




"""simple docstring"""





import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
					A   =       """pt"""
elif is_tf_available():
					A   =       """tf"""
else:
					A   =       """jax"""



class      a__				(	__magic_name__							,    unittest.TestCase   ):
			lowercase_    =	PerceiverTokenizer
			lowercase_    =	False


			def       a_     (      self      :    Optional[int]):


						"""simple docstring"""




						super().setUp()
						__UpperCAmelCase	: Dict		=					PerceiverTokenizer()
						tokenizer.save_pretrained(self.tmpdirname)


			@cached_property
			def       a_     (      self      :    int):


						"""simple docstring"""




						return PerceiverTokenizer.from_pretrained("deepmind/language-perceiver")


			def       a_     (      self      :    Any      ,  **UpperCamelCase_      :    Optional[int]):


						"""simple docstring"""




						return self.tokenizer_class.from_pretrained(self.tmpdirname      ,  **UpperCamelCase_)


			def       a_     (      self      :    Optional[Any]      ,  UpperCamelCase_      :    List[Any]      ,  UpperCamelCase_      :    Any=False      ,  UpperCamelCase_      :    Dict=20      ,  UpperCamelCase_      :    Union[str, Any]=5):


						"""simple docstring"""




						__UpperCAmelCase	: Optional[int]		=					[]
						for i in range(len(UpperCamelCase_)):
									try:
												__UpperCAmelCase	: Union[str, Any]		=					tokenizer.decode([i]      ,  clean_up_tokenization_spaces=UpperCamelCase_)
									except UnicodeDecodeError:
												pass
									toks.append((i, tok))

						__UpperCAmelCase	: Union[str, Any]		=					list(filter(lambda UpperCamelCase_: re.match(r"^[ a-zA-Z]+$"      ,  t[1])      ,  UpperCamelCase_))
						__UpperCAmelCase	: Dict		=					list(filter(lambda UpperCamelCase_: [t[0]] == tokenizer.encode(t[1]      ,  add_special_tokens=UpperCamelCase_)      ,  UpperCamelCase_))
						if max_length is not None and len(UpperCamelCase_) > max_length:
									__UpperCAmelCase	: Dict		=					toks[:max_length]
						if min_length is not None and len(UpperCamelCase_) < min_length and len(UpperCamelCase_) > 0:
									while len(UpperCamelCase_) < min_length:
												__UpperCAmelCase	: int		=					toks + toks
        # toks_str = [t[1] for t in toks]
						__UpperCAmelCase	: Dict		=					[t[0] for t in toks]

						# Ensure consistency
						__UpperCAmelCase	: List[Any]		=					tokenizer.decode(UpperCamelCase_      ,  clean_up_tokenization_spaces=UpperCamelCase_)
						if " " not in output_txt and len(UpperCamelCase_) > 1:
									__UpperCAmelCase	: Optional[int]		=					(
									    tokenizer.decode([toks_ids[0]]      ,  clean_up_tokenization_spaces=UpperCamelCase_)
									    + " "
									    + tokenizer.decode(toks_ids[1:]      ,  clean_up_tokenization_spaces=UpperCamelCase_)
									)
						if with_prefix_space:
									__UpperCAmelCase	: int		=					" " + output_txt
						__UpperCAmelCase	: Optional[Any]		=					tokenizer.encode(UpperCamelCase_      ,  add_special_tokens=UpperCamelCase_)
						return output_txt, output_ids


			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase	: int		=					self.perceiver_tokenizer
						__UpperCAmelCase	: Any		=					"Unicode €."
						__UpperCAmelCase	: Union[str, Any]		=					tokenizer(UpperCamelCase_)
						__UpperCAmelCase	: Optional[Any]		=					[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
						self.assertEqual(encoded["input_ids"]      ,  UpperCamelCase_)

						# decoding
						__UpperCAmelCase	: List[Any]		=					tokenizer.decode(UpperCamelCase_)
						self.assertEqual(UpperCamelCase_      ,  "[CLS]Unicode €.[SEP]")

						__UpperCAmelCase	: Tuple		=					tokenizer("e è é ê ë")
						__UpperCAmelCase	: Dict		=					[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
						self.assertEqual(encoded["input_ids"]      ,  UpperCamelCase_)
						# decoding
						__UpperCAmelCase	: Dict		=					tokenizer.decode(UpperCamelCase_)
						self.assertEqual(UpperCamelCase_      ,  "[CLS]e è é ê ë[SEP]")

						# encode/decode, but with `encode` instead of `__call__`
						self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë"))      ,  "[CLS]e è é ê ë[SEP]")


			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					self.perceiver_tokenizer
						__UpperCAmelCase	: int		=					["A long paragraph for summarization.", "Another paragraph for summarization."]
						# fmt: off
						__UpperCAmelCase	: List[str]		=					[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
						# fmt: on
						__UpperCAmelCase	: str		=					tokenizer(UpperCamelCase_      ,  padding=UpperCamelCase_      ,  return_tensors=UpperCamelCase_)
						self.assertIsInstance(UpperCamelCase_      ,  UpperCamelCase_)

						if FRAMEWORK != "jax":
									__UpperCAmelCase	: Dict		=					list(batch.input_ids.numpy()[0])
						else:
									__UpperCAmelCase	: Tuple		=					list(batch.input_ids.tolist()[0])

						self.assertListEqual(UpperCamelCase_      ,  UpperCamelCase_)

						self.assertEqual((2, 38)      ,  batch.input_ids.shape)
						self.assertEqual((2, 38)      ,  batch.attention_mask.shape)


			def       a_     (      self      :    str):


						"""simple docstring"""




						__UpperCAmelCase	: int		=					self.perceiver_tokenizer
						__UpperCAmelCase	: Union[str, Any]		=					["A long paragraph for summarization.", "Another paragraph for summarization."]
						__UpperCAmelCase	: Union[str, Any]		=					tokenizer(UpperCamelCase_      ,  padding=UpperCamelCase_      ,  return_tensors=UpperCamelCase_)
						# check if input_ids are returned and no decoder_input_ids
						self.assertIn("input_ids"      ,  UpperCamelCase_)
						self.assertIn("attention_mask"      ,  UpperCamelCase_)
						self.assertNotIn("decoder_input_ids"      ,  UpperCamelCase_)
						self.assertNotIn("decoder_attention_mask"      ,  UpperCamelCase_)


			def       a_     (      self      :    Tuple):


						"""simple docstring"""




						__UpperCAmelCase	: Tuple		=					self.perceiver_tokenizer
						__UpperCAmelCase	: Dict		=					[
						    "Summary of the text.",
						    "Another summary.",
						]
						__UpperCAmelCase	: Optional[int]		=					tokenizer(
						    text_target=UpperCamelCase_      ,  max_length=32      ,  padding="max_length"      ,  truncation=UpperCamelCase_      ,  return_tensors=UpperCamelCase_)
						self.assertEqual(32      ,  targets["input_ids"].shape[1])


			def       a_     (      self      :    Any):


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					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
						__UpperCAmelCase	: Optional[Any]		=					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
												__UpperCAmelCase	: Tuple		=					tempfile.mkdtemp()

												__UpperCAmelCase	: List[str]		=					" He is very happy, UNwant\u00E9d,running"
												__UpperCAmelCase	: str		=					tokenizer.encode(UpperCamelCase_      ,  add_special_tokens=UpperCamelCase_)
												tokenizer.save_pretrained(UpperCamelCase_)

												__UpperCAmelCase	: List[str]		=					tokenizer.__class__.from_pretrained(UpperCamelCase_)
												__UpperCAmelCase	: Optional[int]		=					after_tokenizer.encode(UpperCamelCase_      ,  add_special_tokens=UpperCamelCase_)
												self.assertListEqual(UpperCamelCase_      ,  UpperCamelCase_)

												shutil.rmtree(UpperCamelCase_)

						__UpperCAmelCase	: List[str]		=					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
												__UpperCAmelCase	: str		=					tempfile.mkdtemp()

												__UpperCAmelCase	: Optional[Any]		=					" He is very happy, UNwant\u00E9d,running"
												tokenizer.add_tokens(["bim", "bambam"])
												__UpperCAmelCase	: str		=					tokenizer.additional_special_tokens
												additional_special_tokens.append("new_additional_special_token")
												tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens})
												__UpperCAmelCase	: Tuple		=					tokenizer.encode(UpperCamelCase_      ,  add_special_tokens=UpperCamelCase_)
												tokenizer.save_pretrained(UpperCamelCase_)

												__UpperCAmelCase	: Optional[Any]		=					tokenizer.__class__.from_pretrained(UpperCamelCase_)
												__UpperCAmelCase	: str		=					after_tokenizer.encode(UpperCamelCase_      ,  add_special_tokens=UpperCamelCase_)
												self.assertListEqual(UpperCamelCase_      ,  UpperCamelCase_)
												self.assertIn("new_additional_special_token"      ,  after_tokenizer.additional_special_tokens)
												self.assertEqual(after_tokenizer.model_max_length      ,  42)

												__UpperCAmelCase	: Union[str, Any]		=					tokenizer.__class__.from_pretrained(UpperCamelCase_      ,  model_max_length=43)
												self.assertEqual(tokenizer.model_max_length      ,  43)

												shutil.rmtree(UpperCamelCase_)


			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase	: List[Any]		=					[]
						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(UpperCamelCase_)

												with open(os.path.join(UpperCamelCase_      ,  "special_tokens_map.json")      ,  encoding="utf-8") as json_file:
															__UpperCAmelCase	: int		=					json.load(UpperCamelCase_)

												with open(os.path.join(UpperCamelCase_      ,  "tokenizer_config.json")      ,  encoding="utf-8") as json_file:
															__UpperCAmelCase	: Tuple		=					json.load(UpperCamelCase_)

												__UpperCAmelCase	: str		=					[F"<extra_id_{i}>" for i in range(125)]

												__UpperCAmelCase	: List[Any]		=					added_tokens_extra_ids + [
												    "an_additional_special_token"
												]
												__UpperCAmelCase	: Optional[int]		=					added_tokens_extra_ids + [
												    "an_additional_special_token"
												]

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

												# 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
												__UpperCAmelCase	: Tuple		=					tokenizer_class.from_pretrained(
												    UpperCamelCase_      ,  )
												self.assertIn(
												    "an_additional_special_token"      ,  tokenizer_without_change_in_init.additional_special_tokens)
												self.assertEqual(
												    ["an_additional_special_token"]      ,  tokenizer_without_change_in_init.convert_ids_to_tokens(
												        tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"]))      ,  )

												# Now we test that we can change the value of additional_special_tokens in the from_pretrained
												__UpperCAmelCase	: int		=					added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"      ,  lstrip=UpperCamelCase_)]
												__UpperCAmelCase	: Union[str, Any]		=					tokenizer_class.from_pretrained(
												    UpperCamelCase_      ,  additional_special_tokens=UpperCamelCase_      ,  )

												self.assertIn("a_new_additional_special_token"      ,  tokenizer.additional_special_tokens)
												self.assertEqual(
												    ["a_new_additional_special_token"]      ,  tokenizer.convert_ids_to_tokens(
												        tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"]))      ,  )


			def       a_     (      self      :    Union[str, Any]):


						"""simple docstring"""




						__UpperCAmelCase	: List[Any]		=					self.perceiver_tokenizer
						self.assertEqual(tokenizer.decode([178])      ,  "�")


			def       a_     (      self      :    Dict):


						"""simple docstring"""




						pass


			def       a_     (      self      :    str):


						"""simple docstring"""




						pass


			def       a_     (      self      :    int):


						"""simple docstring"""




						pass


			def       a_     (      self      :    Tuple):


						"""simple docstring"""




						pass


			def       a_     (      self      :    Any):


						"""simple docstring"""




						__UpperCAmelCase	: Dict		=					self.get_tokenizers(fast=UpperCamelCase_      ,  do_lower_case=UpperCamelCase_)
						for tokenizer in tokenizers:
									with self.subTest(F"{tokenizer.__class__.__name__}"):
												__UpperCAmelCase	: Any		=					["[CLS]", "t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "s", "t", "[SEP]"]
												__UpperCAmelCase	: Optional[Any]		=					tokenizer.convert_tokens_to_string(UpperCamelCase_)

												self.assertIsInstance(UpperCamelCase_      ,  UpperCamelCase_)








"""simple docstring"""





from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: List[str]		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[int]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Any		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: Tuple		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Optional[Any]		=					(1 - _cos) / 2
			__UpperCAmelCase	: Any		=					1 - _cos

			__UpperCAmelCase	: List[str]		=					1 + alpha
			__UpperCAmelCase	: List[Any]		=					-2 * _cos
			__UpperCAmelCase	: Dict		=					1 - alpha

			__UpperCAmelCase	: str		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: int		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[Any]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Dict		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: Tuple		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Dict		=					(1 + _cos) / 2
			__UpperCAmelCase	: Tuple		=					-1 - _cos

			__UpperCAmelCase	: Any		=					1 + alpha
			__UpperCAmelCase	: int		=					-2 * _cos
			__UpperCAmelCase	: int		=					1 - alpha

			__UpperCAmelCase	: Union[str, Any]		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: Tuple		=					tau * frequency / samplerate
			__UpperCAmelCase	: Tuple		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: List[str]		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: List[Any]		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Any		=					_sin / 2
			__UpperCAmelCase	: Optional[int]		=					0
			__UpperCAmelCase	: int		=					-ba

			__UpperCAmelCase	: Dict		=					1 + alpha
			__UpperCAmelCase	: List[str]		=					-2 * _cos
			__UpperCAmelCase	: int		=					1 - alpha

			__UpperCAmelCase	: int		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)							)			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: str		=					tau * frequency / samplerate
			__UpperCAmelCase	: List[Any]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Any		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: List[str]		=					_sin / (2 * q_factor)

			__UpperCAmelCase	: Optional[Any]		=					1 - alpha
			__UpperCAmelCase	: Tuple		=					-2 * _cos
			__UpperCAmelCase	: List[Any]		=					1 + alpha

			__UpperCAmelCase	: str		=					IIRFilter(2							)
			filt.set_coefficients([ba, ba, ba]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)				,       )			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: Dict		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[int]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Optional[Any]		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: List[Any]		=					_sin / (2 * q_factor)
			__UpperCAmelCase	: List[Any]		=					10 ** (gain_db / 40)

			__UpperCAmelCase	: List[str]		=					1 + alpha * big_a
			__UpperCAmelCase	: Optional[Any]		=					-2 * _cos
			__UpperCAmelCase	: int		=					1 - alpha * big_a
			__UpperCAmelCase	: Optional[int]		=					1 + alpha / big_a
			__UpperCAmelCase	: Union[str, Any]		=					-2 * _cos
			__UpperCAmelCase	: Dict		=					1 - alpha / big_a

			__UpperCAmelCase	: Dict		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt

def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)				,       )			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: str		=					tau * frequency / samplerate
			__UpperCAmelCase	: int		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Optional[Any]		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: str		=					_sin / (2 * q_factor)
			__UpperCAmelCase	: str		=					10 ** (gain_db / 40)
			__UpperCAmelCase	: Union[str, Any]		=					(big_a + 1) - (big_a - 1) * _cos
			__UpperCAmelCase	: Optional[int]		=					(big_a + 1) + (big_a - 1) * _cos
			__UpperCAmelCase	: List[str]		=					(big_a - 1) - (big_a + 1) * _cos
			__UpperCAmelCase	: List[Any]		=					(big_a - 1) + (big_a + 1) * _cos
			__UpperCAmelCase	: Optional[Any]		=					2 * sqrt(UpperCamelCase							) * alpha

			__UpperCAmelCase	: Tuple		=					big_a * (pmc + aaa)
			__UpperCAmelCase	: Union[str, Any]		=					2 * big_a * mpc
			__UpperCAmelCase	: Optional[int]		=					big_a * (pmc - aaa)
			__UpperCAmelCase	: Any		=					ppmc + aaa
			__UpperCAmelCase	: Dict		=					-2 * pmpc
			__UpperCAmelCase	: Any		=					ppmc - aaa

			__UpperCAmelCase	: str		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt





def 					_UpperCamelCase    (			UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase				,       UpperCamelCase = 1 / sqrt(2							)				,       )			->			IIRFilter:


			"""simple docstring"""
			__UpperCAmelCase	: Dict		=					tau * frequency / samplerate
			__UpperCAmelCase	: Optional[int]		=					sin(UpperCamelCase							)
			__UpperCAmelCase	: Dict		=					cos(UpperCamelCase							)
			__UpperCAmelCase	: str		=					_sin / (2 * q_factor)
			__UpperCAmelCase	: int		=					10 ** (gain_db / 40)
			__UpperCAmelCase	: Optional[Any]		=					(big_a + 1) - (big_a - 1) * _cos
			__UpperCAmelCase	: Optional[int]		=					(big_a + 1) + (big_a - 1) * _cos
			__UpperCAmelCase	: Union[str, Any]		=					(big_a - 1) - (big_a + 1) * _cos
			__UpperCAmelCase	: Tuple		=					(big_a - 1) + (big_a + 1) * _cos
			__UpperCAmelCase	: Optional[Any]		=					2 * sqrt(UpperCamelCase							) * alpha

			__UpperCAmelCase	: Tuple		=					big_a * (ppmc + aaa)
			__UpperCAmelCase	: Any		=					-2 * big_a * pmpc
			__UpperCAmelCase	: int		=					big_a * (ppmc - aaa)
			__UpperCAmelCase	: int		=					pmc + aaa
			__UpperCAmelCase	: Tuple		=					2 * mpc
			__UpperCAmelCase	: Union[str, Any]		=					pmc - aaa

			__UpperCAmelCase	: Any		=					IIRFilter(2							)
			filt.set_coefficients([aa, aa, aa]				,       [ba, ba, ba]							)
			return filt


