


'''simple docstring'''
import os
from pathlib import Path



def 				lowerCAmelCase__	(       UpperCAmelCase    ,       UpperCAmelCase    ,       UpperCAmelCase    ,       UpperCAmelCase     ):






       """simple docstring"""





       snake_case__					:	Dict          =					{
           """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]
       snake_case__					:	Tuple          =					{
           """wmt19-de-en-6-6-base""": [0, 3_8.3_7],
           """wmt19-de-en-6-6-big""": [0, 3_9.9_0],
       }
       snake_case__					:	Tuple          =					f"""{src_lang}-{tgt_lang}"""

       snake_case__					:	Tuple          =					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=lowercase_    ,       exist_ok=lowercase_     )
       snake_case__					:	List[str]          =					os.path.join(lowercase_    ,       """README.md"""     )
       print(f"""Generating {path}"""     )
       with open(lowercase_    ,       """w"""    ,       encoding="""utf-8"""     ) as f:
              f.write(lowercase_     )


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

for model_name in ["wmt19-de-en-6-6-base", "wmt19-de-en-6-6-big"]:
     lowerCAmelCase__  =     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 subprocess
from argparse import ArgumentParser
from typing import List, Union

from huggingface_hub.hf_api import HfFolder, create_repo, whoami
from requests.exceptions import HTTPError

from . import BaseTransformersCLICommand





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					@staticmethod
					def 							__SCREAMING_SNAKE_CASE      (       __UpperCamelCase					):
							_snake_case      			=			parser.add_parser("login",    help="Log in using the same credentials as on huggingface.co"					)
							login_parser.set_defaults(func=lambda __UpperCamelCase					: LoginCommand(__UpperCamelCase					)					)
							_snake_case      			=			parser.add_parser("whoami",    help="Find out which huggingface.co account you are logged in as."					)
							whoami_parser.set_defaults(func=lambda __UpperCamelCase					: WhoamiCommand(__UpperCamelCase					)					)
							_snake_case      			=			parser.add_parser("logout",    help="Log out"					)
							logout_parser.set_defaults(func=lambda __UpperCamelCase					: LogoutCommand(__UpperCamelCase					)					)

							# new system: git-based repo system
							_snake_case      			=			parser.add_parser(
							    "repo",    help="Deprecated: use `huggingface-cli` instead. Commands to interact with your huggingface.co repos.",    )
							_snake_case      			=			repo_parser.add_subparsers(
							    help="Deprecated: use `huggingface-cli` instead. huggingface.co repos related commands"					)
							_snake_case      			=			repo_subparsers.add_parser(
							    "create",    help="Deprecated: use `huggingface-cli` instead. Create a new repo on huggingface.co"					)
							repo_create_parser.add_argument(
							    "name",    type=__UpperCamelCase,    help="Name for your model's repo. Will be namespaced under your username to build the model id.",    )
							repo_create_parser.add_argument("--organization",    type=__UpperCamelCase,    help="Optional: organization namespace."					)
							repo_create_parser.add_argument("-y",    "--yes",    action="store_true",    help="Optional: answer Yes to the prompt"					)
							repo_create_parser.set_defaults(func=lambda __UpperCamelCase					: RepoCreateCommand(__UpperCamelCase					)					)





class 	lowerCamelCase_				:




					'''simple docstring'''






					lowercase__       =					"""\u001b[1m"""
					lowercase__       =					"""\u001b[31m"""
					lowercase__       =					"""\u001b[90m"""
					lowercase__       =					"""\u001b[0m"""






					@classmethod
					def 							__SCREAMING_SNAKE_CASE      (       cls,    __UpperCamelCase					):
							return f'''{cls._bold}{s}{cls._reset}'''






					@classmethod
					def 							__SCREAMING_SNAKE_CASE      (       cls,    __UpperCamelCase					):
							return f'''{cls._bold}{cls._red}{s}{cls._reset}'''






					@classmethod
					def 							__SCREAMING_SNAKE_CASE      (       cls,    __UpperCamelCase					):
							return f'''{cls._gray}{s}{cls._reset}'''






def 						_lowercase						(      lowercase_		,				lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			[max(len(str(lowercase_    )    ) for x in col    ) for col in zip(*lowercase_		,				lowercase_    )]
		_snake_case      			=			("{{:{}}} " * len(lowercase_    )).format(*lowercase_    )
		_snake_case      			=			[]
		lines.append(row_format.format(*lowercase_    )    )
		lines.append(row_format.format(*["-" * w for w in col_widths]    )    )
		for row in rows:
				lines.append(row_format.format(*lowercase_    )    )
		return "\n".join(lowercase_    )





class 	lowerCamelCase_				:




					'''simple docstring'''






					def __init__(       self,    __UpperCamelCase					):
							_snake_case      			=			args





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					def 							__SCREAMING_SNAKE_CASE      (       self					):
							print(
							    ANSI.red(
							        "ERROR! `huggingface-cli login` uses an outdated login mechanism "
							        "that is not compatible with the Hugging Face Hub backend anymore. "
							        "Please use `huggingface-cli login instead."					)					)





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					def 							__SCREAMING_SNAKE_CASE      (       self					):
							print(
							    ANSI.red(
							        "WARNING! `transformers-cli whoami` is deprecated and will be removed in v5. Please use "
							        "`huggingface-cli whoami` instead."					)					)
							_snake_case      			=			HfFolder.get_token()
							if token is None:
									print("Not logged in"					)
									exit()
							try:
									_snake_case			,       _snake_case      			=			whoami(__UpperCamelCase					)
									print(__UpperCamelCase					)
									if orgs:
											print(ANSI.bold("orgs: "					),    ",".join(__UpperCamelCase					)					)
							except HTTPError as e:
									print(__UpperCamelCase					)
									print(ANSI.red(e.response.text					)					)
									exit(1					)





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					def 							__SCREAMING_SNAKE_CASE      (       self					):
							print(
							    ANSI.red(
							        "ERROR! `transformers-cli logout` uses an outdated logout mechanism "
							        "that is not compatible with the Hugging Face Hub backend anymore. "
							        "Please use `huggingface-cli logout instead."					)					)





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					def 							__SCREAMING_SNAKE_CASE      (       self					):
							print(
							    ANSI.red(
							        "WARNING! Managing repositories through transformers-cli is deprecated. "
							        "Please use `huggingface-cli` instead."					)					)
							_snake_case      			=			HfFolder.get_token()
							if token is None:
									print("Not logged in"					)
									exit(1					)
							try:
									_snake_case      			=			subprocess.check_output(["git", "--version"]					).decode("utf-8"					)
									print(ANSI.gray(stdout.strip()					)					)
							except FileNotFoundError:
									print("Looks like you do not have git installed, please install."					)

							try:
									_snake_case      			=			subprocess.check_output(["git-lfs", "--version"]					).decode("utf-8"					)
									print(ANSI.gray(stdout.strip()					)					)
							except FileNotFoundError:
									print(
									    ANSI.red(
									        "Looks like you do not have git-lfs installed, please install."
									        " You can install from https://git-lfs.github.com/."
									        " Then run `git lfs install` (you only have to do this once)."					)					)
							print(""					)

							_snake_case			,       _snake_case      			=			whoami(__UpperCamelCase					)
							_snake_case      			=			self.args.organization if self.args.organization is not None else user
							_snake_case      			=			f'''{namespace}/{self.args.name}'''
							print(f'''You are about to create {ANSI.bold(__UpperCamelCase					)}'''					)

							if not self.args.yes:
									_snake_case      			=			input("Proceed? [Y/n] "					).lower()
									if not (choice == "" or choice == "y" or choice == "yes"):
											print("Abort"					)
											exit()
							try:
									_snake_case      			=			create_repo(__UpperCamelCase,    name=self.args.name,    organization=self.args.organization					)
							except HTTPError as e:
									print(__UpperCamelCase					)
									print(ANSI.red(e.response.text					)					)
									exit(1					)
							print("\nYour repo now lives at:"					)
							print(f'''  {ANSI.bold(__UpperCamelCase					)}'''					)
							print("\nYou can clone it locally with the command below, and commit/push as usual."					)
							print(f'''\n  git clone {url}'''					)
							print(""					)





