sc', 'ro', 'la'],
 'NORTH_EU': ['de', 'nl', 'fy', 'af', 'da', 'fo', 'is', 'no', 'nb', 'nn', 'sv'],
 'SCANDINAVIA': ['da', 'fo', 'is', 'no', 'nb', 'nn', 'sv'],
 'SAMI': ['se', 'sma', 'smj', 'smn', 'sms'],
 'NORWAY': ['nb_NO', 'nb', 'nn_NO', 'nn', 'nog', 'no_nb', 'no'],
 'CELTIC': ['ga', 'cy', 'br', 'gd', 'kw', 'gv']
}
```

> What's your language?
> Maybe it's part of a multilingual group (below) or has been [trained](http://opus.nlpl.eu/Opus-MT/) since we did the conversion?
> Otherwise, you're out of luck unfortunately.
> 
> ```
> GROUP_MEMBERS = {
>  'ZH': ['cmn', 'cn', 'yue', 'ze_zh', 'zh_cn', 'zh_CN', 'zh_HK', 'zh_tw', 'zh_TW', 'zh_yue', 'zhs', 'zht', 'zh'],
>  'ROMANCE': ['fr', 'fr_BE', 'fr_CA', 'fr_FR', 'wa', 'frp', 'oc', 'ca', 'rm', 'lld', 'fur', 'lij', 'lmo', 'es', 'es_AR', 'es_CL', 'es_CO', 'es_CR', 'es_DO', 'es_EC', 'es_ES', 'es_GT', 'es_HN', 'es_MX', 'es_NI', 'es_PA', 'es_PE', 'es_PR', 'es_SV', 'es_UY', 'es_VE', 'pt', 'pt_br', 'pt_BR', 'pt_PT', 'gl', 'lad', 'an', 'mwl', 'it', 'it_IT', 'co', 'nap', 'scn', 'vec', 'sc', 'ro', 'la'],
>  'NORTH_EU': ['de', 'nl', 'fy', 'af', 'da', 'fo', 'is', 'no', 'nb', 'nn', 'sv'],
>  'SCANDINAVIA': ['da', 'fo', 'is', 'no', 'nb', 'nn', 'sv'],
>  'SAMI': ['se', 'sma', 'smj', 'smn', 'sms'],
>  'NORWAY': ['nb_NO', 'nb', 'nn_NO', 'nn', 'nog', 'no_nb', 'no'],
>  'CELTIC': ['ga', 'cy', 'br', 'gd', 'kw', 'gv']
> }
> ```

Swahili, oooh!
add T5 fine-tuning notebook [Community notebooks]
Author: patil-suraj
Pull request: yes

@patrickvonplaten 
This is the second notebook which shows how to fine-tune T5 for multiple tasks with text-to-text approach (IMDB, emotion classification, SWAG) that we discussed in issue #4426 . I didn't find emotion and SWAG dataset in the `nlp` library so I decided to keep my original dataset code to keep everything unified.

Also there's growing interest in `pytoch-lightning` so I decided to keep the `lightning`  trainer. But if you think I should use HF Trainer then I can add that as well.

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=h1) Report
> Merging [#4462](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8f1d0471489352ec01556ae61f8e8246002bbc58&el=desc) will **increase** coverage by `0.04%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/4462/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #4462      +/-   ##
==========================================
+ Coverage   77.93%   77.98%   +0.04%     
==========================================
  Files         123      123              
  Lines       20430    20430              
==========================================
+ Hits        15922    15932      +10     
+ Misses       4508     4498      -10     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.41% <0.00%> (-0.12%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `88.66% <0.00%> (+1.80%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4462?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/4462?src=pr&el=footer). Last update [8f1d047...ca0d2a0](https://codecov.io/gh/huggingface/transformers/pull/4462?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


That's awesome. Thanks @patil-suraj! @mariamabarham @lhoestq - might it be interesting to add `emotion classification` and `swag` to `nlp`? 

Reworded the description a bit - hope that's ok @patil-suraj 

> Reworded the description a bit - hope that's ok @patil-suraj

@patrickvonplaten  yes, it's more clear now. Thank you!
[Tests, GPU, SLOW] fix a bunch of GPU hardcoded tests in Pytorch
Author: patrickvonplaten
Pull request: yes

in almost all tests I forgot to put the model on gpu via 
`model = model.to(torch_device)`

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4468?src=pr&el=h1) Report
> Merging [#4468](https://codecov.io/gh/huggingface/transformers/pull/4468?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5856999a9f2926923f037ecd8d27b8058bcf9dae&el=desc) will **decrease** coverage by `0.00%`.
> The diff coverage is `0.00%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/4468/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4468?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #4468      +/-   ##
==========================================
- Coverage   77.98%   77.98%   -0.01%     
==========================================
  Files         123      123              
  Lines       20436    20436              
==========================================
- Hits        15938    15937       -1     
- Misses       4498     4499       +1     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4468?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.41% <0.00%> (ø)` | |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.44% <0.00%> (-0.42%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4468?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/4468?src=pr&el=footer). Last update [5856999...7d9fd53](https://codecov.io/gh/huggingface/transformers/pull/4468?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Great!
[gpu slow tests] fix mbart-large-enro gpu tests
Author: sshleifer
Pull request: yes


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4472?src=pr&el=h1) Report
> Merging [#4472](https://codecov.io/gh/huggingface/transformers/pull/4472?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/48c3a70b4eaedab1dd9ad49990cfaa4d6cb8f6a0&el=desc) will **decrease** coverage by `0.41%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/4472/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4472?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #4472      +/-   ##
==========================================
- Coverage   78.41%   77.99%   -0.42%     
==========================================
  Files         123      123              
  Lines       20432    20432              
==========================================
- Hits        16021    15936      -85     
- Misses       4411     4496      +85     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4472?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/4472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `28.66% <0.00%> (-28.03%)` | :arrow_down: |
| [src/transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.53% <0.00%> (+0.11%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `88.66% <0.00%> (+0.16%)` | :arrow_up: |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.85% <0.00%> (+0.41%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4472?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/4472?src=pr&el=footer). Last update [48c3a70...9152273](https://codecov.io/gh/huggingface/transformers/pull/4472?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Problems About Using the Run_language_modeling with Tf2.
Author: RichardLS09
Pull request: no

# 🐛 Bug

### Model I am using Bert.

### The problem arises when using:
I'm using the run_language_modling.py to fine-tuning with (Tf2.0.0/Tf2.2.0). Of course i modify the script.
I use TFAutoModelWithLMHead,TFTrainer in this repo to build my script.
When i'm traning,here is the problem.
`ValueError: Trying to create optimizer slot variable under the scope for tf.distribute.Strategy (<tensorflow.python.distribute.one_device_strategy.OneDeviceStrategy object at 0x15b49bed0>), which is different from the scope used for the original variable (<tf.Variable 'tf_bert_for_masked_lm/bert/embeddings/word_embeddings/weight:0' shape=(21128, 768) dtype=float32, numpy=array(),dtype=float32)>). Make sure the slot variables are created under the same strategy scope. This may happen if you're restoring from a checkpoint outside the scope`
I move initializing the model to TFTrainer().args.strategy.scope() and work well!

### Someing to say
- It seems that when using tf2.0, there's some problems about TFTrainer's design. Will you improve this design so that one can use tf2.0 more conveniently in this repo?
- Thanks for this repo and your contribution.


Comments:
cc @jplu, might be of interest :)

Hello!

Like this there is not enough details to see what is the issue. Can you provide the piece of code you are trying to run? plz :)

Also if you are looking for how to properly use the trainer I suggest you to look at the already existing examples:

- [Question-answering](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_tf_squad.py)
- [Token classification](https://github.com/huggingface/transformers/blob/master/examples/token-classification/run_tf_ner.py)
- [Sequence classification](https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_tf_glue.py)
- [Multiple Choice](https://github.com/huggingface/transformers/blob/master/examples/multiple-choice/run_tf_multiple_choice.py)

They are all working well with CPU/Single GPU/Multiple GPU, only TPU need to be further tested for now.

Basically the score is created the first time when you call the `strategy` property of the `tf_training_args.py`. Be careful if you try to translate the PT script to TF there are quite a lot of differences to care about. The training arguments are one of them.

Nevertheless, thanks a lot for trying to make a language modeling with TF2 and will be happy to help in case you need some.

Thanks for your reply!  @jplu 

Sorry for that i'm not looking at the examples.In the examples, it initializes the model with trainng_args.strategy.scope(),and in my script, i initialize the model in TFTrainer.\__init\__ with the self.args.strategy.scope(). It looks the same.

If we initianize the model in  trainng_args.strategy.scope(), it's be ok ! At first, I think we should pass the model_args to TFTrainer, not the model, and initialize the model in \__init\__. Therefore i think maybe we should improve the design. 

Thanks again for your reply!
Remove warning of deprecation
Author: astariul
Pull request: yes

Remove warning of deprecated overload of `addcdiv_`

Fix #4451

Comments:
Signature is of `addcdiv_` is different between Pytorch 1.4 and 1.5

https://pytorch.org/docs/1.4.0/tensors.html?highlight=addcdiv#torch.Tensor.addcdiv
https://pytorch.org/docs/stable/tensors.html?highlight=addcdiv_#torch.Tensor.addcdiv

I guess as long as Pytorch 1.4 is supported by `transformers` we can just ignore the Warning given when using Pytorch 1.5

See #4477 for a fix that work for both PT1.4 and PT1.5
train model from scratch with big data
Author: jorgtied
Pull request: no
Labels: name: wontfix

# 🚀 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 would like to train a new model from scratch with some big data sets and the tutorial suggests to load and tokenize examples on the fly. It would be great if that feature is readily integrated in the example scripts (e.g. `run_language_modeling.py`). It is not entirely clear to me how to implement this in the most efficient way. My data set does not fit into memory and I cannot train out-of-the box with the existing scripts.

<!-- 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

<!-- 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:
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.
mbart config.json missing
Author: WeiliangGuo
Pull request: no

I downloaded mbart from fairseq, there are dict.txt, model.pt, sentence.bpe.model in it but no config.json, where can we get it (and other necessary missing files)?
I use mbart as pretrained model.

Is bart-large trained on multilingual data?
 Anyone has compared bart with t5?

Comments:
fairseq doesn't use config.json.

`BartConfig.from_pretrained('mbart-large-en-ro').to_json_file('config.json')` gets the config.json for English-Romanian, which is the only mbart checkpoint that's usable in this repository.
UnicodeDecodeError when loading BART from fairseq checkpoint
Author: marmg
Pull request: no

# 🐛 Bug

When trying to load a checpoint from the fariseq library I'm getting an UnicodeError

## Information

Model I am using (Bert, XLNet ...): BART

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. Train a checkpoint with the fairseq library
2. Load it using BartForMaskedLM.from_pretrained

<!-- 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

Get the checpoint loaded into a BART model.
<!-- A clear and concise description of what you would expect to happen. -->

## Environment info
<!-- You can run the command `python transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: master
- Platform: linux
- Python version: 3.6.7
- PyTorch version (GPU?): 1.4.0 / Yes
- Tensorflow version (GPU?):
- Using GPU in script?: No
- Using distributed or parallel set-up in script?:
- `fairseq` version: master

Comments:
Unfortunately, I don't think the conversion you are describing is currently supported. 
If I were to attempt this on my own, I would try to modify https://github.com/huggingface/transformers/blob/master/src/transformers/convert_bart_original_pytorch_checkpoint_to_pytorch.py to take in a path to a checkpoint, rather than a `torch.hub` alias.

This function converts from saved fairseq checkpoints: https://github.com/huggingface/transformers/blob/7a7fdf71f80452fcae064bd016f06e9a0f0f19ed/src/transformers/convert_bart_original_pytorch_checkpoint_to_pytorch.py#L81

Let me know if that helps!
add BERT trained from review corpus.
Author: howardhsu
Pull request: yes
Labels: name: model card

add BERT trained from review corpus.

Comments:
Hi @howardhsu, the file path is not correct, it should be something like `model_cards/activebus/BERT_Review/README.md` 

I updated paths as suggested, thanks.

# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4405?src=pr&el=h1) Report
> Merging [#4405](https://codecov.io/gh/huggingface/transformers/pull/4405?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/3e0f06210646a440509efa718b30d18322d6a830&el=desc) will **increase** coverage by `0.02%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/4405/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4405?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #4405      +/-   ##
==========================================
+ Coverage   78.16%   78.19%   +0.02%     
==========================================
  Files         120      120              
  Lines       20058    20058              
==========================================
+ Hits        15679    15684       +5     
+ Misses       4379     4374       -5     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4405?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4405/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `92.93% <0.00%> (+0.82%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4405?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/4405?src=pr&el=footer). Last update [3e0f062...466c62e](https://codecov.io/gh/huggingface/transformers/pull/4405?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Great: [model pages](https://huggingface.co/activebus)
Model card for RuPERTa-base fine-tuned for NER
Author: mrm8488
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4466?src=pr&el=h1) Report
> Merging [#4466](https://codecov.io/gh/huggingface/transformers/pull/4466?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5856999a9f2926923f037ecd8d27b8058bcf9dae&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/4466/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4466?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #4466      +/-   ##
==========================================
- Coverage   77.98%   77.98%   -0.01%     
==========================================
  Files         123      123              
  Lines       20436    20436              
==========================================
- Hits        15938    15937       -1     
- Misses       4498     4499       +1     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4466?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4466/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `88.50% <0.00%> (-0.17%)` | :arrow_down: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4466?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`
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nice example