import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin




class   lowercase_    (    lowerCamelCase__ ,	unittest.TestCase		):



	"""simple docstring"""





	UpperCAmelCase_    :   Dict  =							CanineTokenizer
	UpperCAmelCase_    :   Optional[Any]  =							False


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Tuple:
								super().setUp()
								lowerCAmelCase      						=						CanineTokenizer()
								tokenizer.save_pretrained(self.tmpdirname							)


	@cached_property
	def      SCREAMING_SNAKE_CASE_							(				self							)		->Any:
								return CanineTokenizer.from_pretrained('''google/canine-s'''							)


	def      SCREAMING_SNAKE_CASE_							(				self						,     **__SCREAMING_SNAKE_CASE							)		->Any:
								lowerCAmelCase      						=						self.tokenizer_class.from_pretrained(self.tmpdirname						,     **a__							)
								lowerCAmelCase      						=						1024
								return tokenizer


	@require_torch
	def      SCREAMING_SNAKE_CASE_							(				self							)		->str:
								lowerCAmelCase      						=						self.canine_tokenizer
								lowerCAmelCase      						=						['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
								# fmt: off
								lowerCAmelCase      						=						[57344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57345, 0, 0, 0, 0]
								# fmt: on
								lowerCAmelCase      						=						tokenizer(a__						,     padding=a__						,     return_tensors='''pt'''							)
								self.assertIsInstance(a__						,     a__							)

								lowerCAmelCase      						=						list(batch.input_ids.numpy()[0]							)

								self.assertListEqual(a__						,     a__							)

								self.assertEqual((2, 39)						,     batch.input_ids.shape							)
								self.assertEqual((2, 39)						,     batch.attention_mask.shape							)


	@require_torch
	def      SCREAMING_SNAKE_CASE_							(				self							)		->Union[str, Any]:
								lowerCAmelCase      						=						self.canine_tokenizer
								lowerCAmelCase      						=						['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
								lowerCAmelCase      						=						tokenizer(a__						,     padding=a__						,     return_tensors='''pt'''							)
								# check if input_ids, attention_mask and token_type_ids are returned
								self.assertIn('''input_ids'''						,     a__							)
								self.assertIn('''attention_mask'''						,     a__							)
								self.assertIn('''token_type_ids'''						,     a__							)


	@require_torch
	def      SCREAMING_SNAKE_CASE_							(				self							)		->Tuple:
								lowerCAmelCase      						=						self.canine_tokenizer
								lowerCAmelCase      						=						[
								    '''What\'s the weater?''',
								    '''It\'s about 25 degrees.''',
								]
								lowerCAmelCase      						=						tokenizer(
								    text_target=a__						,     max_length=32						,     padding='''max_length'''						,     truncation=a__						,     return_tensors='''pt'''							)
								self.assertEqual(32						,     targets['''input_ids'''].shape[1]							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->List[str]:
								lowerCAmelCase      						=						self.get_tokenizers()
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						self.assertNotEqual(tokenizer.model_max_length						,     42							)

        # Now let's start the test
								lowerCAmelCase      						=						self.get_tokenizers()
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						# Isolate this from the other tests because we save additional tokens/etc
																						lowerCAmelCase      						=						tempfile.mkdtemp()

																						lowerCAmelCase      						=						''' He is very happy, UNwant\u00E9d,running'''
																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)
																						tokenizer.save_pretrained(a__							)

																						lowerCAmelCase      						=						tokenizer.__class__.from_pretrained(a__							)
																						lowerCAmelCase      						=						after_tokenizer.encode(a__						,     add_special_tokens=a__							)
																						self.assertListEqual(a__						,     a__							)

																						shutil.rmtree(a__							)

								lowerCAmelCase      						=						self.get_tokenizers(model_max_length=42							)
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						# Isolate this from the other tests because we save additional tokens/etc
																						lowerCAmelCase      						=						tempfile.mkdtemp()

																						lowerCAmelCase      						=						''' He is very happy, UNwant\u00E9d,running'''

																						lowerCAmelCase      						=						tokenizer.additional_special_tokens

																						# We can add a new special token for Canine as follows:
																						lowerCAmelCase      						=						chr(0XE_007							)
																						additional_special_tokens.append(a__							)
																						tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}							)
																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)
																						tokenizer.save_pretrained(a__							)

																						lowerCAmelCase      						=						tokenizer.__class__.from_pretrained(a__							)
																						lowerCAmelCase      						=						after_tokenizer.encode(a__						,     add_special_tokens=a__							)
																						self.assertListEqual(a__						,     a__							)
																						self.assertIn(a__						,     after_tokenizer.additional_special_tokens							)
																						self.assertEqual(after_tokenizer.model_max_length						,     42							)

																						lowerCAmelCase      						=						tokenizer.__class__.from_pretrained(a__						,     model_max_length=43							)
																						self.assertEqual(tokenizer.model_max_length						,     43							)

																						shutil.rmtree(a__							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->int:
								lowerCAmelCase      						=						self.get_tokenizers(do_lower_case=a__							)
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						lowerCAmelCase      						=						self.get_clean_sequence(a__							)

																						# a special token for Canine can be defined as follows:
																						lowerCAmelCase      						=						0XE_005
																						lowerCAmelCase      						=						chr(a__							)

																						tokenizer.add_special_tokens({'''cls_token''': special_token}							)
																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)
																						self.assertEqual(len(a__							)						,     1							)

																						lowerCAmelCase      						=						tokenizer.decode(ids + encoded_special_token						,     clean_up_tokenization_spaces=a__							)
																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)

																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)
																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)
																						self.assertEqual(a__						,     input_encoded + special_token_id							)

																						lowerCAmelCase      						=						tokenizer.decode(a__						,     skip_special_tokens=a__							)
																						self.assertTrue(special_token not in decoded							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Tuple:
								lowerCAmelCase      						=						self.get_tokenizers(do_lower_case=a__							)
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						lowerCAmelCase      						=						chr(0XE_005							)
																						lowerCAmelCase      						=						chr(0XE_006							)

																						# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
																						tokenizer.add_tokens([SPECIAL_TOKEN_1]						,     special_tokens=a__							)
																						# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
																						# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
																						tokenizer.add_special_tokens({'''additional_special_tokens''': [SPECIAL_TOKEN_2]}							)

																						lowerCAmelCase      						=						tokenizer.tokenize(a__							)
																						lowerCAmelCase      						=						tokenizer.tokenize(a__							)

																						self.assertEqual(len(a__							)						,     1							)
																						self.assertEqual(len(a__							)						,     1							)
																						self.assertEqual(token_a[0]						,     a__							)
																						self.assertEqual(token_a[0]						,     a__							)


	@require_tokenizers
	def      SCREAMING_SNAKE_CASE_							(				self							)		->Dict:
								lowerCAmelCase      						=						self.get_tokenizers(do_lower_case=a__							)
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						# a special token for Canine can be defined as follows:
																						lowerCAmelCase      						=						0XE_006
																						lowerCAmelCase      						=						chr(a__							)

																						lowerCAmelCase      						=						AddedToken(a__						,     lstrip=a__							)
																						tokenizer.add_special_tokens({'''additional_special_tokens''': [new_token]}							)

																						with tempfile.TemporaryDirectory() as tmp_dir_name:
																													tokenizer.save_pretrained(a__							)
																													tokenizer.from_pretrained(a__							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->List[str]:
								lowerCAmelCase      						=						[]
								if self.test_slow_tokenizer:
															tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

								if self.test_rust_tokenizer:
															tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

								for tokenizer_class, tokenizer_utils in tokenizer_list:
															with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer_utils.save_pretrained(a__							)

																						with open(os.path.join(a__						,     '''special_tokens_map.json'''							)						,     encoding='''utf-8'''							) as json_file:
																													lowerCAmelCase      						=						json.load(a__							)

																						with open(os.path.join(a__						,     '''tokenizer_config.json'''							)						,     encoding='''utf-8'''							) as json_file:
																													lowerCAmelCase      						=						json.load(a__							)

																						# a special token for Canine can be defined as follows:
																						lowerCAmelCase      						=						0XE_006
																						lowerCAmelCase      						=						chr(a__							)

																						lowerCAmelCase      						=						[new_token_a]
																						lowerCAmelCase      						=						[new_token_a]

																						with open(os.path.join(a__						,     '''special_tokens_map.json'''							)						,     '''w'''						,     encoding='''utf-8'''							) as outfile:
																													json.dump(a__						,     a__							)
																						with open(os.path.join(a__						,     '''tokenizer_config.json'''							)						,     '''w'''						,     encoding='''utf-8'''							) as outfile:
																													json.dump(a__						,     a__							)

																						# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																						# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																						# "special_tokens_map.json" files
																						lowerCAmelCase      						=						tokenizer_class.from_pretrained(a__						,     extra_ids=0							)
																						self.assertIn(a__						,     tokenizer_without_change_in_init.additional_special_tokens							)
																						# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																						self.assertEqual(
																						    [new_token_a]						,     tokenizer_without_change_in_init.convert_ids_to_tokens(
																						        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]							)							)						,     )

																						lowerCAmelCase      						=						0XE_007
																						lowerCAmelCase      						=						chr(a__							)
																						# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																						lowerCAmelCase      						=						[AddedToken(a__						,     lstrip=a__							)]
																						lowerCAmelCase      						=						tokenizer_class.from_pretrained(
																						    a__						,     additional_special_tokens=a__						,     extra_ids=0							)

																						self.assertIn(a__						,     tokenizer.additional_special_tokens							)
																						# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
																						self.assertEqual(
																						    [new_token_a]						,     tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]							)							)							)


	@require_tokenizers
	def      SCREAMING_SNAKE_CASE_							(				self							)		->List[str]:
								lowerCAmelCase      						=						self.get_tokenizers(do_lower_case=a__							)
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						lowerCAmelCase      						=						'''hello world'''
																						if self.space_between_special_tokens:
																													lowerCAmelCase      						=						'''[CLS] hello world [SEP]'''
																						else:
																													lowerCAmelCase      						=						input
																						lowerCAmelCase      						=						tokenizer.encode(a__						,     add_special_tokens=a__							)
																						lowerCAmelCase      						=						tokenizer.decode(a__						,     spaces_between_special_tokens=self.space_between_special_tokens							)
																						self.assertIn(a__						,     [output, output.lower()]							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Optional[int]:
								lowerCAmelCase      						=						self.get_tokenizers()
								for tokenizer in tokenizers:
															with self.subTest(F"{tokenizer.__class__.__name__}"							):
																						lowerCAmelCase      						=						[
																						    '''bos_token''',
																						    '''eos_token''',
																						    '''unk_token''',
																						    '''sep_token''',
																						    '''pad_token''',
																						    '''cls_token''',
																						    '''mask_token''',
																						]

								lowerCAmelCase      						=						'''a'''
								lowerCAmelCase      						=						ord(a__							)

								for attr in attributes_list:
															setattr(a__						,     attr + '''_id'''						,     a__							)
															self.assertEqual(getattr(a__						,     a__							)						,     a__							)
															self.assertEqual(getattr(a__						,     attr + '''_id'''							)						,     a__							)

															setattr(a__						,     attr + '''_id'''						,     a__							)
															self.assertEqual(getattr(a__						,     a__							)						,     a__							)
															self.assertEqual(getattr(a__						,     attr + '''_id'''							)						,     a__							)

								setattr(a__						,     '''additional_special_tokens_ids'''						,     []							)
								self.assertListEqual(getattr(a__						,     '''additional_special_tokens'''							)						,     []							)
								self.assertListEqual(getattr(a__						,     '''additional_special_tokens_ids'''							)						,     []							)

								lowerCAmelCase      						=						0XE_006
								lowerCAmelCase      						=						chr(a__							)
								setattr(a__						,     '''additional_special_tokens_ids'''						,     [additional_special_token_id]							)
								self.assertListEqual(getattr(a__						,     '''additional_special_tokens'''							)						,     [additional_special_token]							)
								self.assertListEqual(getattr(a__						,     '''additional_special_tokens_ids'''							)						,     [additional_special_token_id]							)


	def      SCREAMING_SNAKE_CASE_							(				self							)		->List[str]:
								pass


	def      SCREAMING_SNAKE_CASE_							(				self							)		->int:
								pass


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Any:
								pass


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Dict:
								pass


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Union[str, Any]:
								pass


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Optional[int]:
								pass


	def      SCREAMING_SNAKE_CASE_							(				self							)		->Tuple:
								pass




	def      SCREAMING_SNAKE_CASE_							(				self							)		->str:
								pass










import doctest
from collections import deque

import numpy as np







class       __A							:




      """simple docstring"""







      def __init__(		self):



             """simple docstring"""





             _lowerCamelCase				:  Any						=		[2, 1, 2, -1]
             _lowerCamelCase				:  Optional[int]						=		[1, 2, 3, 4]



      def 					__snake_case      (		self):



             """simple docstring"""





             _lowerCamelCase				:  Optional[int]						=		len(self.first_signal)
             _lowerCamelCase				:  str						=		len(self.second_signal)

             _lowerCamelCase				:  str						=		max(a__   ,				a__)

             # create a zero matrix of max_length x max_length
             _lowerCamelCase				:  Optional[Any]						=		[[0] * max_length for i in range(a__)]

             # fills the smaller signal with zeros to make both signals of same length
             if length_first_signal < length_second_signal:
                    self.first_signal += [0] * (max_length - length_first_signal)
             elif length_first_signal > length_second_signal:
                    self.second_signal += [0] * (max_length - length_second_signal)
             for i in range(a__):
                    _lowerCamelCase				:  Optional[Any]						=		deque(self.second_signal)
                    rotated_signal.rotate(a__)
                    for j, item in enumerate(a__):
                           matrix[i][j] += item

        # multiply the matrix with the first signal
             _lowerCamelCase				:  List[Any]						=		np.matmul(np.transpose(a__)   ,				np.transpose(self.first_signal))

             # rounding-off to two decimal places
             return [round(a__   ,				2) for i in final_signal]


if __name__ == "__main__":
       doctest.testmod()

