


# Usage:
# ./gen-card-allenai-wmt16.py

import os
from pathlib import Path



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		Dict:
    _lowercase :							List[str]   	=	{
        '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]
    _lowercase :							List[str]   	=	{
        'wmt16-en-de-dist-12-1': [28.3, 27.52],
        'wmt16-en-de-dist-6-1': [27.4, 27.11],
        'wmt16-en-de-12-1': [26.9, 25.75],
    }
    _lowercase :							Dict   	=	F'''{src_lang}-{tgt_lang}'''

    _lowercase :							Optional[Any]   	=	F'''
---
language:
- {src_lang}
- {tgt_lang}
thumbnail:
tags:
- translation
- wmt16
- allenai
license: apache-2.0
datasets:
- wmt16
metrics:
- bleu
---

# FSMT

## Model description

This is a ported version of fairseq-based [wmt16 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).

All 3 models are available:

* [wmt16-en-de-dist-12-1](https://huggingface.co/allenai/wmt16-en-de-dist-12-1)
* [wmt16-en-de-dist-6-1](https://huggingface.co/allenai/wmt16-en-de-dist-6-1)
* [wmt16-en-de-12-1](https://huggingface.co/allenai/wmt16-en-de-12-1)


## 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   | fairseq | transformers
-------|---------|----------
{model_name}  | {scores[model_name][0]} | {scores[model_name][1]}

The score is slightly below the score reported in the paper, as the researchers don\'t use `sacrebleu` and measure the score on tokenized outputs. `transformers` score was measured using `sacrebleu` on detokenized outputs.

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 wmt16 -l $PAIR --echo src > $DATA_DIR/val.source
sacrebleu -t wmt16 -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/wmt16/)
- [test set](http://matrix.statmt.org/test_sets/newstest2016.tgz?1504722372)


### 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=lowerCamelCase_							,				exist_ok=lowerCamelCase_				)
    _lowercase :							int   	=	os.path.join(lowerCamelCase_							,				'README.md'				)
    print(F'''Generating {path}'''				)
    with open(lowerCamelCase_							,				'w'							,				encoding='utf-8'				) as f:
        f.write(lowerCamelCase_				)


# make sure we are under the root of the project
SCREAMING_SNAKE_CASE :   List[str]							      =				Path(__file__).resolve().parent.parent.parent
SCREAMING_SNAKE_CASE :   List[str]							      =				repo_dir / "model_cards"

for model_name in ["wmt16-en-de-dist-12-1", "wmt16-en-de-dist-6-1", "wmt16-en-de-12-1"]:
 SCREAMING_SNAKE_CASE :   int							      =				model_cards_dir / "allenai" / model_name
 write_model_card(model_card_dir, src_lang="en", tgt_lang="de", model_name=model_name)






from __future__ import annotations

SCREAMING_SNAKE_CASE :   Union[str, Any]							      =				tuple[int, int, int]
SCREAMING_SNAKE_CASE :   Any							      =				tuple[str, str, str]


# used alphabet --------------------------
# from string.ascii_uppercase
SCREAMING_SNAKE_CASE :   Optional[Any]							      =				"ABCDEFGHIJKLMNOPQRSTUVWXYZ"

# -------------------------- default selection --------------------------
# rotors --------------------------
SCREAMING_SNAKE_CASE :   Tuple							      =				"EGZWVONAHDCLFQMSIPJBYUKXTR"
SCREAMING_SNAKE_CASE :   List[str]							      =				"FOBHMDKEXQNRAULPGSJVTYICZW"
SCREAMING_SNAKE_CASE :   Dict							      =				"ZJXESIUQLHAVRMDOYGTNFWPBKC"
# reflector --------------------------
SCREAMING_SNAKE_CASE :   Any							      =				{
    "A": "N",
    "N": "A",
    "B": "O",
    "O": "B",
    "C": "P",
    "P": "C",
    "D": "Q",
    "Q": "D",
    "E": "R",
    "R": "E",
    "F": "S",
    "S": "F",
    "G": "T",
    "T": "G",
    "H": "U",
    "U": "H",
    "I": "V",
    "V": "I",
    "J": "W",
    "W": "J",
    "K": "X",
    "X": "K",
    "L": "Y",
    "Y": "L",
    "M": "Z",
    "Z": "M",
}

# -------------------------- extra rotors --------------------------
SCREAMING_SNAKE_CASE :   List[Any]							      =				"RMDJXFUWGISLHVTCQNKYPBEZOA"
SCREAMING_SNAKE_CASE :   Dict							      =				"SGLCPQWZHKXAREONTFBVIYJUDM"
SCREAMING_SNAKE_CASE :   Optional[int]							      =				"HVSICLTYKQUBXDWAJZOMFGPREN"
SCREAMING_SNAKE_CASE :   List[Any]							      =				"RZWQHFMVDBKICJLNTUXAGYPSOE"
SCREAMING_SNAKE_CASE :   Optional[int]							      =				"LFKIJODBEGAMQPXVUHYSTCZRWN"
SCREAMING_SNAKE_CASE :   Optional[Any]							      =				"KOAEGVDHXPQZMLFTYWJNBRCIUS"



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		tuple[RotorPositionT, RotorSelectionT, dict[str, str]]:
    # Checks if there are 3 unique rotors

    if (unique_rotsel := len(set(lowerCamelCase_				)				)) < 3:
        _lowercase :							int   	=	F'''Please use 3 unique rotors (not {unique_rotsel})'''
        raise Exception(lowerCamelCase_				)

    # Checks if rotor positions are valid
    _lowercase	,       _lowercase	,       _lowercase :							Union[str, Any]   	=	rotpos
    if not 0 < rotorposa <= len(lowerCamelCase_				):
        _lowercase :							Union[str, Any]   	=	F'''First rotor position is not within range of 1..26 ({rotorposa}'''
        raise ValueError(lowerCamelCase_				)
    if not 0 < rotorposa <= len(lowerCamelCase_				):
        _lowercase :							Tuple   	=	F'''Second rotor position is not within range of 1..26 ({rotorposa})'''
        raise ValueError(lowerCamelCase_				)
    if not 0 < rotorposa <= len(lowerCamelCase_				):
        _lowercase :							str   	=	F'''Third rotor position is not within range of 1..26 ({rotorposa})'''
        raise ValueError(lowerCamelCase_				)

    # Validates string and returns dict
    _lowercase :							Optional[int]   	=	_plugboard(lowerCamelCase_				)

    return rotpos, rotsel, pbdict



def        UpperCamelCase_(   lowerCamelCase_				)					->		dict[str, str]:

    # tests the input string if it
    # a) is type string
    # b) has even length (so pairs can be made)
    if not isinstance(lowerCamelCase_							,				lowerCamelCase_				):
        _lowercase :							List[Any]   	=	F'''Plugboard setting isn\'t type string ({type(lowerCamelCase_				)})'''
        raise TypeError(lowerCamelCase_				)
    elif len(lowerCamelCase_				) % 2 != 0:
        _lowercase :							Optional[Any]   	=	F'''Odd number of symbols ({len(lowerCamelCase_				)})'''
        raise Exception(lowerCamelCase_				)
    elif pbstring == "":
        return {}

    pbstring.replace(' '							,				''				)

    # Checks if all characters are unique
    _lowercase :							List[Any]   	=	set()
    for i in pbstring:
        if i not in abc:
            _lowercase :							str   	=	F'''\'{i}\' not in list of symbols'''
            raise Exception(lowerCamelCase_				)
        elif i in tmppbl:
            _lowercase :							Tuple   	=	F'''Duplicate symbol ({i})'''
            raise Exception(lowerCamelCase_				)
        else:
            tmppbl.add(lowerCamelCase_				)
    del tmppbl

    # Created the dictionary
    _lowercase :							List[Any]   	=	{}
    for j in range(0							,				len(lowerCamelCase_				) - 1							,				2				):
        _lowercase :							str   	=	pbstring[j + 1]
        _lowercase :							Union[str, Any]   	=	pbstring[j]

    return pb



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_ = (rotora, rotora, rotora)							,				lowerCamelCase_ = ""							,				)					->		str:
    _lowercase :							int   	=	text.upper()
    _lowercase	,       _lowercase	,       _lowercase :							Optional[int]   	=	_validator(
        lowerCamelCase_							,				lowerCamelCase_							,				plugb.upper()				)

    _lowercase	,       _lowercase	,       _lowercase :							Union[str, Any]   	=	rotor_position
    _lowercase	,       _lowercase	,       _lowercase :							Optional[Any]   	=	rotor_selection
    rotorposa -= 1
    rotorposa -= 1
    rotorposa -= 1

    _lowercase :							Any   	=	[]

    # encryption/decryption process --------------------------
    for symbol in text:
        if symbol in abc:
            # 1st plugboard --------------------------
            if symbol in plugboard:
                _lowercase :							List[str]   	=	plugboard[symbol]

            # rotor ra --------------------------
            _lowercase :							Any   	=	abc.index(lowerCamelCase_				) + rotorposa
            _lowercase :							Any   	=	rotora[index % len(lowerCamelCase_				)]

            # rotor rb --------------------------
            _lowercase :							List[Any]   	=	abc.index(lowerCamelCase_				) + rotorposa
            _lowercase :							Any   	=	rotora[index % len(lowerCamelCase_				)]

            # rotor rc --------------------------
            _lowercase :							Tuple   	=	abc.index(lowerCamelCase_				) + rotorposa
            _lowercase :							Tuple   	=	rotora[index % len(lowerCamelCase_				)]

            # reflector --------------------------
            # this is the reason you don't need another machine to decipher

            _lowercase :							List[Any]   	=	reflector[symbol]

            # 2nd rotors
            _lowercase :							int   	=	abc[rotora.index(lowerCamelCase_				) - rotorposa]
            _lowercase :							str   	=	abc[rotora.index(lowerCamelCase_				) - rotorposa]
            _lowercase :							int   	=	abc[rotora.index(lowerCamelCase_				) - rotorposa]

            # 2nd plugboard
            if symbol in plugboard:
                _lowercase :							Optional[int]   	=	plugboard[symbol]

            # moves/resets rotor positions
            rotorposa += 1
            if rotorposa >= len(lowerCamelCase_				):
                _lowercase :							Optional[Any]   	=	0
                rotorposa += 1
            if rotorposa >= len(lowerCamelCase_				):
                _lowercase :							Any   	=	0
                rotorposa += 1
            if rotorposa >= len(lowerCamelCase_				):
                _lowercase :							Any   	=	0

        # else:
        #    pass
        #    Error could be also raised
        #    raise ValueError(
        #       'Invalid symbol('+repr(symbol)+')')
        result.append(lowerCamelCase_				)

    return "".join(lowerCamelCase_				)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE :   Optional[int]							      =				"This is my Python script that emulates the Enigma machine from WWII."
 SCREAMING_SNAKE_CASE :   Optional[int]							      =				(1, 1, 1)
 SCREAMING_SNAKE_CASE :   List[Any]							      =				"pictures"
 SCREAMING_SNAKE_CASE :   int							      =				(rotora, rotora, rotora)
 SCREAMING_SNAKE_CASE :   List[Any]							      =				enigma(message, rotor_pos, rotor_sel, pb)

 print("Encrypted message:", en)
 print("Decrypted message:", enigma(en, rotor_pos, rotor_sel, pb))


