


"""simple docstring"""







# Usage:
# ./gen-card-allenai-wmt19.py

import os
from pathlib import Path






def        a__			(							_UpperCamelCase						,      _UpperCamelCase						,      _UpperCamelCase						,      _UpperCamelCase			):





						"""simple docstring"""

						UpperCAmelCase__												=     {
						    '''en''': '''Machine learning is great, isn\'t it?''',
						    '''ru''': '''Машинное обучение - это здорово, не так ли?''',
						    '''de''': '''Maschinelles Lernen ist großartig, nicht wahr?''',
						}

						# BLUE scores as follows:
						# "pair": [fairseq, transformers]
						UpperCAmelCase__												=     {
						    '''wmt19-de-en-6-6-base''': [0, 38.37],
						    '''wmt19-de-en-6-6-big''': [0, 39.90],
						}
						UpperCAmelCase__												=     F"""{src_lang}-{tgt_lang}"""

						UpperCAmelCase__												=     F"""
---

language:
- {src_lang}
- {tgt_lang}
thumbnail:
tags:
- translation
- wmt19
- allenai
license: apache-2.0
datasets:
- wmt19
metrics:
- bleu
---

# FSMT

## Model description

This is a ported version of fairseq-based [wmt19 transformer](https://github.com/jungokasai/deep-shallow/) for {src_lang}-{tgt_lang}.

For more details, please, see [Deep Encoder, Shallow Decoder: Reevaluating the Speed-Quality Tradeoff in Machine Translation](https://arxiv.org/abs/2006.10369).

2 models are available:

* [wmt19-de-en-6-6-big](https://huggingface.co/allenai/wmt19-de-en-6-6-big)
* [wmt19-de-en-6-6-base](https://huggingface.co/allenai/wmt19-de-en-6-6-base)


## Intended uses & limitations

#### How to use

```python
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
mname = \"allenai/{model_name}\"
tokenizer = FSMTTokenizer.from_pretrained(mname)
model = FSMTForConditionalGeneration.from_pretrained(mname)

input = \"{texts[src_lang]}\"
input_ids = tokenizer.encode(input, return_tensors=\"pt\")
outputs = model.generate(input_ids)
decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(decoded) # {texts[tgt_lang]}

```

#### Limitations and bias


## Training data

Pretrained weights were left identical to the original model released by allenai. For more details, please, see the [paper](https://arxiv.org/abs/2006.10369).

## Eval results

Here are the BLEU scores:

model   |  transformers
-------|---------
{model_name}  |  {scores[model_name][1]}

The score was calculated using this code:

```bash
git clone https://github.com/huggingface/transformers
cd transformers
export PAIR={pair}
export DATA_DIR=data/$PAIR
export SAVE_DIR=data/$PAIR
export BS=8
export NUM_BEAMS=5
mkdir -p $DATA_DIR
sacrebleu -t wmt19 -l $PAIR --echo src > $DATA_DIR/val.source
sacrebleu -t wmt19 -l $PAIR --echo ref > $DATA_DIR/val.target
echo $PAIR
PYTHONPATH=\"src:examples/seq2seq\" python examples/seq2seq/run_eval.py allenai/{model_name} $DATA_DIR/val.source $SAVE_DIR/test_translations.txt --reference_path $DATA_DIR/val.target --score_path $SAVE_DIR/test_bleu.json --bs $BS --task translation --num_beams $NUM_BEAMS
```

## Data Sources

- [training, etc.](http://www.statmt.org/wmt19/)
- [test set](http://matrix.statmt.org/test_sets/newstest2019.tgz?1556572561)


### BibTeX entry and citation info

```
@misc{{kasai2020deep,
    title={{Deep Encoder, Shallow Decoder: Reevaluating the Speed-Quality Tradeoff in Machine Translation}},
    author={{Jungo Kasai and Nikolaos Pappas and Hao Peng and James Cross and Noah A. Smith}},
    year={{2020}},
    eprint={{2006.10369}},
    archivePrefix={{arXiv}},
    primaryClass={{cs.CL}}
}}
```

"""
						model_card_dir.mkdir(parents=_UpperCamelCase						,      exist_ok=_UpperCamelCase			)
						UpperCAmelCase__												=     os.path.join(_UpperCamelCase						,      '''README.md'''			)
						print(F"""Generating {path}"""			)
						with open(_UpperCamelCase						,      '''w'''						,      encoding='''utf-8'''			) as f:
												f.write(_UpperCamelCase			)


# make sure we are under the root of the project
__a      			= Path(__file__).resolve().parent.parent.parent
__a      			= repo_dir / "model_cards"

for model_name in ["wmt19-de-en-6-6-base", "wmt19-de-en-6-6-big"]:
						__a      			= model_cards_dir / "allenai" / model_name
						write_model_card(model_card_dir, src_lang="de", tgt_lang="en", model_name=model_name)



"""simple docstring"""







import inspect
import json
import os
import tempfile
import unittest

from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES

from ...test_tokenization_common import TokenizerTesterMixin
class 				lowerCamelCase							(      __SCREAMING_SNAKE_CASE					,       unittest.TestCase			):


							"""simple docstring"""
							SCREAMING_SNAKE_CASE              =   SpeechaTextaTokenizer
							SCREAMING_SNAKE_CASE              =   False






							def        lowerCAmelCase  (    self			:  Dict					):
													super().setUp()

													UpperCAmelCase__												=     '''<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'''.split(''' '''					)
													UpperCAmelCase__												=     ['''he re</w> 123''', '''here a 1456''']
													UpperCAmelCase__												=     dict(zip(lowerCamelCase_		,			range(len(lowerCamelCase_					)					)					)					)

													UpperCAmelCase__												=     {'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}

													UpperCAmelCase__												=     tempfile.mkdtemp()
													UpperCAmelCase__												=     os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES['''vocab_file''']					)
													UpperCAmelCase__												=     os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES['''merges_file''']					)

													with open(self.vocab_file		,			'''w'''		,			encoding='''utf-8'''					) as fp:
																			fp.write(json.dumps(lowerCamelCase_					) + '''\n'''					)

													with open(self.merges_file		,			'''w'''					) as fp:
																			fp.write('''\n'''.join(lowerCamelCase_					)					)






							def        lowerCAmelCase  (    self			:  Union[str, Any]					):
													UpperCAmelCase__												=     list(self.get_tokenizer().get_vocab().keys()					)

													self.assertEqual(vocab_keys[0]		,			'''<s>'''					)
													self.assertEqual(vocab_keys[1]		,			'''<pad>'''					)
													self.assertEqual(vocab_keys[-1]		,			'''vocab'''					)
													self.assertEqual(len(lowerCamelCase_					)		,			14					)






							def        lowerCAmelCase  (    self			:  Optional[Any]					):
													self.assertEqual(self.get_tokenizer().vocab_size		,			14					)






							def        lowerCAmelCase  (    self			:  Any					):
													UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

													# make sure @@ is correctly concatenated
													UpperCAmelCase__												=     [4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
													UpperCAmelCase__												=     tokenizer.decode(lowerCamelCase_					)

													self.assertTrue(output_string == '''herecouple words ofthe'''					)






							def        lowerCAmelCase  (    self			:  int					):
													UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(self.tmpdirname					)

													with tempfile.TemporaryDirectory() as tmp_dirname:
																			tokenizer.save_pretrained(lowerCamelCase_					)
																			os.remove(os.path.join(lowerCamelCase_		,			'''merges.txt'''					)					)

																			# load tokenizer without merges file should not throw an error
																			UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(lowerCamelCase_					)

													with tempfile.TemporaryDirectory() as tmp_dirname:
																			# save tokenizer and load again
																			tokenizer.save_pretrained(lowerCamelCase_					)
																			UpperCAmelCase__												=     SpeechaTextaTokenizer.from_pretrained(lowerCamelCase_					)

													self.assertIsNotNone(lowerCamelCase_					)






							def        lowerCAmelCase  (    self			:  int					):
													if not self.test_slow_tokenizer:
																			return

													UpperCAmelCase__												=     inspect.signature(self.tokenizer_class.__init__					)
													UpperCAmelCase__												=     self.get_tokenizer()

													for parameter_name, parameter in signature.parameters.items():
																			if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
																									self.assertIn(lowerCamelCase_		,			tokenizer.init_kwargs					)