"""simple docstring"""




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_fnet import FNetTokenizer
else:
				__lowerCamelCase											=  None

__lowerCamelCase											=  logging.get_logger(__name__)
__lowerCamelCase											=  {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

__lowerCamelCase											=  {
    "vocab_file": {
        "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/spiece.model",
        "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/spiece.model",
    },
    "tokenizer_file": {
        "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json",
        "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json",
    },
}

__lowerCamelCase											=  {
    "google/fnet-base": 5_12,
    "google/fnet-large": 5_12,
}

__lowerCamelCase											=  "▁"
class     UpperCamelCase__(			__A ):
						lowerCAmelCase__  :						Tuple													=		VOCAB_FILES_NAMES
						lowerCAmelCase__  :						Optional[Any]													=		PRETRAINED_VOCAB_FILES_MAP
						lowerCAmelCase__  :						Tuple													=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						lowerCAmelCase__  :						Union[str, Any]													=		['input_ids', 'token_type_ids']
						lowerCAmelCase__  :						str													=		FNetTokenizer





						def __init__(       self		,__UpperCAmelCase=None		,__UpperCAmelCase=None		,__UpperCAmelCase=False		,__UpperCAmelCase=True		,__UpperCAmelCase=True		,__UpperCAmelCase="<unk>"		,__UpperCAmelCase="[SEP]"		,__UpperCAmelCase="<pad>"		,__UpperCAmelCase="[CLS]"		,__UpperCAmelCase="[MASK]"		,**__UpperCAmelCase		,)					->				Tuple:
													# Mask token behave like a normal word, i.e. include the space before it and
													# is included in the raw text, there should be a match in a non-normalized sentence.
													A__	     =							(
													    AddedToken(__UpperCAmelCase		,lstrip=__UpperCAmelCase		,rstrip=__UpperCAmelCase		,normalized=__UpperCAmelCase     )
													    if isinstance(__UpperCAmelCase		,__UpperCAmelCase     )
													    else mask_token
													)

													super().__init__(
													    __UpperCAmelCase		,tokenizer_file=__UpperCAmelCase		,do_lower_case=__UpperCAmelCase		,remove_space=__UpperCAmelCase		,keep_accents=__UpperCAmelCase		,unk_token=__UpperCAmelCase		,sep_token=__UpperCAmelCase		,pad_token=__UpperCAmelCase		,cls_token=__UpperCAmelCase		,mask_token=__UpperCAmelCase		,**__UpperCAmelCase		,)

													A__	     =							do_lower_case
													A__	     =							remove_space
													A__	     =							keep_accents
													A__	     =							vocab_file
													A__	     =							False if not self.vocab_file else True





						def 				snake_case__	(       self		,__UpperCAmelCase		,__UpperCAmelCase = None     )					->				List[int]:
													A__	     =							[self.sep_token_id]
													A__	     =							[self.cls_token_id]
													if token_ids_a is None:
																				return cls + token_ids_a + sep
													return cls + token_ids_a + sep + token_ids_a + sep





						def 				snake_case__	(       self		,__UpperCAmelCase		,__UpperCAmelCase = None     )					->				List[int]:
													A__	     =							[self.sep_token_id]
													A__	     =							[self.cls_token_id]

													if token_ids_a is None:
																				return len(cls + token_ids_a + sep     ) * [0]
													return len(cls + token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1]





						def 				snake_case__	(       self		,__UpperCAmelCase		,__UpperCAmelCase = None     )					->				Tuple[str]:
													if not os.path.isdir(__UpperCAmelCase     ):
																				logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
																				return
													A__	     =							os.path.join(
													    __UpperCAmelCase		,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )

													if os.path.abspath(self.vocab_file     ) != os.path.abspath(__UpperCAmelCase     ):
																				copyfile(self.vocab_file		,__UpperCAmelCase     )

													return (out_vocab_file,)






"""simple docstring"""




from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np
class     UpperCamelCase__(			__A ):





						def 				snake_case__	(       self		,__UpperCAmelCase     )					->				float:
													return 0.0






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							min([-20, np.min(fft_results[1 : samplerate // 2 - 1]				)]				)
							A__	     =							max([20, np.max(fft_results[1 : samplerate // 2 - 1]				)]				)
							return lowest, highest






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							512
							A__	     =							[1] + [0] * (size - 1)
							A__	     =							[filter_type.process(UpperCamelCase__				) for item in inputs]

							A__	     =							[0] * (samplerate - size)  # zero-padding
							outputs += filler
							A__	     =							np.abs(np.fft.fft(UpperCamelCase__				)				)
							A__	     =							20 * np.logaa(UpperCamelCase__				)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24       ,    samplerate / 2 - 1				)
							plt.xlabel('Frequency (Hz)'				)
							plt.xscale('log'				)

							# Display within reasonable bounds
							A__	     =							get_bounds(UpperCamelCase__       ,    UpperCamelCase__				)
							plt.ylim(max([-80, bounds[0]]				)       ,    min([80, bounds[1]]				)				)
							plt.ylabel('Gain (dB)'				)

							plt.plot(UpperCamelCase__				)
							plt.show()






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							512
							A__	     =							[1] + [0] * (size - 1)
							A__	     =							[filter_type.process(UpperCamelCase__				) for item in inputs]

							A__	     =							[0] * (samplerate - size)  # zero-padding
							outputs += filler
							A__	     =							np.angle(np.fft.fft(UpperCamelCase__				)				)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24       ,    samplerate / 2 - 1				)
							plt.xlabel('Frequency (Hz)'				)
							plt.xscale('log'				)

							plt.ylim(-2 * pi       ,    2 * pi				)
							plt.ylabel('Phase shift (Radians)'				)
							plt.plot(np.unwrap(UpperCamelCase__       ,    -2 * pi				)				)
							plt.show()





