




"""simple docstring"""

import json
import os
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A							=     logging.get_logger(__name__)

__A							=     {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

__A							=     {
    "vocab_file": {
        "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json",
    },
    "merges_file": {"microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt"},
}

__A							=     {
    "microsoft/biogpt": 1_024,
}



def 					UpperCamelCase__       (						lowercase__					:       Optional[int]				):
		snake_case						:  Tuple        =			set()
		snake_case						:  Tuple        =			word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)				)
				snake_case						:  Optional[Any]        =			char
		return pairs
class      lowerCamelCase__      (					lowerCamelCase_     ):
			a__	: str        =       VOCAB_FILES_NAMES
			a__	: List[Any]        =       PRETRAINED_VOCAB_FILES_MAP
			a__	: Optional[int]        =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			a__	: Union[str, Any]        =       ["""input_ids""", """attention_mask"""]


			def __init__(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE="<unk>"			,	SCREAMING_SNAKE_CASE="<s>"			,	SCREAMING_SNAKE_CASE="</s>"			,	SCREAMING_SNAKE_CASE="</s>"			,	SCREAMING_SNAKE_CASE="<pad>"			,	**SCREAMING_SNAKE_CASE			,	):



					"""simple docstring"""







					super().__init__(
					    bos_token=SCREAMING_SNAKE_CASE			,	eos_token=SCREAMING_SNAKE_CASE			,	sep_token=SCREAMING_SNAKE_CASE			,	unk_token=SCREAMING_SNAKE_CASE			,	pad_token=SCREAMING_SNAKE_CASE			,	**SCREAMING_SNAKE_CASE			,	)

					try:
							import sacremoses
					except ImportError:
							raise ImportError(
							    "You need to install sacremoses to use BioGptTokenizer. "
							    "See https://pypi.org/project/sacremoses/ for installation."							)

					snake_case						:  int        =			"en"
					snake_case						:  List[Any]        =			sacremoses
					# cache of sm.MosesTokenizer instance
					snake_case						:  Optional[int]        =			{}
					snake_case						:  List[Any]        =			{}
					with open(SCREAMING_SNAKE_CASE			,	encoding="utf-8"							) as vocab_handle:
							snake_case						:  int        =			json.load(SCREAMING_SNAKE_CASE							)
					snake_case						:  Union[str, Any]        =			{v: k for k, v in self.encoder.items()}
					with open(SCREAMING_SNAKE_CASE			,	encoding="utf-8"							) as merges_handle:
							snake_case						:  Optional[Any]        =			merges_handle.read().split("\n"							)[:-1]
					snake_case						:  str        =			[tuple(merge.split()[:2]							) for merge in merges]
					snake_case						:  Any        =			dict(zip(SCREAMING_SNAKE_CASE			,	range(len(SCREAMING_SNAKE_CASE							)							)							)							)
					snake_case						:  Union[str, Any]        =			{}


			@property
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					return len(self.encoder							)


			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					return dict(self.encoder			,	**self.added_tokens_encoder							)


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					if lang not in self.cache_moses_tokenizer:
							snake_case						:  Dict        =			self.sm.MosesTokenizer(lang=SCREAMING_SNAKE_CASE							)
							snake_case						:  List[str]        =			moses_tokenizer
					return self.cache_moses_tokenizer[lang].tokenize(
					    SCREAMING_SNAKE_CASE			,	aggressive_dash_splits=SCREAMING_SNAKE_CASE			,	return_str=SCREAMING_SNAKE_CASE			,	escape=SCREAMING_SNAKE_CASE							)


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					if lang not in self.cache_moses_detokenizer:
							snake_case						:  Optional[int]        =			self.sm.MosesDetokenizer(lang=SCREAMING_SNAKE_CASE							)
							snake_case						:  Optional[Any]        =			moses_detokenizer
					return self.cache_moses_detokenizer[lang].detokenize(SCREAMING_SNAKE_CASE							)


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case						:  Optional[int]        =			tuple(token[:-1]							) + (token[-1] + "</w>",)
					if token in self.cache:
							return self.cache[token]
					snake_case						:  str        =			get_pairs(SCREAMING_SNAKE_CASE							)

					if not pairs:
							return token + "</w>"

					while True:
							snake_case						:  List[Any]        =			min(SCREAMING_SNAKE_CASE			,	key=lambda SCREAMING_SNAKE_CASE							: self.bpe_ranks.get(SCREAMING_SNAKE_CASE			,	float("inf"							)							)							)
							if bigram not in self.bpe_ranks:
									break
							snake_case						:  List[Any]        =			bigram
							snake_case						:  int        =			[]
							snake_case						:  List[Any]        =			0
							while i < len(SCREAMING_SNAKE_CASE							):
									try:
											snake_case						:  str        =			word.index(SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE							)
									except ValueError:
											new_word.extend(word[i:]							)
											break
									else:
											new_word.extend(word[i:j]							)
											snake_case						:  Any        =			j

									if word[i] == first and i < len(SCREAMING_SNAKE_CASE							) - 1 and word[i + 1] == second:
											new_word.append(first + second							)
											i += 2
									else:
											new_word.append(word[i]							)
											i += 1
							snake_case						:  Optional[int]        =			tuple(SCREAMING_SNAKE_CASE							)
							snake_case						:  Optional[Any]        =			new_word
							if len(SCREAMING_SNAKE_CASE							) == 1:
									break
							else:
									snake_case						:  Union[str, Any]        =			get_pairs(SCREAMING_SNAKE_CASE							)
					snake_case						:  Optional[int]        =			" ".join(SCREAMING_SNAKE_CASE							)
					if word == "\n  </w>":
							snake_case						:  Tuple        =			"\n</w>"
					snake_case						:  Union[str, Any]        =			word
					return word


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE=False							):



					"""simple docstring"""







					if bypass_tokenizer:
							snake_case						:  Dict        =			text.split()
					else:
							snake_case						:  int        =			self.moses_tokenize(SCREAMING_SNAKE_CASE			,	self.lang							)

					snake_case						:  str        =			[]
					for token in text:
							if token:
									split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE							).split(" "							)							)							)

					return split_tokens


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return self.encoder.get(SCREAMING_SNAKE_CASE			,	self.encoder.get(self.unk_token							)							)


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					return self.decoder.get(SCREAMING_SNAKE_CASE			,	self.unk_token							)


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case						:  Optional[int]        =			[t.replace(" "			,	""							).replace("</w>"			,	" "							) for t in tokens]
					snake_case						:  Dict        =			"".join(SCREAMING_SNAKE_CASE							).split()
					# detokenize
					snake_case						:  str        =			self.moses_detokenize(SCREAMING_SNAKE_CASE			,	self.lang							)
					return text


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE = None							):



					"""simple docstring"""







					if token_ids_a is None:
							return [self.sep_token_id] + token_ids_a
					snake_case						:  Union[str, Any]        =			[self.sep_token_id]
					return sep + token_ids_a + sep + token_ids_a


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE = None			,	SCREAMING_SNAKE_CASE = False							):



					"""simple docstring"""







					if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=SCREAMING_SNAKE_CASE			,	token_ids_a=SCREAMING_SNAKE_CASE			,	already_has_special_tokens=SCREAMING_SNAKE_CASE							)
					# no bos used in fairseq
					if token_ids_a is not None:
							return [1] + ([0] * len(SCREAMING_SNAKE_CASE							)) + [1] + ([0] * len(SCREAMING_SNAKE_CASE							))
					return [1] + ([0] * len(SCREAMING_SNAKE_CASE							))


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE = None							):



					"""simple docstring"""







					snake_case						:  str        =			[self.sep_token_id]

					# no bos used in fairseq
					if token_ids_a is None:
							return len(token_ids_a + sep							) * [0]
					return len(token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1]


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE = None							):



					"""simple docstring"""







					if not os.path.isdir(SCREAMING_SNAKE_CASE							):
							logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
							return
					snake_case						:  List[Any]        =			os.path.join(
					    SCREAMING_SNAKE_CASE			,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)
					snake_case						:  Optional[int]        =			os.path.join(
					    SCREAMING_SNAKE_CASE			,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]							)

					with open(SCREAMING_SNAKE_CASE			,	"w"			,	encoding="utf-8"							) as f:
							f.write(json.dumps(self.encoder			,	indent=2			,	sort_keys=SCREAMING_SNAKE_CASE			,	ensure_ascii=SCREAMING_SNAKE_CASE							) + "\n"							)

					snake_case						:  Dict        =			0
					with open(SCREAMING_SNAKE_CASE			,	"w"			,	encoding="utf-8"							) as writer:
							for bpe_tokens, token_index in sorted(self.bpe_ranks.items()			,	key=lambda SCREAMING_SNAKE_CASE							: kv[1]							):
									if index != token_index:
											logger.warning(
											    F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
											    " Please check that the tokenizer is not corrupted!"							)
											snake_case						:  Optional[int]        =			token_index
									writer.write(" ".join(SCREAMING_SNAKE_CASE							) + "\n"							)
									index += 1

					return vocab_file, merge_file


			def __getstate__(       self							):



					"""simple docstring"""







					snake_case						:  int        =			self.__dict__.copy()
					snake_case						:  Optional[int]        =			None
					return state



			def __setstate__(       self			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case						:  Dict        =			d

					try:
							import sacremoses
					except ImportError:
							raise ImportError(
							    "You need to install sacremoses to use XLMTokenizer. "
							    "See https://pypi.org/project/sacremoses/ for installation."							)

					snake_case						:  List[str]        =			sacremoses







"""simple docstring"""

import unittest

import pytest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    MBartaaTokenizerFast,
    MBartConfig,
    MBartForConditionalGeneration,
    TranslationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch, slow

from .test_pipelines_common import ANY
@is_pipeline_test
class      lowerCamelCase__      (					unittest.TestCase     ):
			a__	: List[str]        =       MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
			a__	: List[Any]        =       TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					if isinstance(model.config			,	SCREAMING_SNAKE_CASE							):
							snake_case     ,			snake_case						:  Optional[Any]        =			list(tokenizer.lang_code_to_id.keys()							)[:2]
							snake_case						:  Tuple        =			TranslationPipeline(model=SCREAMING_SNAKE_CASE			,	tokenizer=SCREAMING_SNAKE_CASE			,	src_lang=SCREAMING_SNAKE_CASE			,	tgt_lang=SCREAMING_SNAKE_CASE							)
					else:
							snake_case						:  List[Any]        =			TranslationPipeline(model=SCREAMING_SNAKE_CASE			,	tokenizer=SCREAMING_SNAKE_CASE							)
					return translator, ["Some string", "Some other text"]


			def 							lowerCamelCase_			(       self			,	SCREAMING_SNAKE_CASE			,	SCREAMING_SNAKE_CASE							):



					"""simple docstring"""







					snake_case						:  List[str]        =			translator("Some string"							)
					self.assertEqual(SCREAMING_SNAKE_CASE			,	[{"translation_text": ANY(SCREAMING_SNAKE_CASE							)}]							)

					snake_case						:  Optional[Any]        =			translator(["Some string"]							)
					self.assertEqual(SCREAMING_SNAKE_CASE			,	[{"translation_text": ANY(SCREAMING_SNAKE_CASE							)}]							)

					snake_case						:  List[Any]        =			translator(["Some string", "other string"]							)
					self.assertEqual(SCREAMING_SNAKE_CASE			,	[{"translation_text": ANY(SCREAMING_SNAKE_CASE							)}, {"translation_text": ANY(SCREAMING_SNAKE_CASE							)}]							)


			@require_torch
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  Optional[int]        =			pipeline("translation_en_to_ro"			,	model="patrickvonplaten/t5-tiny-random"			,	framework="pt"							)
					snake_case						:  Union[str, Any]        =			translator("This is a test string"			,	max_length=20							)
					self.assertEqual(
					    SCREAMING_SNAKE_CASE			,	[
					        {
					            "translation_text": (
					                "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
					                " Beide Beide"
					            )
					        }
					    ]			,	)


			@require_tf
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  int        =			pipeline("translation_en_to_ro"			,	model="patrickvonplaten/t5-tiny-random"			,	framework="tf"							)
					snake_case						:  int        =			translator("This is a test string"			,	max_length=20							)
					self.assertEqual(
					    SCREAMING_SNAKE_CASE			,	[
					        {
					            "translation_text": (
					                "Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide"
					                " Beide Beide"
					            )
					        }
					    ]			,	)


			@require_torch
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  List[Any]        =			pipeline("translation_en_to_de"			,	model="patrickvonplaten/t5-tiny-random"			,	framework="pt"							)
					snake_case						:  List[str]        =			translator("This is a test string"			,	max_length=20							)
					self.assertEqual(
					    SCREAMING_SNAKE_CASE			,	[
					        {
					            "translation_text": (
					                "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
					                " urine urine urine urine urine urine urine"
					            )
					        }
					    ]			,	)



			@require_tf
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  List[str]        =			pipeline("translation_en_to_de"			,	model="patrickvonplaten/t5-tiny-random"			,	framework="tf"							)
					snake_case						:  Tuple        =			translator("This is a test string"			,	max_length=20							)
					self.assertEqual(
					    SCREAMING_SNAKE_CASE			,	[
					        {
					            "translation_text": (
					                "monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine"
					                " urine urine urine urine urine urine urine"
					            )
					        }
					    ]			,	)







class      lowerCamelCase__      (					unittest.TestCase     ):


			@require_torch
			@slow
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					with self.assertRaises(SCREAMING_SNAKE_CASE							):
							pipeline(task="translation_cn_to_ar"							)

					# but we do for this one
					snake_case						:  List[str]        =			pipeline(task="translation_en_to_de"							)
					self.assertEqual(translator._preprocess_params["src_lang"]			,	"en"							)
					self.assertEqual(translator._preprocess_params["tgt_lang"]			,	"de"							)


			@require_torch
			@slow
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  Any        =			MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"							)
					snake_case						:  Union[str, Any]        =			MBartaaTokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt"							)

					snake_case						:  Dict        =			pipeline(task="translation"			,	model=SCREAMING_SNAKE_CASE			,	tokenizer=SCREAMING_SNAKE_CASE							)
					# Missing src_lang, tgt_lang
					with self.assertRaises(SCREAMING_SNAKE_CASE							):
							translator("This is a test"							)

					snake_case						:  Optional[int]        =			translator("This is a test"			,	src_lang="en_XX"			,	tgt_lang="ar_AR"							)
					self.assertEqual(SCREAMING_SNAKE_CASE			,	[{"translation_text": "هذا إختبار"}]							)

					snake_case						:  Dict        =			translator("This is a test"			,	src_lang="en_XX"			,	tgt_lang="hi_IN"							)
					self.assertEqual(SCREAMING_SNAKE_CASE			,	[{"translation_text": "यह एक परीक्षण है"}]							)

					# src_lang, tgt_lang can be defined at pipeline call time
					snake_case						:  Tuple        =			pipeline(task="translation"			,	model=SCREAMING_SNAKE_CASE			,	tokenizer=SCREAMING_SNAKE_CASE			,	src_lang="en_XX"			,	tgt_lang="ar_AR"							)
					snake_case						:  int        =			translator("This is a test"							)
					self.assertEqual(SCREAMING_SNAKE_CASE			,	[{"translation_text": "هذا إختبار"}]							)


			@require_torch
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  int        =			"patrickvonplaten/t5-tiny-random"
					snake_case						:  Tuple        =			pipeline(task="translation_cn_to_ar"			,	model=SCREAMING_SNAKE_CASE							)
					self.assertEqual(translator._preprocess_params["src_lang"]			,	"cn"							)
					self.assertEqual(translator._preprocess_params["tgt_lang"]			,	"ar"							)


			@require_torch
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					snake_case						:  str        =			"patrickvonplaten/t5-tiny-random"
					with pytest.warns(SCREAMING_SNAKE_CASE			,	match=r".*translation_en_to_de.*"							):
							snake_case						:  Dict        =			pipeline(task="translation"			,	model=SCREAMING_SNAKE_CASE							)
					self.assertEqual(translator.task			,	"translation_en_to_de"							)
					self.assertEqual(translator._preprocess_params["src_lang"]			,	"en"							)
					self.assertEqual(translator._preprocess_params["tgt_lang"]			,	"de"							)



			@require_torch
			def 							lowerCamelCase_			(       self							):



					"""simple docstring"""







					with self.assertRaises(SCREAMING_SNAKE_CASE							):
							pipeline(task="translation"							)

