






import json
import os
import unittest
from typing import Tuple

from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from transformers.testing_utils import require_phonemizer

from ...test_tokenization_common import TokenizerTesterMixin




@require_phonemizer
class  UpperCamelCase_      (			snake_case_       ,					unittest.TestCase				):



	'''simple docstring'''




	lowerCAmelCase													= WavaVecaPhonemeCTCTokenizer
	lowerCAmelCase													= False




	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								super().setUp()

								snake_case_				=							(
								    '<s> <pad> </s> <unk> n s t ə l a i k d m ɛ ɾ e ɪ p o ɐ z ð f j v b ɹ ʁ ʊ iː r w ʌ u ɡ æ aɪ ʃ h ɔ ɑː '
								    'ŋ ɚ eɪ β uː y ɑ̃ oʊ ᵻ eː θ aʊ ts oː ɔ̃ ɣ ɜ ɑ dʒ əl x ɜː ç ʒ tʃ ɔː ɑːɹ ɛ̃ ʎ ɔːɹ ʋ aː ɕ œ ø oːɹ ɲ yː '
								    'ʔ iə i5 s. tɕ ?? nʲ ɛː œ̃ ɭ ɔø ʑ tʲ ɨ ɛɹ ts. rʲ ɪɹ ɭʲ i.5 ɔɪ q sʲ u5 ʊɹ iɜ a5 iɛ5 øː ʕ ja əɜ th ɑ5 '
								    'oɪ dʲ ə5 tɕh ts.h mʲ ɯ dʑ vʲ e̞ tʃʲ ei5 o5 onɡ5 ɑu5 iɑ5 ai5 aɪɚ kh ə1 ʐ i2 ʉ ħ t[ aɪə ʲ ju ə2 u2 oɜ '
								    'pː iɛɜ ou5 y5 uɜ tː uo5 d[ uoɜ tsh ɑɜ ɵ i̪5 uei5 ɟ aɜ ɑɨ i.ɜ eʊ o2 ɐ̃ ä pʲ kʲ n̩ ɒ ph ɑu2 uɨ əɪ ɫ ɬ '
								    'yɜ bʲ ɑ2 s̪ aiɜ χ ɐ̃ʊ̃ 1 ə4 yæɜ a2 ɨː t̪ iouɜ ũ onɡɜ aɨ iɛ2 ɔɨ ɑuɜ o̞ ei2 iou2 c kː y2 ɖ oe dˤ yɛɜ '
								    'əʊ S ɡʲ onɡ2 u" eiɜ ʈ ɯᵝ iou5 dZ r̝̊ i.2 tS s^ ʝ yə5 iɑɜ uə5 pf ɨu iɑ2 ou2 ər2 fʲ ai2 r̝ uəɜ ɳ əɨ '
								    'ua5 uɪ ɽ bː yu5 uo2 yɛ5 l̩ ɻ ərɜ ʂ i̪2 ouɜ uaɜ a. a.ː yæ5 dː r̩ ee ɪu ər5 i̪ ɜ æi u: i.ː t^ o1 ɪ^ '
								    'ai ueiɜ æː ɛɪ eə i. ɴ ie ua2 ɑ1 o4 tʃː o: ɑ: u1 N i̪1 au yæ2 u. qː yəɜ y: kʰ tʃʰ iʊ sx õ uo tʰ '
								    'uai5 bʰ u.ː uə2 ʊə d^ s̪ː yiɜ dʰ r. oe: i1 ɟː yu2 nʲʲ i̪4 uei2 tsʲ ɸ ĩ ɑ4 t̪ː eɑ u4 e: tsː ʈʰ ɡʰ '
								    'ɯɯ dʒʲ ʂʲ X ɵː uaiɜ tɕʲ ã t^ː ẽː yɛ2 cː i.1 ɛʊ dˤdˤ dʒː i4 ɡː yi ɕʲ ɟʰ pʰ dʑʲ yuɜ ua1 ua4 æiː ɐɐ '
								    'ui iou1 ʊː a1 iou4 cʰ iɛ1 yə2 ɖʰ ẽ ʒʲ ää ər4 iːː ɪː iɑ1 ər1 œː øi ɪuː cʰcʰ əː1 iː1 ũ kʰː o̞o̞ xʲ '
								    'ou1 iɛ4 e̞e̞ y1 dzː dʲʲ dʰː ɯᵝɯᵝ lː uo1 i.4 i: yɛ5ʲ a4'
								).split(' '					)
								snake_case_				=							dict(zip(a       ,			range(len(a					)					)					)					)

								snake_case_				=							{'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}

								snake_case_				=							os.path.join(self.tmpdirname       ,			VOCAB_FILES_NAMES['vocab_file']					)
								with open(self.vocab_file       ,			'w'       ,			encoding='utf-8'					) as fp:
															fp.write(json.dumps(a					) + '\n'					)




	def 							_UpperCamelCase			(       self       ,			a       ,			a=False       ,			a=20       ,			a=5					)       ->    Tuple[str, list]:
								snake_case_				=							[(i, tokenizer.decode([i]       ,			clean_up_tokenization_spaces=a					)) for i in range(len(a					)					)]
								snake_case_				=							list(filter(lambda a					: [t[0]] == tokenizer.encode(t[1]       ,			do_phonemize=a					)       ,			a					)					)
								if max_length is not None and len(a					) > max_length:
															snake_case_				=							toks[:max_length]
								if min_length is not None and len(a					) < min_length and len(a					) > 0:
															while len(a					) < min_length:
																						snake_case_				=							toks + toks
        # toks_str = [t[1] for t in toks]
								snake_case_				=							[t[0] for t in toks]

								# Ensure consistency
								snake_case_				=							tokenizer.decode(a       ,			clean_up_tokenization_spaces=a					)
								if " " not in output_txt and len(a					) > 1:
															snake_case_				=							(
															    tokenizer.decode([toks_ids[0]]       ,			clean_up_tokenization_spaces=a					)
															    + ' '
															    + tokenizer.decode(toks_ids[1:]       ,			clean_up_tokenization_spaces=a					)
															)
								if with_prefix_space:
															snake_case_				=							' ' + output_txt
								snake_case_				=							tokenizer.encode(a       ,			add_special_tokens=a					)
								return output_txt, output_ids




	def 							_UpperCamelCase			(       self       ,			**a					)       ->    Any:
								kwargs.update(self.special_tokens_map					)
								return WavaVecaPhonemeCTCTokenizer.from_pretrained(self.tmpdirname       ,			**a					)




	def 							_UpperCamelCase			(       self					)       ->    int:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)

								# check adding a single token
								tokenizer.add_tokens('xxx'					)
								snake_case_				=							tokenizer('m xxx ɪ'       ,			do_phonemize=a					).input_ids
								self.assertEqual(a       ,			[13, 3_92, 17]					)  # xxx should be last token

								tokenizer.add_tokens(['aaa', 'bbb', 'ccc']					)
								snake_case_				=							tokenizer('m aaa ɪ ccc'       ,			do_phonemize=a					).input_ids
								self.assertEqual(a       ,			[13, 3_93, 17, 3_95]					)  # aaa and ccc should be after xxx and 2 after aaa

								snake_case_				=							tokenizer('maɪ c'       ,			do_phonemize=a					).input_ids
								self.assertEqual(a       ,			[3, 2_00]					)  # mai should be <unk> (=3)




	def 							_UpperCamelCase			(       self					)       ->    str:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)

								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)
								self.assertEqual(a       ,			'h ə l oʊ h aʊ ɑːɹ j uː'					)




	def 							_UpperCamelCase			(       self					)       ->    Any:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)

								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)
								self.assertEqual(tokenizer(a					).input_ids       ,			tokenizer(a       ,			do_phonemize=a					).input_ids					)




	def 							_UpperCamelCase			(       self					)       ->    str:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)
								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)

								snake_case_				=							tokenizer.decode(tokenizer(a					).input_ids					)

								self.assertEqual(a       ,			a					)




	def 							_UpperCamelCase			(       self					)       ->    List[str]:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)

								snake_case_				=							[
								    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98],
								    [24, 22, 5, 24, 22, 5, 77],
								]
								snake_case_				=							tokenizer.decode(sample_ids[0]					)
								snake_case_				=							tokenizer.batch_decode(a					)
								self.assertEqual(a       ,			batch_tokens[0]					)
								self.assertEqual(a       ,			['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ']					)




	def 							_UpperCamelCase			(       self					)       ->    Union[str, Any]:
								snake_case_				=							self.tokenizer_class.from_pretrained(
								    'facebook/wav2vec2-lv-60-espeak-cv-ft'       ,			word_delimiter_token='|'					)
								tokenizer.add_tokens('|'					)

								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)
								self.assertEqual(a       ,			'h ə l oʊ | h aʊ | ɑːɹ | j uː |'					)




	def 							_UpperCamelCase			(       self					)       ->    Any:
								snake_case_				=							self.tokenizer_class.from_pretrained(
								    'facebook/wav2vec2-lv-60-espeak-cv-ft'       ,			word_delimiter_token='|'					)
								tokenizer.add_tokens('|'					)

								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)
								self.assertEqual(tokenizer(a					).input_ids       ,			tokenizer(a       ,			do_phonemize=a					).input_ids					)




	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								snake_case_				=							self.tokenizer_class.from_pretrained(
								    'facebook/wav2vec2-lv-60-espeak-cv-ft'       ,			word_delimiter_token='|'					)
								tokenizer.add_tokens('|'					)

								# fmt: off
								snake_case_				=							[
								    [11, 5, 15, tokenizer.pad_token_id, tokenizer.word_delimiter_token_id, 15, 8, tokenizer.word_delimiter_token_id, 98],
								    [tokenizer.word_delimiter_token_id, 24, 22, tokenizer.word_delimiter_token_id, 5, 24, 22, 5, 77],
								]
								# fmt: on

								# decode with word_del_token filter
								snake_case_				=							tokenizer.decode(sample_ids[0]					)
								snake_case_				=							tokenizer.batch_decode(a					)
								self.assertEqual(a       ,			batch_tokens[0]					)
								self.assertEqual(a       ,			['k s ɾ ɾ l ɭʲ', 'j ð s j ð s oːɹ']					)

								# decode with no word_del_token filter
								snake_case_				=							tokenizer.decode(sample_ids[0]       ,			filter_word_delimiter_token=a					)
								snake_case_				=							tokenizer.batch_decode(a       ,			filter_word_delimiter_token=a					)
								self.assertEqual(a       ,			batch_tokens[0]					)
								self.assertEqual(a       ,			['k s ɾ | ɾ l | ɭʲ', '| j ð | s j ð s oːɹ']					)




	def 							_UpperCamelCase			(       self					)       ->    Optional[Any]:
								snake_case_				=							self.tokenizer_class.from_pretrained(
								    'facebook/wav2vec2-lv-60-espeak-cv-ft'       ,			word_delimiter_token='|'					)
								tokenizer.add_tokens('|'					)

								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)

								snake_case_				=							tokenizer.decode(tokenizer(a					).input_ids       ,			filter_word_delimiter_token=a					)

								self.assertEqual(a       ,			a					)




	def 							_UpperCamelCase			(       self					)       ->    Optional[Any]:
								snake_case_				=							self.tokenizer_class.from_pretrained(
								    'facebook/wav2vec2-lv-60-espeak-cv-ft'       ,			word_delimiter_token='|'					)
								tokenizer.add_tokens('|'					)

								snake_case_				=							'Hello how are you'
								snake_case_				=							tokenizer.phonemize(a       ,			phonemizer_lang='en-us'					)

								snake_case_				=							tokenizer.decode(tokenizer(a					).input_ids       ,			filter_word_delimiter_token=a					)

								self.assertEqual(' '.join([p.strip() for p in phonemes.split(' |'					)]					).strip()       ,			a					)




	def 							_UpperCamelCase			(       self					)       ->    Dict:
								snake_case_				=							self.tokenizer_class.from_pretrained(
								    'facebook/wav2vec2-lv-60-espeak-cv-ft'       ,			word_delimiter_token=a					)
								snake_case_				=							'Hello how are you'

								snake_case_				=							tokenizer(a       ,			phonemizer_lang='en-us'					).input_ids
								snake_case_				=							tokenizer(a       ,			phonemizer_lang='fr-fr'					).input_ids

								self.assertNotEqual(a       ,			a					)

								snake_case_				=							tokenizer.decode(a					)
								snake_case_				=							tokenizer.decode(a					)

								self.assertEqual(a       ,			'h ə l oʊ h aʊ ɑːɹ j uː'					)
								self.assertEqual(a       ,			'ɛ l o h aʊ a ʁ j u'					)




	def 							_UpperCamelCase			(       self					)       ->    str:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)
								snake_case_				=							'Hello how Are you'
								snake_case_				=							'hello how are you'

								snake_case_				=							tokenizer(a					).input_ids
								snake_case_				=							tokenizer(a					).input_ids

								self.assertEqual(a       ,			a					)




	def 							_UpperCamelCase			(       self					)       ->    Union[str, Any]:
								snake_case_				=							self.tokenizer_class.from_pretrained('facebook/wav2vec2-lv-60-espeak-cv-ft'					)
								tokenizer.add_tokens(['!', '?']					)
								tokenizer.add_special_tokens({'cls_token': '$$$'}					)

								# fmt: off
								snake_case_				=							[
								    [11, 5, 15, tokenizer.pad_token_id, 15, 8, 98, 3_92, 3_92, 3_93, 3_92, 3_92, 3_93, 3_94, 3_94],
								    [24, 22, 5, 24, 22, 5, 77, tokenizer.pad_token_id, 3_94, 3_94],
								]
								# fmt: on

								snake_case_				=							tokenizer.batch_decode(a					)
								self.assertEqual(a       ,			['k s ɾ ɾ l ɭʲ!?!? $$$', 'j ð s j ð s oːɹ $$$']					)




	@staticmethod
	def 							_UpperCamelCase			(       a       ,			a					)       ->    Union[str, Any]:
								snake_case_				=							[d[key] for d in offsets]
								return retrieved_list




	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								snake_case_				=							self.get_tokenizer(word_delimiter_token='|'					)
								tokenizer.add_tokens('|'					)

								# fmt: off
								# ksssɾɾ|ɾɾ<pad>ɾɾ|<pad>ɾlll|ɭʲ -> k s ɾ ɾ | ɾ l | ɭʲ"
								snake_case_				=							[11, 5, 5, 5, 15, 15, tokenizer.pad_token_id, 15, 15, tokenizer.word_delimiter_token_id, tokenizer.pad_token_id, 15, 8, 8, 8, tokenizer.word_delimiter_token_id, 98]
								# fmt: on

								snake_case_				=							tokenizer.decode(a       ,			output_char_offsets=a       ,			filter_word_delimiter_token=a					)
								# check Wav2Vec2CTCTokenizerOutput keys for char
								self.assertEqual(len(outputs.keys()					)       ,			2					)
								self.assertTrue('text' in outputs					)
								self.assertTrue('char_offsets' in outputs					)
								self.assertTrue(isinstance(a       ,			a					)					)

								# check that order of chars is correct and identical for both outputs
								self.assertEqual(' '.join(self.get_from_offsets(outputs['char_offsets']       ,			'char'					)					)       ,			outputs.text					)
								self.assertListEqual(
								    self.get_from_offsets(outputs['char_offsets']       ,			'char'					)       ,			['k', 's', 'ɾ', 'ɾ', '|', 'ɾ', 'l', '|', 'ɭʲ']					)

								# check that offsets are actually correct for char
								# 0-1 is 11, 1-4 is 5, 4-6 is first 15, 6-7 is <pad> (thus not shown), 7-9 is second 15, 9-10 is word_delimiter_token,
								# 10-11 is <pad> (thus not shown), 11-12 is third 15, 12-15 is 8, 15-16 is word_delimiter_token, 16-17 is 98
								self.assertListEqual(
								    self.get_from_offsets(outputs['char_offsets']       ,			'start_offset'					)       ,			[0, 1, 4, 7, 9, 11, 12, 15, 16]					)
								self.assertListEqual(
								    self.get_from_offsets(outputs['char_offsets']       ,			'end_offset'					)       ,			[1, 4, 6, 9, 10, 12, 15, 16, 17]					)




	def 							_UpperCamelCase			(       self					)       ->    Dict:
								snake_case_				=							self.get_tokenizer(word_delimiter_token='|'					)

								def check_list_tuples_equal(a       ,			a					):
															self.assertTrue(isinstance(a       ,			a					)					)
															self.assertTrue(isinstance(outputs_list[0]       ,			a					)					)

															# transform list to ModelOutput
															snake_case_				=							WavaVecaPhonemeCTCTokenizerOutput(
															    {k: [d[k] for d in outputs_list] for k in outputs_list[0]}					)

															self.assertListEqual(outputs_batch['text']       ,			outputs_batch_a['text']					)

															def recursive_check(a       ,			a					):
																						if isinstance(a       ,			a					):
																													[recursive_check(a       ,			a					) for la, la in zip(a       ,			a					)]
																						self.assertEqual(a       ,			a					)

															if "char_offsets" in outputs_batch:
																						recursive_check(outputs_batch['char_offsets']       ,			outputs_batch_a['char_offsets']					)

        # fmt: off
								snake_case_				=							[
								    [11, 5, 15, tokenizer.pad_token_id, 15, 4, 8, 98, 32, 32, 32, 32, 4, 33, tokenizer.word_delimiter_token_id, 32, 32, 33, 34, 34],
								    [24, 22, 5, tokenizer.word_delimiter_token_id, tokenizer.word_delimiter_token_id, 24, 22, 22, 22, 4, 5, 77, tokenizer.pad_token_id, 22, 22, 4, 34, 34, 34, 34],
								]
								# fmt: on

								# We assume that `decode` works as expected. All we will check now is
								# the output type is correct and the output is identical to `decode`

								# char
								snake_case_				=							tokenizer.batch_decode(a       ,			output_char_offsets=a					)
								snake_case_				=							[tokenizer.decode(a       ,			output_char_offsets=a					) for ids in sample_ids]
								check_list_tuples_equal(a       ,			a					)




	@unittest.skip('Wav2Vec2PhonemeTokenizer always lower cases letters to correctly map to phonemes'					)
	def 							_UpperCamelCase			(       self					)       ->    Optional[Any]:
								pass




	@unittest.skip('Wav2Vec2PhonemeTokenizer always puts spaces between phonemes'					)
	def 							_UpperCamelCase			(       self					)       ->    Any:
								pass




	@unittest.skip('encodes to text to ids, but decodes ids to phonemes -> not possible to have internal consistency'					)
	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								pass




	@unittest.skip('Wav2Vec2PhonemeModel has no max model length => no testing'					)
	def 							_UpperCamelCase			(       self					)       ->    List[Any]:
								pass




	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								snake_case_				=							self.get_tokenizers(do_lower_case=a					)
								for tokenizer in tokenizers:
															with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
																						snake_case_				=							tokenizer.vocab_size
																						snake_case_				=							len(a					)

																						self.assertNotEqual(a       ,			0					)

																						# We usually have added tokens from the start in tests because our vocab fixtures are
																						# smaller than the original vocabs - let's not assert this
																						# self.assertEqual(vocab_size, all_size)

																						snake_case_				=							['aaaaa bbbbbb', 'cccccccccdddddddd']
																						snake_case_				=							tokenizer.add_tokens(a					)
																						snake_case_				=							tokenizer.vocab_size
																						snake_case_				=							len(a					)

																						self.assertNotEqual(a       ,			0					)
																						self.assertEqual(a       ,			a					)
																						self.assertEqual(a       ,			len(a					)					)
																						self.assertEqual(a       ,			all_size + len(a					)					)

																						snake_case_				=							tokenizer.encode('aaaaa bbbbbb low cccccccccdddddddd l'       ,			add_special_tokens=a					)

																						self.assertGreaterEqual(len(a					)       ,			4					)
																						self.assertGreater(tokens[0]       ,			tokenizer.vocab_size - 1					)
																						self.assertGreater(tokens[-3]       ,			tokenizer.vocab_size - 1					)

																						snake_case_				=							{'eos_token': '>>>>|||<||<<|<<', 'pad_token': '<<<<<|||>|>>>>|>'}
																						snake_case_				=							tokenizer.add_special_tokens(a					)
																						snake_case_				=							tokenizer.vocab_size
																						snake_case_				=							len(a					)

																						self.assertNotEqual(a       ,			0					)
																						self.assertEqual(a       ,			a					)
																						self.assertEqual(a       ,			len(a					)					)
																						self.assertEqual(a       ,			all_size_a + len(a					)					)

																						snake_case_				=							tokenizer.encode(
																						    '>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'       ,			add_special_tokens=a					)

																						self.assertGreaterEqual(len(a					)       ,			6					)
																						self.assertGreater(tokens[0]       ,			tokenizer.vocab_size - 1					)
																						self.assertGreater(tokens[0]       ,			tokens[1]					)
																						self.assertGreater(tokens[-3]       ,			tokenizer.vocab_size - 1					)
																						self.assertGreater(tokens[-3]       ,			tokens[-4]					)
																						self.assertEqual(tokens[0]       ,			tokenizer.eos_token_id					)
																						self.assertEqual(tokens[-3]       ,			tokenizer.pad_token_id					)




	@unittest.skip('The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode.'					)
	def 							_UpperCamelCase			(       self					)       ->    int:
								pass




	@unittest.skip('The tokenizer shouldn\'t be used to encode input IDs (except for labels), only to decode.'					)
	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								pass






	def 							_UpperCamelCase			(       self					)       ->    Tuple:
								# The default common tokenizer tests assumes that the output of `convert_tokens_to_string` is a string which
								# is not the case for Wav2Vec2PhonemeCTCTokenizer.
								snake_case_				=							self.get_tokenizers(fast=a       ,			do_lower_case=a					)
								for tokenizer in tokenizers:
															with self.subTest(F'''{tokenizer.__class__.__name__}'''					):
																						snake_case_				=							['ð', 'ɪ', 's', 'ɪ', 'z', 'ɐ', 't', 'ɛ', 'k', 's', 't']
																						snake_case_				=							tokenizer.convert_tokens_to_string(a					)

																						self.assertIsInstance(output['text']       ,			a					)













import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX





def 						__UpperCAmelCase			(     a_							,     a_							,     a_							,     a_							,     a_):
							snake_case_				=							np.array([[1, item, train_mtch[i]] for i, item in enumerate(a_)])
							snake_case_				=							np.array(a_)
							snake_case_				=							np.dot(np.dot(np.linalg.inv(np.dot(x.transpose()							,     a_))							,     x.transpose())							,     a_)
							return abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])





def 						__UpperCAmelCase			(     a_							,     a_							,     a_):
							snake_case_				=							(1, 2, 1)
							snake_case_				=							(1, 1, 0, 7)
							snake_case_				=							SARIMAX(
							    a_							,     exog=a_							,     order=a_							,     seasonal_order=a_)
							snake_case_				=							model.fit(disp=a_							,     maxiter=6_00							,     method='nm')
							snake_case_				=							model_fit.predict(1							,     len(a_)							,     exog=[test_match])
							return result[0]





def 						__UpperCAmelCase			(     a_							,     a_							,     a_):
							snake_case_				=							SVR(kernel='rbf'							,     C=1							,     gamma=0.1							,     epsilon=0.1)
							regressor.fit(a_							,     a_)
							snake_case_				=							regressor.predict(a_)
							return y_pred[0]





def 						__UpperCAmelCase			(     a_):
							train_user.sort()
							snake_case_				=							np.percentile(a_							,     25)
							snake_case_				=							np.percentile(a_							,     75)
							snake_case_				=							qa - qa
							snake_case_				=							qa - (iqr * 0.1)
							return low_lim





def 						__UpperCAmelCase			(     a_							,     a_):
							snake_case_				=							0
							snake_case_				=							0
							for i in list_vote:
														if i > actual_result:
																					snake_case_				=							not_safe + 1
														else:
																					if abs(abs(a_) - abs(a_)) <= 0.1:
																												safe += 1
																					else:
																												not_safe += 1
							return safe > not_safe


if __name__ == "__main__":
	# data_input_df = pd.read_csv("ex_data.csv", header=None)
	lowercase  							=					[[18231, 0.0, 1], [22621, 1.0, 2], [15675, 0.0, 3], [23583, 1.0, 4]]
	lowercase  							=					pd.DataFrame(
	    data_input, columns=["total_user", "total_even", "days"]
	)
	lowercase  							=					Normalizer().fit_transform(data_input_df.values)
	# split data
	lowercase  							=					normalize_df[:, 2].tolist()
	lowercase  							=					normalize_df[:, 0].tolist()
	lowercase  							=					normalize_df[:, 1].tolist()

	# for svr (input variable = total date and total match)
	lowercase  							=					normalize_df[:, [1, 2]].tolist()
	lowercase  							=					x[: len(x) - 1]
	lowercase  							=					x[len(x) - 1 :]

	# for linear regression & sarimax
	lowercase  							=					total_date[: len(total_date) - 1]
	lowercase  							=					total_user[: len(total_user) - 1]
	lowercase  							=					total_match[: len(total_match) - 1]

	lowercase  							=					total_date[len(total_date) - 1 :]
	lowercase  							=					total_user[len(total_user) - 1 :]
	lowercase  							=					total_match[len(total_match) - 1 :]

	# voting system with forecasting
	lowercase  							=					[
	    linear_regression_prediction(
	        trn_date, trn_user, trn_match, tst_date, tst_match
	    ),
	    sarimax_predictor(trn_user, trn_match, tst_match),
	    support_vector_regressor(x_train, x_test, trn_user),
	]

	# check the safety of today's data
	lowercase  							=					"" if data_safety_checker(res_vote, tst_user) else "not "
	print("Today's data is {not_str}safe.")





