



from __future__ import annotations

from random import random
from typing import Generic, TypeVar

UpperCAmelCase							 =					TypeVar("""KT""")
UpperCAmelCase							 =					TypeVar("""VT""")

class  __snake_case      (   Generic[KT, VT]):







							'''simple docstring'''






							def __init__(							self  ,  a_ = "root"  ,  a_ = None		):
										a__				      =		key
										a__				      =		value
										a__				      =		[]


							def __repr__(							self		):
										return F'''Node({self.key}: {self.value})'''







							@property
							def _a      (							self		):
										return len(self.forward		)




class  __snake_case      (   Generic[KT, VT]):







							'''simple docstring'''






							def __init__(							self  ,  a_ = 0.5  ,  a_ = 16		):
										a__				      =		Node[KT, VT]()
										a__				      =		0
										a__				      =		p
										a__				      =		max_level


							def __str__(							self		):
										a__				      =		list(self		)

										if len(UpperCamelCase__		) == 0:
													return F'''SkipList(level={self.level})'''

										a__				      =		max((len(str(UpperCamelCase__		)		) for item in items)  ,  default=4		)
										a__				      =		max(UpperCamelCase__  ,  4		) + 4

										a__				      =		self.head
										a__				      =		[]

										a__				      =		node.forward.copy()
										lines.append(F'''[{node.key}]'''.ljust(UpperCamelCase__  ,  """-"""		) + """* """ * len(UpperCamelCase__		)		)
										lines.append(""" """ * label_size + """| """ * len(UpperCamelCase__		)		)

										while len(node.forward		) != 0:
													a__				      =		node.forward[0]

													lines.append(
													    F'''[{node.key}]'''.ljust(UpperCamelCase__  ,  """-"""		)
													    + """ """.join(str(n.key		) if n.key == node.key else """|""" for n in forwards		)		)
													lines.append(""" """ * label_size + """| """ * len(UpperCamelCase__		)		)
													a__				      =		node.forward

										lines.append("""None""".ljust(UpperCamelCase__		) + """* """ * len(UpperCamelCase__		)		)
										return F'''SkipList(level={self.level})\n''' + "\n".join(UpperCamelCase__		)


							def __iter__(							self		):
										a__				      =		self.head

										while len(node.forward		) != 0:
													yield node.forward[0].key
													a__				      =		node.forward[0]


							def _a      (							self		):
										a__				      =		1
										while random() < self.p and level < self.max_level:
													level += 1

										return level


							def _a      (							self  ,  a_		):
										a__				      =		[]

										a__				      =		self.head

										for i in reversed(range(self.level		)		):
													# i < node.level - When node level is lesser than `i` decrement `i`.
													# node.forward[i].key < key - Jumping to node with key value higher
													#                             or equal to searched key would result
													#                             in skipping searched key.
													while i < node.level and node.forward[i].key < key:
																a__				      =		node.forward[i]
													# Each leftmost node (relative to searched node) will potentially have to
													# be updated.
													update_vector.append(UpperCamelCase__		)

										update_vector.reverse()  # Note that we were inserting values in reverse order.

										# len(node.forward) != 0 - If current node doesn't contain any further
										#                          references then searched key is not present.
										# node.forward[0].key == key - Next node key should be equal to search key
										#                              if key is present.
										if len(node.forward		) != 0 and node.forward[0].key == key:
													return node.forward[0], update_vector
										else:
													return None, update_vector


							def _a      (							self  ,  a_		):
										a__      ,			a__				      =		self._locate_node(UpperCamelCase__		)

										if node is not None:
													for i, update_node in enumerate(UpperCamelCase__		):
																# Remove or replace all references to removed node.
																if update_node.level > i and update_node.forward[i].key == key:
																			if node.level > i:
																						a__				      =		node.forward[i]
																			else:
																						a__				      =		update_node.forward[:i]


							def _a      (							self  ,  a_  ,  a_		):
										a__      ,			a__				      =		self._locate_node(UpperCamelCase__		)
										if node is not None:
													a__				      =		value
										else:
													a__				      =		self.random_level()

													if level > self.level:
																# After level increase we have to add additional nodes to head.
																for _ in range(self.level - 1  ,  UpperCamelCase__		):
																			update_vector.append(self.head		)
																a__				      =		level

													a__				      =		Node(UpperCamelCase__  ,  UpperCamelCase__		)

													for i, update_node in enumerate(update_vector[:level]		):
																# Change references to pass through new node.
																if update_node.level > i:
																			new_node.forward.append(update_node.forward[i]		)

																if update_node.level < i + 1:
																			update_node.forward.append(UpperCamelCase__		)
																else:
																			a__				      =		new_node







							def _a      (							self  ,  a_		):
										a__      ,			a__				      =		self._locate_node(UpperCamelCase__		)

										if node is not None:
													return node.value

										return None




def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()
			skip_list.insert("""Key1""" ,		3		)
			skip_list.insert("""Key2""" ,		12		)
			skip_list.insert("""Key3""" ,		41		)
			skip_list.insert("""Key4""" ,		-19		)

			a__				      =		skip_list.head
			a__				      =		{}
			while node.level != 0:
						a__				      =		node.forward[0]
						a__				      =		node.value

			assert len(__a		) == 4
			assert all_values["Key1"] == 3
			assert all_values["Key2"] == 12
			assert all_values["Key3"] == 41
			assert all_values["Key4"] == -19

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()
			skip_list.insert("""Key1""" ,		10		)
			skip_list.insert("""Key1""" ,		12		)

			skip_list.insert("""Key5""" ,		7		)
			skip_list.insert("""Key7""" ,		10		)
			skip_list.insert("""Key10""" ,		5		)

			skip_list.insert("""Key7""" ,		7		)
			skip_list.insert("""Key5""" ,		5		)
			skip_list.insert("""Key10""" ,		10		)

			a__				      =		skip_list.head
			a__				      =		{}
			while node.level != 0:
						a__				      =		node.forward[0]
						a__				      =		node.value

			if len(__a		) != 4:
						print()
			assert len(__a		) == 4
			assert all_values["Key1"] == 12
			assert all_values["Key7"] == 7
			assert all_values["Key5"] == 5
			assert all_values["Key10"] == 10

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()
			assert skip_list.find("""Some key"""		) is None

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()

			skip_list.insert("""Key2""" ,		20		)
			assert skip_list.find("""Key2"""		) == 20

			skip_list.insert("""Some Key""" ,		10		)
			skip_list.insert("""Key2""" ,		8		)
			skip_list.insert("""V""" ,		13		)

			assert skip_list.find("""Y"""		) is None
			assert skip_list.find("""Key2"""		) == 8
			assert skip_list.find("""Some Key"""		) == 10
			assert skip_list.find("""V"""		) == 13

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()
			skip_list.delete("""Some key"""		)

			assert len(skip_list.head.forward		) == 0

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()

			skip_list.insert("""Key1""" ,		12		)
			skip_list.insert("""V""" ,		13		)
			skip_list.insert("""X""" ,		14		)
			skip_list.insert("""Key2""" ,		15		)

			skip_list.delete("""V"""		)
			skip_list.delete("""Key2"""		)

			assert skip_list.find("""V"""		) is None
			assert skip_list.find("""Key2"""		) is None

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()

			skip_list.insert("""Key1""" ,		12		)
			skip_list.insert("""V""" ,		13		)
			skip_list.insert("""X""" ,		14		)
			skip_list.insert("""Key2""" ,		15		)

			skip_list.delete("""V"""		)
			assert skip_list.find("""V"""		) is None
			assert skip_list.find("""X"""		) == 14
			assert skip_list.find("""Key1"""		) == 12
			assert skip_list.find("""Key2"""		) == 15

			skip_list.delete("""X"""		)
			assert skip_list.find("""V"""		) is None
			assert skip_list.find("""X"""		) is None
			assert skip_list.find("""Key1"""		) == 12
			assert skip_list.find("""Key2"""		) == 15

			skip_list.delete("""Key1"""		)
			assert skip_list.find("""V"""		) is None
			assert skip_list.find("""X"""		) is None
			assert skip_list.find("""Key1"""		) is None
			assert skip_list.find("""Key2"""		) == 15

			skip_list.delete("""Key2"""		)
			assert skip_list.find("""V"""		) is None
			assert skip_list.find("""X"""		) is None
			assert skip_list.find("""Key1"""		) is None
			assert skip_list.find("""Key2"""		) is None

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()

			skip_list.insert("""Key1""" ,		12		)
			skip_list.insert("""V""" ,		13		)
			skip_list.insert("""X""" ,		142		)
			skip_list.insert("""Key2""" ,		15		)

			skip_list.delete("""X"""		)

			def traverse_keys(__a     :				Union[str, Any]		):
						yield node.key
						for forward_node in node.forward:
									yield from traverse_keys(__a		)

			assert len(set(traverse_keys(skip_list.head		)		)		) == 4

def 			A_      (	):

			"""simple docstring"""
			def is_sorted(__a     :				Tuple		):
						return all(next_item >= item for item, next_item in zip(__a ,		lst[1:]		)		)

			a__				      =		SkipList()
			for i in range(10		):
						skip_list.insert(__a ,		__a		)
			assert is_sorted(list(__a		)		)
			skip_list.delete(5		)
			skip_list.delete(8		)
			skip_list.delete(2		)
			assert is_sorted(list(__a		)		)
			skip_list.insert(-12 ,		-12		)
			skip_list.insert(77 ,		77		)
			assert is_sorted(list(__a		)		)

def 			A_      (	):

			"""simple docstring"""
			for _ in range(100		):
						# Repeat test 100 times due to the probabilistic nature of skip list
						# random values == random bugs
						test_insert()
						test_insert_overrides_existing_value()

						test_searching_empty_list_returns_none()
						test_search()

						test_deleting_item_from_empty_list_do_nothing()
						test_deleted_items_are_not_founded_by_find_method()
						test_delete_removes_only_given_key()
						test_delete_doesnt_leave_dead_nodes()

						test_iter_always_yields_sorted_values()

def 			A_      (	):

			"""simple docstring"""
			a__				      =		SkipList()
			skip_list.insert(2 ,		"""2"""		)
			skip_list.insert(4 ,		"""4"""		)
			skip_list.insert(6 ,		"""4"""		)
			skip_list.insert(4 ,		"""5"""		)
			skip_list.insert(8 ,		"""4"""		)
			skip_list.insert(9 ,		"""4"""		)

			skip_list.delete(4		)

			print(__a		)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()






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

import os
from pathlib import Path

def 			A_      (	__a     :				List[Any] ,		__a     :				List[str] ,		__a     :				Union[str, Any]		):

				"""simple docstring"""
				a__				      =		{
				    """en""": """Machine learning is great, isn't it?""",
				    """ru""": """Машинное обучение - это здорово, не так ли?""",
				    """de""": """Maschinelles Lernen ist großartig, oder?""",
				}

				# BLUE scores as follows:
				# "pair": [fairseq, transformers]
				a__				      =		{
				    """ru-en""": ["""[41.3](http://matrix.statmt.org/matrix/output/1907?run_id=6937)""", """39.20"""],
				    """en-ru""": ["""[36.4](http://matrix.statmt.org/matrix/output/1914?run_id=6724)""", """33.47"""],
				    """en-de""": ["""[43.1](http://matrix.statmt.org/matrix/output/1909?run_id=6862)""", """42.83"""],
				    """de-en""": ["""[42.3](http://matrix.statmt.org/matrix/output/1902?run_id=6750)""", """41.35"""],
				}
				a__				      =		F'''{src_lang}-{tgt_lang}'''

				a__				      =		F'''
---
language: 
- {src_lang}
- {tgt_lang}
thumbnail:
tags:
- translation
- wmt19
- facebook
license: apache-2.0
datasets:
- wmt19
metrics:
- bleu
---

# FSMT

## Model description

This is a ported version of [fairseq wmt19 transformer](https://github.com/pytorch/fairseq/blob/master/examples/wmt19/README.md) for {src_lang}-{tgt_lang}.

For more details, please see, [Facebook FAIR\'s WMT19 News Translation Task Submission](https://arxiv.org/abs/1907.06616).

The abbreviation FSMT stands for FairSeqMachineTranslation

All four models are available:

* [wmt19-en-ru](https://huggingface.co/facebook/wmt19-en-ru)
* [wmt19-ru-en](https://huggingface.co/facebook/wmt19-ru-en)
* [wmt19-en-de](https://huggingface.co/facebook/wmt19-en-de)
* [wmt19-de-en](https://huggingface.co/facebook/wmt19-de-en)

## Intended uses & limitations

#### How to use

```python
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
mname = "facebook/wmt19-{src_lang}-{tgt_lang}"
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

- The original (and this ported model) doesn\'t seem to handle well inputs with repeated sub-phrases, [content gets truncated](https://discuss.huggingface.co/t/issues-with-translating-inputs-containing-repeated-phrases/981)

## Training data

Pretrained weights were left identical to the original model released by fairseq. For more details, please, see the [paper](https://arxiv.org/abs/1907.06616).

## Eval results

pair   | fairseq | transformers
-------|---------|----------
{pair}  | {scores[pair][0]} | {scores[pair][1]}

The score is slightly below the score reported by `fairseq`, since `transformers`` currently doesn\'t support:
- model ensemble, therefore the best performing checkpoint was ported (``model4.pt``).
- re-ranking

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=15
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 $PAIR
PYTHONPATH="src:examples/seq2seq" python examples/seq2seq/run_eval.py facebook/wmt19-$PAIR $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
```
note: fairseq reports using a beam of 50, so you should get a slightly higher score if re-run with `--num_beams 50`.

## 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

```bibtex
@inproceedings{{...,
  year={{2020}},
  title={{Facebook FAIR\'s WMT19 News Translation Task Submission}},
  author={{Ng, Nathan and Yee, Kyra and Baevski, Alexei and Ott, Myle and Auli, Michael and Edunov, Sergey}},
  booktitle={{Proc. of WMT}},
}}
```


## TODO

- port model ensemble (fairseq uses 4 model checkpoints)

'''
				os.makedirs(__a ,		exist_ok=__a		)
				a__				      =		os.path.join(__a ,		"""README.md"""		)
				print(F'''Generating {path}'''		)
				with open(__a ,		"""w""" ,		encoding="""utf-8"""		) as f:
								f.write(__a		)


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

for model_name in ["wmt19-ru-en", "wmt19-en-ru", "wmt19-en-de", "wmt19-de-en"]:
	UpperCAmelCase ,       UpperCAmelCase ,       UpperCAmelCase							 =					model_name.split("""-""")
	UpperCAmelCase							 =					model_cards_dir / """facebook""" / model_name
	write_model_card(model_card_dir, src_lang=src_lang, tgt_lang=tgt_lang)

