import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class        lowercase_   (					__snake_case						,			unittest.TestCase		):
							_lowerCamelCase						=		XLMTokenizer
							_lowerCamelCase						=		False



							def 	UpperCamelCase	(						self    ):
													super().setUp()

													# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
													_snake_case						:					Optional[int]    =   [
													    "l",
													    "o",
													    "w",
													    "e",
													    "r",
													    "s",
													    "t",
													    "i",
													    "d",
													    "n",
													    "w</w>",
													    "r</w>",
													    "t</w>",
													    "lo",
													    "low",
													    "er</w>",
													    "low</w>",
													    "lowest</w>",
													    "newer</w>",
													    "wider</w>",
													    "<unk>",
													]
													_snake_case						:					int    =   dict(zip(lowercase_				,    range(len(lowercase_    )    )    )    )
													_snake_case						:					Optional[Any]    =   ["l o 123", "lo w 1456", "e r</w> 1789", ""]

													_snake_case						:					int    =   os.path.join(self.tmpdirname				,    VOCAB_FILES_NAMES["vocab_file"]    )
													_snake_case						:					Optional[Any]    =   os.path.join(self.tmpdirname				,    VOCAB_FILES_NAMES["merges_file"]    )
													with open(self.vocab_file				,    "w"    ) as fp:
																			fp.write(json.dumps(lowercase_    )    )
													with open(self.merges_file				,    "w"    ) as fp:
																			fp.write("\n".join(lowercase_    )    )



							def 	UpperCamelCase	(						self				,    lowercase_    ):
													_snake_case						:					Any    =   "lower newer"
													_snake_case						:					Union[str, Any]    =   "lower newer"
													return input_text, output_text



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Any    =   XLMTokenizer(self.vocab_file				,    self.merges_file    )

													_snake_case						:					Dict    =   "lower"
													_snake_case						:					List[str]    =   ["low", "er</w>"]
													_snake_case						:					Optional[int]    =   tokenizer.tokenize(lowercase_    )
													self.assertListEqual(lowercase_				,    lowercase_    )

													_snake_case						:					int    =   tokens + ["<unk>"]
													_snake_case						:					Union[str, Any]    =   [14, 15, 20]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_    )				,    lowercase_    )



							@slow
							def 	UpperCamelCase	(						self    ):
													_snake_case						:					List[Any]    =   XLMTokenizer.from_pretrained("xlm-mlm-en-2048"    )

													_snake_case						:					Tuple    =   tokenizer.encode("sequence builders"				,    add_special_tokens=lowercase_    )
													_snake_case						:					Optional[Any]    =   tokenizer.encode("multi-sequence build"				,    add_special_tokens=lowercase_    )

													_snake_case						:					Tuple    =   tokenizer.build_inputs_with_special_tokens(lowercase_    )
													_snake_case						:					List[str]    =   tokenizer.build_inputs_with_special_tokens(lowercase_				,    lowercase_    )

													assert encoded_sentence == [0] + text + [1]
													assert encoded_pair == [0] + text + [1] + text_a + [1]
import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list



@require_torchaudio
@require_sentencepiece
class        lowercase_   (					unittest.TestCase		):



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					str    =   "laion/clap-htsat-unfused"
													_snake_case						:					Dict    =   tempfile.mkdtemp()



							def 	UpperCamelCase	(						self				,    **lowercase_    ):
													return RobertaTokenizer.from_pretrained(self.checkpoint				,    **lowercase_    )



							def 	UpperCamelCase	(						self				,    **lowercase_    ):
													return ClapFeatureExtractor.from_pretrained(self.checkpoint				,    **lowercase_    )



							def 	UpperCamelCase	(						self    ):
													shutil.rmtree(self.tmpdirname    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Optional[int]    =   self.get_tokenizer()
													_snake_case						:					List[Any]    =   self.get_feature_extractor()

													_snake_case						:					Optional[Any]    =   ClapProcessor(tokenizer=lowercase_				,    feature_extractor=lowercase_    )

													processor.save_pretrained(self.tmpdirname    )
													_snake_case						:					Tuple    =   ClapProcessor.from_pretrained(self.tmpdirname    )

													self.assertEqual(processor.tokenizer.get_vocab()				,    tokenizer.get_vocab()    )
													self.assertIsInstance(processor.tokenizer				,    lowercase_    )

													self.assertEqual(processor.feature_extractor.to_json_string()				,    feature_extractor.to_json_string()    )
													self.assertIsInstance(processor.feature_extractor				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Any    =   ClapProcessor(tokenizer=self.get_tokenizer()				,    feature_extractor=self.get_feature_extractor()    )
													processor.save_pretrained(self.tmpdirname    )

													_snake_case						:					Any    =   self.get_tokenizer(bos_token="(BOS)"				,    eos_token="(EOS)"    )
													_snake_case						:					List[Any]    =   self.get_feature_extractor(do_normalize=lowercase_				,    padding_value=1.0    )

													_snake_case						:					List[Any]    =   ClapProcessor.from_pretrained(
													    self.tmpdirname				,    bos_token="(BOS)"				,    eos_token="(EOS)"				,    do_normalize=lowercase_				,    padding_value=1.0    )

													self.assertEqual(processor.tokenizer.get_vocab()				,    tokenizer_add_kwargs.get_vocab()    )
													self.assertIsInstance(processor.tokenizer				,    lowercase_    )

													self.assertEqual(processor.feature_extractor.to_json_string()				,    feature_extractor_add_kwargs.to_json_string()    )
													self.assertIsInstance(processor.feature_extractor				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Tuple    =   self.get_feature_extractor()
													_snake_case						:					Union[str, Any]    =   self.get_tokenizer()

													_snake_case						:					Optional[Any]    =   ClapProcessor(tokenizer=lowercase_				,    feature_extractor=lowercase_    )

													_snake_case						:					List[str]    =   floats_list((3, 1_000)    )

													_snake_case						:					Union[str, Any]    =   feature_extractor(lowercase_				,    return_tensors="np"    )
													_snake_case						:					Any    =   processor(audios=lowercase_				,    return_tensors="np"    )

													for key in input_feat_extract.keys():
																			self.assertAlmostEqual(input_feat_extract[key].sum()				,    input_processor[key].sum()				,    delta=1e-2    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					str    =   self.get_feature_extractor()
													_snake_case						:					Optional[Any]    =   self.get_tokenizer()

													_snake_case						:					Dict    =   ClapProcessor(tokenizer=lowercase_				,    feature_extractor=lowercase_    )

													_snake_case						:					Any    =   "This is a test string"

													_snake_case						:					Optional[Any]    =   processor(text=lowercase_    )

													_snake_case						:					Optional[Any]    =   tokenizer(lowercase_    )

													for key in encoded_tok.keys():
																			self.assertListEqual(encoded_tok[key]				,    encoded_processor[key]    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					Dict    =   self.get_feature_extractor()
													_snake_case						:					Dict    =   self.get_tokenizer()

													_snake_case						:					List[Any]    =   ClapProcessor(tokenizer=lowercase_				,    feature_extractor=lowercase_    )

													_snake_case						:					Dict    =   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

													_snake_case						:					List[Any]    =   processor.batch_decode(lowercase_    )
													_snake_case						:					Optional[int]    =   tokenizer.batch_decode(lowercase_    )

													self.assertListEqual(lowercase_				,    lowercase_    )



							def 	UpperCamelCase	(						self    ):
													_snake_case						:					List[str]    =   self.get_feature_extractor()
													_snake_case						:					str    =   self.get_tokenizer()

													_snake_case						:					Optional[int]    =   ClapProcessor(tokenizer=lowercase_				,    feature_extractor=lowercase_    )

													self.assertListEqual(
													    processor.model_input_names[2:]				,    feature_extractor.model_input_names				,    msg="`processor` and `feature_extractor` model input names do not match"				,    )