



import unittest

import numpy as np
import timeout_decorator  # noqa

from transformers import MarianConfig, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor


if is_flax_available():
	import os

	# The slow tests are often failing with OOM error on GPU
	# This makes JAX allocate exactly what is needed on demand, and deallocate memory that is no longer needed
	# but will be slower as stated here https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html
	A__       =			'platform'

	import jax
	import jax.numpy as jnp

	from transformers import MarianTokenizer
	from transformers.models.marian.modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, shift_tokens_right


def 						_UpperCAmelCase							( snake_case      ,		snake_case      ,		snake_case=None      ,		snake_case=None      ,		snake_case=None      ,		snake_case=None      ,		snake_case=None      ,		snake_case=None      ,		):





					"""simple docstring"""

					if attention_mask is None:
										_lowerCAmelCase         =       np.where(input_ids != config.pad_token_id      ,		1      ,		0     )
					if decoder_attention_mask is None:
										_lowerCAmelCase         =       np.where(decoder_input_ids != config.pad_token_id      ,		1      ,		0     )
					if head_mask is None:
										_lowerCAmelCase         =       np.ones((config.encoder_layers, config.encoder_attention_heads)     )
					if decoder_head_mask is None:
										_lowerCAmelCase         =       np.ones((config.decoder_layers, config.decoder_attention_heads)     )
					if cross_attn_head_mask is None:
										_lowerCAmelCase         =       np.ones((config.decoder_layers, config.decoder_attention_heads)     )
					return {
					    "input_ids": input_ids,
					    "decoder_input_ids": decoder_input_ids,
					    "attention_mask": attention_mask,
					    "decoder_attention_mask": attention_mask,
					}





class    __lowerCAmelCase					:




				def __init__(				self		,							_snake_case		,							_snake_case=13		,							_snake_case=7		,							_snake_case=True		,							_snake_case=False		,							_snake_case=99		,							_snake_case=16		,							_snake_case=2		,							_snake_case=4		,							_snake_case=4		,							_snake_case="gelu"		,							_snake_case=0.1		,							_snake_case=0.1		,							_snake_case=32		,							_snake_case=2		,							_snake_case=1		,							_snake_case=0		,							_snake_case=0.02		,							):



									"""simple docstring"""





									_lowerCAmelCase         =       parent
									_lowerCAmelCase         =       batch_size
									_lowerCAmelCase         =       seq_length
									_lowerCAmelCase         =       is_training
									_lowerCAmelCase         =       use_labels
									_lowerCAmelCase         =       vocab_size
									_lowerCAmelCase         =       hidden_size
									_lowerCAmelCase         =       num_hidden_layers
									_lowerCAmelCase         =       num_attention_heads
									_lowerCAmelCase         =       intermediate_size
									_lowerCAmelCase         =       hidden_act
									_lowerCAmelCase         =       hidden_dropout_prob
									_lowerCAmelCase         =       attention_probs_dropout_prob
									_lowerCAmelCase         =       max_position_embeddings
									_lowerCAmelCase         =       eos_token_id
									_lowerCAmelCase         =       pad_token_id
									_lowerCAmelCase         =       bos_token_id
									_lowerCAmelCase         =       initializer_range




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       np.clip(ids_tensor([self.batch_size, self.seq_length - 1]		,							self.vocab_size						)		,							3		,							self.vocab_size						)
									_lowerCAmelCase         =       np.concatenate((input_ids, 2 * np.ones((self.batch_size, 1)		,							dtype=np.intaa						))		,							-1						)

									_lowerCAmelCase         =       shift_tokens_right(_UpperCAmelCase		,							1		,							2						)

									_lowerCAmelCase         =       MarianConfig(
									    vocab_size=self.vocab_size		,							d_model=self.hidden_size		,							encoder_layers=self.num_hidden_layers		,							decoder_layers=self.num_hidden_layers		,							encoder_attention_heads=self.num_attention_heads		,							decoder_attention_heads=self.num_attention_heads		,							encoder_ffn_dim=self.intermediate_size		,							decoder_ffn_dim=self.intermediate_size		,							dropout=self.hidden_dropout_prob		,							attention_dropout=self.attention_probs_dropout_prob		,							max_position_embeddings=self.max_position_embeddings		,							eos_token_id=self.eos_token_id		,							bos_token_id=self.bos_token_id		,							pad_token_id=self.pad_token_id		,							initializer_range=self.initializer_range		,							use_cache=_UpperCAmelCase		,							)
									_lowerCAmelCase         =       prepare_marian_inputs_dict(_UpperCAmelCase		,							_UpperCAmelCase		,							_UpperCAmelCase						)
									return config, inputs_dict




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase      ,      _lowerCAmelCase         =       self.prepare_config_and_inputs()
									return config, inputs_dict




				def 				snake_case  (				self		,							_snake_case		,							_snake_case		,							_snake_case						):



									"""simple docstring"""





									_lowerCAmelCase         =       20
									_lowerCAmelCase         =       model_class_name(_UpperCAmelCase						)

									_lowerCAmelCase         =       model.encode(inputs_dict["""input_ids"""]						)

									_lowerCAmelCase      ,      _lowerCAmelCase         =       (
									    inputs_dict["""decoder_input_ids"""],
									    inputs_dict["""decoder_attention_mask"""],
									)

									_lowerCAmelCase         =       model.init_cache(decoder_input_ids.shape[0]		,							_UpperCAmelCase		,							_UpperCAmelCase						)
									_lowerCAmelCase         =       jnp.ones((decoder_input_ids.shape[0], max_decoder_length)		,							dtype="""i4"""						)

									_lowerCAmelCase         =       jnp.broadcast_to(
									    jnp.arange(decoder_input_ids.shape[-1] - 1						)[None, :]		,							(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)		,							)
									_lowerCAmelCase         =       model.decode(
									    decoder_input_ids[:, :-1]		,							_UpperCAmelCase		,							decoder_attention_mask=_UpperCAmelCase		,							past_key_values=_UpperCAmelCase		,							decoder_position_ids=_UpperCAmelCase		,							)

									_lowerCAmelCase         =       jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]		,							dtype="""i4"""						)
									_lowerCAmelCase         =       model.decode(
									    decoder_input_ids[:, -1:]		,							_UpperCAmelCase		,							decoder_attention_mask=_UpperCAmelCase		,							past_key_values=outputs_cache.past_key_values		,							decoder_position_ids=_UpperCAmelCase		,							)

									_lowerCAmelCase         =       model.decode(_UpperCAmelCase		,							_UpperCAmelCase						)

									_lowerCAmelCase         =       np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])						)						)
									self.parent.assertTrue(diff < 1e-3		,							msg=F'Max diff is {diff}'						)




				def 				snake_case  (				self		,							_snake_case		,							_snake_case		,							_snake_case						):



									"""simple docstring"""





									_lowerCAmelCase         =       20
									_lowerCAmelCase         =       model_class_name(_UpperCAmelCase						)

									_lowerCAmelCase         =       model.encode(inputs_dict["""input_ids"""]						)

									_lowerCAmelCase      ,      _lowerCAmelCase         =       (
									    inputs_dict["""decoder_input_ids"""],
									    inputs_dict["""decoder_attention_mask"""],
									)

									_lowerCAmelCase         =       jnp.concatenate(
									    [
									        decoder_attention_mask,
									        jnp.zeros((decoder_attention_mask.shape[0], max_decoder_length - decoder_attention_mask.shape[1])						),
									    ]		,							axis=-1		,							)

									_lowerCAmelCase         =       model.init_cache(decoder_input_ids.shape[0]		,							_UpperCAmelCase		,							_UpperCAmelCase						)
									_lowerCAmelCase         =       jnp.broadcast_to(
									    jnp.arange(decoder_input_ids.shape[-1] - 1						)[None, :]		,							(decoder_input_ids.shape[0], decoder_input_ids.shape[-1] - 1)		,							)

									_lowerCAmelCase         =       model.decode(
									    decoder_input_ids[:, :-1]		,							_UpperCAmelCase		,							decoder_attention_mask=_UpperCAmelCase		,							past_key_values=_UpperCAmelCase		,							decoder_position_ids=_UpperCAmelCase		,							)
									_lowerCAmelCase         =       jnp.array(decoder_input_ids.shape[0] * [[decoder_input_ids.shape[-1] - 1]]		,							dtype="""i4"""						)
									_lowerCAmelCase         =       model.decode(
									    decoder_input_ids[:, -1:]		,							_UpperCAmelCase		,							past_key_values=outputs_cache.past_key_values		,							decoder_attention_mask=_UpperCAmelCase		,							decoder_position_ids=_UpperCAmelCase		,							)

									_lowerCAmelCase         =       model.decode(_UpperCAmelCase		,							_UpperCAmelCase		,							decoder_attention_mask=_UpperCAmelCase						)

									_lowerCAmelCase         =       np.max(np.abs((outputs_cache_next[0][:, -1, :5] - outputs[0][:, -1, :5])						)						)
									self.parent.assertTrue(diff < 1e-3		,							msg=F'Max diff is {diff}'						)





@require_flax
class    __lowerCAmelCase					(	lowerCamelCase__			,		unittest.TestCase			,		lowerCamelCase__			):
				__lowerCamelCase					=							True
				__lowerCamelCase					=							(FlaxMarianModel, FlaxMarianMTModel) if is_flax_available() else ()
				__lowerCamelCase					=							(FlaxMarianMTModel,) if is_flax_available() else ()




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       FlaxMarianModelTester(self						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase      ,      _lowerCAmelCase         =       self.model_tester.prepare_config_and_inputs()
									for model_class in self.all_model_classes:
														self.model_tester.check_use_cache_forward(_UpperCAmelCase		,							_UpperCAmelCase		,							_UpperCAmelCase						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase      ,      _lowerCAmelCase         =       self.model_tester.prepare_config_and_inputs()
									for model_class in self.all_model_classes:
														self.model_tester.check_use_cache_forward_with_attn_mask(_UpperCAmelCase		,							_UpperCAmelCase		,							_UpperCAmelCase						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase      ,      _lowerCAmelCase         =       self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
														with self.subTest(model_class.__name__						):
																			_lowerCAmelCase         =       self._prepare_for_class(_UpperCAmelCase		,							_UpperCAmelCase						)
																			_lowerCAmelCase         =       model_class(_UpperCAmelCase						)

																			@jax.jit
																			def encode_jitted(_snake_case		,							_snake_case=None		,							**_snake_case						):
																								return model.encode(input_ids=_UpperCAmelCase		,							attention_mask=_UpperCAmelCase						)

																			with self.subTest("""JIT Enabled"""						):
																								_lowerCAmelCase         =       encode_jitted(**_UpperCAmelCase						).to_tuple()

																			with self.subTest("""JIT Disabled"""						):
																								with jax.disable_jit():
																													_lowerCAmelCase         =       encode_jitted(**_UpperCAmelCase						).to_tuple()

																			self.assertEqual(len(_UpperCAmelCase						)		,							len(_UpperCAmelCase						)						)
																			for jitted_output, output in zip(_UpperCAmelCase		,							_UpperCAmelCase						):
																								self.assertEqual(jitted_output.shape		,							output.shape						)




				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase      ,      _lowerCAmelCase         =       self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
														with self.subTest(model_class.__name__						):
																			_lowerCAmelCase         =       model_class(_UpperCAmelCase						)
																			_lowerCAmelCase         =       model.encode(inputs_dict["""input_ids"""]		,							inputs_dict["""attention_mask"""]						)

																			_lowerCAmelCase         =       {
																			    """decoder_input_ids""": inputs_dict["""decoder_input_ids"""],
																			    """decoder_attention_mask""": inputs_dict["""decoder_attention_mask"""],
																			    """encoder_outputs""": encoder_outputs,
																			}

																			@jax.jit
																			def decode_jitted(_snake_case		,							_snake_case		,							_snake_case						):
																								return model.decode(
																								    decoder_input_ids=_UpperCAmelCase		,							decoder_attention_mask=_UpperCAmelCase		,							encoder_outputs=_UpperCAmelCase		,							)

																			with self.subTest("""JIT Enabled"""						):
																								_lowerCAmelCase         =       decode_jitted(**_UpperCAmelCase						).to_tuple()

																			with self.subTest("""JIT Disabled"""						):
																								with jax.disable_jit():
																													_lowerCAmelCase         =       decode_jitted(**_UpperCAmelCase						).to_tuple()

																			self.assertEqual(len(_UpperCAmelCase						)		,							len(_UpperCAmelCase						)						)
																			for jitted_output, output in zip(_UpperCAmelCase		,							_UpperCAmelCase						):
																								self.assertEqual(jitted_output.shape		,							output.shape						)




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									for model_class_name in self.all_model_classes:
														_lowerCAmelCase         =       model_class_name.from_pretrained("""Helsinki-NLP/opus-mt-en-de"""						)
														# FlaxMarianForSequenceClassification expects eos token in input_ids
														_lowerCAmelCase         =       np.ones((1, 1)						) * model.config.eos_token_id
														_lowerCAmelCase         =       model(_UpperCAmelCase						)
														self.assertIsNotNone(_UpperCAmelCase						)





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	unittest.TestCase			):
				__lowerCamelCase					=							None
				__lowerCamelCase					=							None




				@classmethod
				def 				snake_case  (				cls						):



									"""simple docstring"""





									_lowerCAmelCase         =       F'Helsinki-NLP/opus-mt-{cls.src}-{cls.tgt}'
									return cls




				@cached_property
				def 				snake_case  (				self						):



									"""simple docstring"""





									return MarianTokenizer.from_pretrained(self.model_name						)




				@property
				def 				snake_case  (				self						):



									"""simple docstring"""





									return self.tokenizer.eos_token_id




				@cached_property
				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       FlaxMarianMTModel.from_pretrained(self.model_name						)
									self.assertEqual(model.config.decoder_start_token_id		,							model.config.pad_token_id						)
									return model




				def 				snake_case  (				self		,							**_snake_case						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.translate_src_text(**_UpperCAmelCase						)
									self.assertListEqual(self.expected_text		,							_UpperCAmelCase						)




				def 				snake_case  (				self		,							**_snake_case						):



									"""simple docstring"""





									_lowerCAmelCase         =       self.tokenizer(self.src_text		,							padding=_UpperCAmelCase		,							return_tensors="""np"""		,							**_UpperCAmelCase						)
									_lowerCAmelCase         =       self.model.generate(
									    model_inputs.input_ids		,							attention_mask=model_inputs.attention_mask		,							num_beams=2		,							max_length=128		,							).sequences
									_lowerCAmelCase         =       self.tokenizer.batch_decode(_UpperCAmelCase		,							skip_special_tokens=_UpperCAmelCase						)
									return generated_words





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''en'''
				__lowerCamelCase					=							'''fr'''
				__lowerCamelCase					=							[
				    '''I am a small frog.''',
				    '''Now I can forget the 100 words of german that I know.''',
				]
				__lowerCamelCase					=							[
				    '''Je suis une petite grenouille.''',
				    '''Maintenant, je peux oublier les 100 mots d\'allemand que je connais.''',
				]




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''fr'''
				__lowerCamelCase					=							'''en'''
				__lowerCamelCase					=							[
				    '''Donnez moi le micro.''',
				    '''Tom et Mary étaient assis à une table.''',  # Accents
				]
				__lowerCamelCase					=							[
				    '''Give me the microphone.''',
				    '''Tom and Mary were sitting at a table.''',
				]




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''mt'''
				__lowerCamelCase					=							'''en'''
				__lowerCamelCase					=							['''Billi messu b\'mod ġentili, Ġesù fejjaq raġel li kien milqut bil - marda kerha tal - ġdiem.''']
				__lowerCamelCase					=							['''Touching gently, Jesus healed a man who was affected by the sad disease of leprosy.''']




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''en'''
				__lowerCamelCase					=							'''de'''
				__lowerCamelCase					=							[
				    '''I am a small frog.''',
				    '''Now I can forget the 100 words of german that I know.''',
				    '''Tom asked his teacher for advice.''',
				    '''That\'s how I would do it.''',
				    '''Tom really admired Mary\'s courage.''',
				    '''Turn around and close your eyes.''',
				]
				__lowerCamelCase					=							[
				    '''Ich bin ein kleiner Frosch.''',
				    '''Jetzt kann ich die 100 Wörter des Deutschen vergessen, die ich kenne.''',
				    '''Tom bat seinen Lehrer um Rat.''',
				    '''So würde ich das machen.''',
				    '''Tom bewunderte Marias Mut wirklich.''',
				    '''Drehen Sie sich um und schließen Sie die Augen.''',
				]




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''en'''
				__lowerCamelCase					=							'''zh'''
				__lowerCamelCase					=							['''My name is Wolfgang and I live in Berlin''']
				__lowerCamelCase					=							['''我叫沃尔夫冈 我住在柏林''']




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''ru'''
				__lowerCamelCase					=							'''fr'''
				__lowerCamelCase					=							['''Он показал мне рукопись своей новой пьесы.''']
				__lowerCamelCase					=							['''Il m\'a montré le manuscrit de sa nouvelle pièce.''']




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()





@require_flax
@require_sentencepiece
@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							'''en'''
				__lowerCamelCase					=							'''ROMANCE'''
				__lowerCamelCase					=							[
				    '''>>fr<< Don\'t spend so much time watching TV.''',
				    '''>>pt<< Your message has been sent.''',
				    '''>>es<< He\'s two years older than me.''',
				]
				__lowerCamelCase					=							[
				    '''Ne passez pas autant de temps à regarder la télé.''',
				    '''A sua mensagem foi enviada.''',
				    '''Es dos años más viejo que yo.''',
				]




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									self._assert_generated_batch_equal_expected()











import json
import os
import re
import unicodedata
from typing import Dict, List, Optional, Tuple

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


_UpperCAmelCase					:						Dict         =     logging.get_logger(__name__)

_UpperCAmelCase					:						int         =     {
    'src_vocab_file': 'vocab-src.json',
    'tgt_vocab_file': 'vocab-tgt.json',
    'merges_file': 'merges.txt',
}

_UpperCAmelCase					:						Optional[int]         =     {
    'src_vocab_file': {
        'stas/tiny-wmt19-en-de': 'https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/vocab-src.json'
    },
    'tgt_vocab_file': {
        'stas/tiny-wmt19-en-de': 'https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/vocab-tgt.json'
    },
    'merges_file': {'stas/tiny-wmt19-en-de': 'https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/merges.txt'},
}

_UpperCAmelCase					:						Optional[int]         =     {'stas/tiny-wmt19-en-de': 1024}
_UpperCAmelCase					:						List[Any]         =     {
    'stas/tiny-wmt19-en-de': {
        'langs': ['en', 'de'],
        'model_max_length': 1024,
        'special_tokens_map_file': None,
        'full_tokenizer_file': None,
    }
}






def  UpperCAmelCase__						(    lowerCamelCase	:			Dict    ):
   lowerCamelCase									=set()
   lowerCamelCase									=word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)    )
      lowerCamelCase									=char
   return pairs






def  UpperCAmelCase__						(    lowerCamelCase	:			Optional[Any]    ):
   lowerCamelCase									=text.replace("""，"""			,""","""    )
   lowerCamelCase									=re.sub(R"""。\s*"""			,""". """			,lowerCamelCase    )
   lowerCamelCase									=text.replace("""、"""			,""","""    )
   lowerCamelCase									=text.replace("""”"""			,"""\""""    )
   lowerCamelCase									=text.replace("""“"""			,"""\""""    )
   lowerCamelCase									=text.replace("""∶"""			,""":"""    )
   lowerCamelCase									=text.replace("""："""			,""":"""    )
   lowerCamelCase									=text.replace("""？"""			,"""?"""    )
   lowerCamelCase									=text.replace("""《"""			,"""\""""    )
   lowerCamelCase									=text.replace("""》"""			,"""\""""    )
   lowerCamelCase									=text.replace("""）"""			,""")"""    )
   lowerCamelCase									=text.replace("""！"""			,"""!"""    )
   lowerCamelCase									=text.replace("""（"""			,"""("""    )
   lowerCamelCase									=text.replace("""；"""			,""";"""    )
   lowerCamelCase									=text.replace("""１"""			,"""1"""    )
   lowerCamelCase									=text.replace("""」"""			,"""\""""    )
   lowerCamelCase									=text.replace("""「"""			,"""\""""    )
   lowerCamelCase									=text.replace("""０"""			,"""0"""    )
   lowerCamelCase									=text.replace("""３"""			,"""3"""    )
   lowerCamelCase									=text.replace("""２"""			,"""2"""    )
   lowerCamelCase									=text.replace("""５"""			,"""5"""    )
   lowerCamelCase									=text.replace("""６"""			,"""6"""    )
   lowerCamelCase									=text.replace("""９"""			,"""9"""    )
   lowerCamelCase									=text.replace("""７"""			,"""7"""    )
   lowerCamelCase									=text.replace("""８"""			,"""8"""    )
   lowerCamelCase									=text.replace("""４"""			,"""4"""    )
   lowerCamelCase									=re.sub(R"""．\s*"""			,""". """			,lowerCamelCase    )
   lowerCamelCase									=text.replace("""～"""			,"""~"""    )
   lowerCamelCase									=text.replace("""’"""			,"""'"""    )
   lowerCamelCase									=text.replace("""…"""			,"""..."""    )
   lowerCamelCase									=text.replace("""━"""			,"""-"""    )
   lowerCamelCase									=text.replace("""〈"""			,"""<"""    )
   lowerCamelCase									=text.replace("""〉"""			,""">"""    )
   lowerCamelCase									=text.replace("""【"""			,"""["""    )
   lowerCamelCase									=text.replace("""】"""			,"""]"""    )
   lowerCamelCase									=text.replace("""％"""			,"""%"""    )
   return text






def  UpperCAmelCase__						(    lowerCamelCase	:			Optional[int]    ):
   lowerCamelCase									=[]
   for char in text:
      lowerCamelCase									=unicodedata.category(lowerCamelCase    )
      if cat.startswith("""C"""    ):
         continue
      output.append(lowerCamelCase    )
   return "".join(lowerCamelCase    )







class 		lowerCAmelCase_				(  UpperCamelCase ):
     __lowerCamelCase       :    Optional[int] 	=     VOCAB_FILES_NAMES
     __lowerCamelCase       :    List[Any] 	=     PRETRAINED_VOCAB_FILES_MAP
     __lowerCamelCase       :    List[Any] 	=     PRETRAINED_INIT_CONFIGURATION
     __lowerCamelCase       :    Tuple 	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __lowerCamelCase       :    Optional[int] 	=     ['''input_ids''', '''attention_mask''']





     def __init__(	self							, _UpperCAmelCase=None							, _UpperCAmelCase=None							, _UpperCAmelCase=None							, _UpperCAmelCase=None							, _UpperCAmelCase=False							, _UpperCAmelCase="<unk>"							, _UpperCAmelCase="<s>"							, _UpperCAmelCase="</s>"							, _UpperCAmelCase="<pad>"							, **_UpperCAmelCase							, )		->				Tuple:
        super().__init__(
            langs=_UpperCAmelCase							, src_vocab_file=_UpperCAmelCase							, tgt_vocab_file=_UpperCAmelCase							, merges_file=_UpperCAmelCase							, do_lower_case=_UpperCAmelCase							, unk_token=_UpperCAmelCase							, bos_token=_UpperCAmelCase							, sep_token=_UpperCAmelCase							, pad_token=_UpperCAmelCase							, **_UpperCAmelCase							, )

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

        lowerCamelCase									=sacremoses

        lowerCamelCase									=src_vocab_file
        lowerCamelCase									=tgt_vocab_file
        lowerCamelCase									=merges_file
        lowerCamelCase									=do_lower_case

        # cache of sm.MosesPunctNormalizer instance
        lowerCamelCase									={}
        # cache of sm.MosesTokenizer instance
        lowerCamelCase									={}
        lowerCamelCase									={}

        if langs and len(_UpperCAmelCase  ) == 2:
           lowerCamelCase				,       lowerCamelCase									=langs
        else:
           raise ValueError(
               F'''arg `langs` needs to be a list of 2 langs, e.g. [\'en\', \'ru\'], but got {langs}. '''
               """Usually that means that tokenizer can't find a mapping for the given model path """
               """in PRETRAINED_VOCAB_FILES_MAP, and other maps of this tokenizer."""  )

        with open(_UpperCAmelCase							, encoding="""utf-8"""  ) as src_vocab_handle:
           lowerCamelCase									=json.load(_UpperCAmelCase  )
        with open(_UpperCAmelCase							, encoding="""utf-8"""  ) as tgt_vocab_handle:
           lowerCamelCase									=json.load(_UpperCAmelCase  )
           lowerCamelCase									={v: k for k, v in tgt_vocab.items()}
        with open(_UpperCAmelCase							, encoding="""utf-8"""  ) as merges_handle:
           lowerCamelCase									=merges_handle.read().split("""\n"""  )[:-1]
        lowerCamelCase									=[tuple(merge.split()[:2]  ) for merge in merges]
        lowerCamelCase									=dict(zip(_UpperCAmelCase							, range(len(_UpperCAmelCase  )  )  )  )
        lowerCamelCase									={}





     def 						lowerCamelCase							(	self  )		->				Dict[str, int]:
        return self.get_src_vocab()





     @property
     def 						lowerCamelCase							(	self  )		->				int:
        return self.src_vocab_size





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				int:
        if lang not in self.cache_moses_punct_normalizer:
           lowerCamelCase									=self.sm.MosesPunctNormalizer(lang=_UpperCAmelCase  )
           lowerCamelCase									=punct_normalizer
        return self.cache_moses_punct_normalizer[lang].normalize(_UpperCAmelCase  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				str:
        if lang not in self.cache_moses_tokenizer:
           lowerCamelCase									=self.sm.MosesTokenizer(lang=_UpperCAmelCase  )
           lowerCamelCase									=moses_tokenizer
        return self.cache_moses_tokenizer[lang].tokenize(
            _UpperCAmelCase							, aggressive_dash_splits=_UpperCAmelCase							, return_str=_UpperCAmelCase							, escape=_UpperCAmelCase  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				Dict:
        if lang not in self.cache_moses_detokenizer:
           lowerCamelCase									=self.sm.MosesDetokenizer(lang=_UpperCAmelCase  )
           lowerCamelCase									=moses_detokenizer
        return self.cache_moses_detokenizer[lang].detokenize(_UpperCAmelCase  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				List[str]:
        lowerCamelCase									=replace_unicode_punct(_UpperCAmelCase  )
        lowerCamelCase									=self.moses_punct_norm(_UpperCAmelCase							, _UpperCAmelCase  )
        lowerCamelCase									=remove_non_printing_char(_UpperCAmelCase  )
        return text





     @property
     def 						lowerCamelCase							(	self  )		->				Dict:
        return len(self.encoder  )





     @property
     def 						lowerCamelCase							(	self  )		->				Union[str, Any]:
        return len(self.decoder  )





     def 						lowerCamelCase							(	self  )		->				Optional[Any]:
        return dict(self.encoder							, **self.added_tokens_encoder  )





     def 						lowerCamelCase							(	self  )		->				Union[str, Any]:
        return dict(self.decoder							, **self.added_tokens_decoder  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				Union[str, Any]:
        lowerCamelCase									=tuple(token[:-1]  ) + (token[-1] + """</w>""",)
        if token in self.cache:
           return self.cache[token]
        lowerCamelCase									=get_pairs(_UpperCAmelCase  )

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

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

              if word[i] == first and i < len(_UpperCAmelCase  ) - 1 and word[i + 1] == second:
                 new_word.append(first + second  )
                 i += 2
              else:
                 new_word.append(word[i]  )
                 i += 1
           lowerCamelCase									=tuple(_UpperCAmelCase  )
           lowerCamelCase									=new_word
           if len(_UpperCAmelCase  ) == 1:
              break
           else:
              lowerCamelCase									=get_pairs(_UpperCAmelCase  )
        lowerCamelCase									=""" """.join(_UpperCAmelCase  )
        if word == "\n  </w>":
           lowerCamelCase									="""\n</w>"""
        lowerCamelCase									=word
        return word





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase="en"							, _UpperCAmelCase=False  )		->				str:
        lowerCamelCase									=self.src_lang

        if self.do_lower_case:
           lowerCamelCase									=text.lower()

        if bypass_tokenizer:
           lowerCamelCase									=text.split()
        else:
           lowerCamelCase									=self.moses_pipeline(_UpperCAmelCase							, lang=_UpperCAmelCase  )
           lowerCamelCase									=self.moses_tokenize(_UpperCAmelCase							, lang=_UpperCAmelCase  )

        lowerCamelCase									=[]
        for token in text:
           if token:
              split_tokens.extend(list(self.bpe(_UpperCAmelCase  ).split(""" """  )  )  )

        return split_tokens





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				List[str]:
        return self.encoder.get(_UpperCAmelCase							, self.encoder.get(self.unk_token  )  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				Tuple:
        return self.decoder.get(_UpperCAmelCase							, self.unk_token  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				List[Any]:
        lowerCamelCase									=[t.replace(""" """							, """"""  ).replace("""</w>"""							, """ """  ) for t in tokens]
        lowerCamelCase									="""""".join(_UpperCAmelCase  ).split()
        # detokenize
        lowerCamelCase									=self.moses_detokenize(_UpperCAmelCase							, self.tgt_lang  )
        return text





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None  )		->				List[int]:
        lowerCamelCase									=[self.sep_token_id]

        # no bos used in fairseq
        if token_ids_a is None:
           return token_ids_a + sep
        return token_ids_a + sep + token_ids_a + sep





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None							, _UpperCAmelCase = False  )		->				List[int]:

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





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None  )		->				List[int]:
        lowerCamelCase									=[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							, _UpperCAmelCase							, _UpperCAmelCase = None  )		->				Tuple[str]:
        if not os.path.isdir(_UpperCAmelCase  ):
           logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
           return

        lowerCamelCase									=os.path.join(
            _UpperCAmelCase							, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""src_vocab_file"""]  )
        lowerCamelCase									=os.path.join(
            _UpperCAmelCase							, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""tgt_vocab_file"""]  )
        lowerCamelCase									=os.path.join(
            _UpperCAmelCase							, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]  )

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

        with open(_UpperCAmelCase							, """w"""							, encoding="""utf-8"""  ) as f:
           lowerCamelCase									={v: k for k, v in self.decoder.items()}
           f.write(json.dumps(_UpperCAmelCase							, indent=2							, sort_keys=_UpperCAmelCase							, ensure_ascii=_UpperCAmelCase  ) + """\n"""  )

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

        return src_vocab_file, tgt_vocab_file, merges_file





     def __getstate__(	self  )		->				List[Any]:
        lowerCamelCase									=self.__dict__.copy()
        lowerCamelCase									=None
        return state





     def __setstate__(	self							, _UpperCAmelCase  )		->				Union[str, Any]:
        lowerCamelCase									=d

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

        lowerCamelCase									=sacremoses