




"""simple docstring"""

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
       from PIL import Image

       from transformers import AlignProcessor, EfficientNetImageProcessor





@require_vision
class 							lowercase_			(	unittest.TestCase				):



 '''simple docstring'''

 def      lowerCAmelCase_				(					self			:			List[Any]						):
       _A     =  tempfile.mkdtemp()

       _A     =  [
           """[UNK]""",
           """[CLS]""",
           """[SEP]""",
           """[PAD]""",
           """[MASK]""",
           """want""",
           """##want""",
           """##ed""",
           """wa""",
           """un""",
           """runn""",
           """##ing""",
           """,""",
           """low""",
           """lowest""",
       ]
       _A     =  os.path.join(self.tmpdirname       ,				VOCAB_FILES_NAMES['vocab_file']						)
       with open(self.vocab_file       ,				'w'       ,				encoding='utf-8'						) as vocab_writer:
             vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]						)						)

       _A     =  {
           """do_resize""": True,
           """size""": 20,
           """do_center_crop""": True,
           """crop_size""": 18,
           """do_normalize""": True,
           """image_mean""": [0.4814_5466, 0.457_8275, 0.4082_1073],
           """image_std""": [0.2686_2954, 0.2613_0258, 0.2757_7711],
       }
       _A     =  os.path.join(self.tmpdirname       ,				lowerCamelCase__						)
       with open(self.image_processor_file       ,				'w'       ,				encoding='utf-8'						) as fp:
             json.dump(lowerCamelCase__       ,				lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Tuple       ,				**_UpperCAmelCase			:			Tuple						):
       return BertTokenizer.from_pretrained(self.tmpdirname       ,				**lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Dict       ,				**_UpperCAmelCase			:			List[str]						):
       return BertTokenizerFast.from_pretrained(self.tmpdirname       ,				**lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				**_UpperCAmelCase			:			Dict						):
       return EfficientNetImageProcessor.from_pretrained(self.tmpdirname       ,				**lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       shutil.rmtree(self.tmpdirname						)

 def      lowerCAmelCase_				(					self			:			int						):
       _A     =  [np.random.randint(255       ,				size=(3, 30, 400)       ,				dtype=np.uinta						)]
       _A     =  [Image.fromarray(np.moveaxis(lowerCamelCase__       ,				0       ,				-1						)						) for x in image_inputs]
       return image_inputs

 def      lowerCAmelCase_				(					self			:			Any						):
       _A     =  self.get_tokenizer()
       _A     =  self.get_rust_tokenizer()
       _A     =  self.get_image_processor()

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)
       processor_slow.save_pretrained(self.tmpdirname						)
       _A     =  AlignProcessor.from_pretrained(self.tmpdirname       ,				use_fast=lowerCamelCase__						)

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)
       processor_fast.save_pretrained(self.tmpdirname						)
       _A     =  AlignProcessor.from_pretrained(self.tmpdirname						)

       self.assertEqual(processor_slow.tokenizer.get_vocab()       ,				tokenizer_slow.get_vocab()						)
       self.assertEqual(processor_fast.tokenizer.get_vocab()       ,				tokenizer_fast.get_vocab()						)
       self.assertEqual(tokenizer_slow.get_vocab()       ,				tokenizer_fast.get_vocab()						)
       self.assertIsInstance(processor_slow.tokenizer       ,				lowerCamelCase__						)
       self.assertIsInstance(processor_fast.tokenizer       ,				lowerCamelCase__						)

       self.assertEqual(processor_slow.image_processor.to_json_string()       ,				image_processor.to_json_string()						)
       self.assertEqual(processor_fast.image_processor.to_json_string()       ,				image_processor.to_json_string()						)
       self.assertIsInstance(processor_slow.image_processor       ,				lowerCamelCase__						)
       self.assertIsInstance(processor_fast.image_processor       ,				lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _A     =  AlignProcessor(tokenizer=self.get_tokenizer()       ,				image_processor=self.get_image_processor()						)
       processor.save_pretrained(self.tmpdirname						)

       _A     =  self.get_tokenizer(bos_token='(BOS)'       ,				eos_token='(EOS)'						)
       _A     =  self.get_image_processor(do_normalize=lowerCamelCase__       ,				padding_value=1.0						)

       _A     =  AlignProcessor.from_pretrained(
           self.tmpdirname       ,				bos_token='(BOS)'       ,				eos_token='(EOS)'       ,				do_normalize=lowerCamelCase__       ,				padding_value=1.0						)

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

       self.assertEqual(processor.image_processor.to_json_string()       ,				image_processor_add_kwargs.to_json_string()						)
       self.assertIsInstance(processor.image_processor       ,				lowerCamelCase__						)

 def      lowerCAmelCase_				(					self			:			Tuple						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)

       _A     =  self.prepare_image_inputs()

       _A     =  image_processor(lowerCamelCase__       ,				return_tensors='np'						)
       _A     =  processor(images=lowerCamelCase__       ,				return_tensors='np'						)

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

 def      lowerCAmelCase_				(					self			:			str						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)

       _A     =  """lower newer"""

       _A     =  processor(text=lowerCamelCase__						)

       _A     =  tokenizer(lowerCamelCase__       ,				padding='max_length'       ,				max_length=64						)

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

 def      lowerCAmelCase_				(					self			:			int						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)

       _A     =  """lower newer"""
       _A     =  self.prepare_image_inputs()

       _A     =  processor(text=lowerCamelCase__       ,				images=lowerCamelCase__						)

       self.assertListEqual(list(inputs.keys()						)       ,				['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values']						)

       # test if it raises when no input is passed
       with pytest.raises(lowerCamelCase__						):
             processor()

 def      lowerCAmelCase_				(					self			:			Any						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)

       _A     =  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       _A     =  processor.batch_decode(lowerCamelCase__						)
       _A     =  tokenizer.batch_decode(lowerCamelCase__						)

       self.assertListEqual(lowerCamelCase__       ,				lowerCamelCase__						)



 def      lowerCAmelCase_				(					self			:			Optional[int]						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  AlignProcessor(tokenizer=lowerCamelCase__       ,				image_processor=lowerCamelCase__						)

       _A     =  """lower newer"""
       _A     =  self.prepare_image_inputs()

       _A     =  processor(text=lowerCamelCase__       ,				images=lowerCamelCase__						)

       self.assertListEqual(list(inputs.keys()						)       ,				processor.model_input_names						)





"""simple docstring"""


from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       str				=						tau * frequency / samplerate
 lowercase__       :       Union[str, Any]				=						sin(lowerCamelCase__  )
 lowercase__       :       int				=						cos(lowerCamelCase__  )
 lowercase__       :       Union[str, Any]				=						_sin / (2 * q_factor)

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

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

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


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       Optional[int]				=						tau * frequency / samplerate
 lowercase__       :       Any				=						sin(lowerCamelCase__  )
 lowercase__       :       Any				=						cos(lowerCamelCase__  )
 lowercase__       :       Tuple				=						_sin / (2 * q_factor)

 lowercase__       :       Tuple				=						(1 + _cos) / 2
 lowercase__       :       str				=						-1 - _cos

 lowercase__       :       Dict				=						1 + alpha
 lowercase__       :       Dict				=						-2 * _cos
 lowercase__       :       int				=						1 - alpha

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


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       Optional[int]				=						tau * frequency / samplerate
 lowercase__       :       str				=						sin(lowerCamelCase__  )
 lowercase__       :       int				=						cos(lowerCamelCase__  )
 lowercase__       :       Dict				=						_sin / (2 * q_factor)

 lowercase__       :       Dict				=						_sin / 2
 lowercase__       :       Union[str, Any]				=						0
 lowercase__       :       int				=						-ba

 lowercase__       :       List[Any]				=						1 + alpha
 lowercase__       :       Tuple				=						-2 * _cos
 lowercase__       :       List[str]				=						1 - alpha

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


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )  ):
 lowercase__       :       str				=						tau * frequency / samplerate
 lowercase__       :       Dict				=						sin(lowerCamelCase__  )
 lowercase__       :       Union[str, Any]				=						cos(lowerCamelCase__  )
 lowercase__       :       Tuple				=						_sin / (2 * q_factor)

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

 lowercase__       :       List[Any]				=						IIRFilter(2  )
 filt.set_coefficients([ba, ba, ba]       ,		[ba, ba, ba]  )
 return filt


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )       ,		):
 lowercase__       :       Tuple				=						tau * frequency / samplerate
 lowercase__       :       str				=						sin(lowerCamelCase__  )
 lowercase__       :       List[str]				=						cos(lowerCamelCase__  )
 lowercase__       :       Optional[int]				=						_sin / (2 * q_factor)
 lowercase__       :       Optional[Any]				=						10 ** (gain_db / 40)

 lowercase__       :       Optional[Any]				=						1 + alpha * big_a
 lowercase__       :       Dict				=						-2 * _cos
 lowercase__       :       Tuple				=						1 - alpha * big_a
 lowercase__       :       List[str]				=						1 + alpha / big_a
 lowercase__       :       List[Any]				=						-2 * _cos
 lowercase__       :       Optional[int]				=						1 - alpha / big_a

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


def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )       ,		):
 lowercase__       :       Optional[int]				=						tau * frequency / samplerate
 lowercase__       :       Dict				=						sin(lowerCamelCase__  )
 lowercase__       :       Union[str, Any]				=						cos(lowerCamelCase__  )
 lowercase__       :       int				=						_sin / (2 * q_factor)
 lowercase__       :       Union[str, Any]				=						10 ** (gain_db / 40)
 lowercase__       :       Dict				=						(big_a + 1) - (big_a - 1) * _cos
 lowercase__       :       Union[str, Any]				=						(big_a + 1) + (big_a - 1) * _cos
 lowercase__       :       List[Any]				=						(big_a - 1) - (big_a + 1) * _cos
 lowercase__       :       Dict				=						(big_a - 1) + (big_a + 1) * _cos
 lowercase__       :       Optional[int]				=						2 * sqrt(lowerCamelCase__  ) * alpha

 lowercase__       :       str				=						big_a * (pmc + aaa)
 lowercase__       :       Optional[Any]				=						2 * big_a * mpc
 lowercase__       :       str				=						big_a * (pmc - aaa)
 lowercase__       :       Dict				=						ppmc + aaa
 lowercase__       :       List[Any]				=						-2 * pmpc
 lowercase__       :       List[Any]				=						ppmc - aaa

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






def    _lowerCamelCase   (     lowerCamelCase__	:							int       ,		lowerCamelCase__	:							int       ,		lowerCamelCase__	:							float       ,		lowerCamelCase__	:							float = 1 / sqrt(2  )       ,		):
 lowercase__       :       int				=						tau * frequency / samplerate
 lowercase__       :       List[Any]				=						sin(lowerCamelCase__  )
 lowercase__       :       List[Any]				=						cos(lowerCamelCase__  )
 lowercase__       :       List[str]				=						_sin / (2 * q_factor)
 lowercase__       :       int				=						10 ** (gain_db / 40)
 lowercase__       :       str				=						(big_a + 1) - (big_a - 1) * _cos
 lowercase__       :       Optional[Any]				=						(big_a + 1) + (big_a - 1) * _cos
 lowercase__       :       Optional[int]				=						(big_a - 1) - (big_a + 1) * _cos
 lowercase__       :       int				=						(big_a - 1) + (big_a + 1) * _cos
 lowercase__       :       Optional[Any]				=						2 * sqrt(lowerCamelCase__  ) * alpha

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

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