

'''simple docstring'''






from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def 		_A     (    A__     ,				A__     ,				A__ = 1 / sqrt(2      )      ):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)

 __lowercase							  = (1 - _cos) / 2
 __lowercase							  = 1 - _cos

 __lowercase							  = 1 + alpha
 __lowercase							  = -2 * _cos
 __lowercase							  = 1 - alpha

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([aa, aa, aa]     ,				[ba, ba, ba]      )
 return filt


def 		_A     (    A__     ,				A__     ,				A__ = 1 / sqrt(2      )      ):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)

 __lowercase							  = (1 + _cos) / 2
 __lowercase							  = -1 - _cos

 __lowercase							  = 1 + alpha
 __lowercase							  = -2 * _cos
 __lowercase							  = 1 - alpha

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([aa, aa, aa]     ,				[ba, ba, ba]      )
 return filt


def 		_A     (    A__     ,				A__     ,				A__ = 1 / sqrt(2      )      ):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)

 __lowercase							  = _sin / 2
 __lowercase							  = 0
 __lowercase							  = -ba

 __lowercase							  = 1 + alpha
 __lowercase							  = -2 * _cos
 __lowercase							  = 1 - alpha

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([aa, aa, aa]     ,				[ba, ba, ba]      )
 return filt


def 		_A     (    A__     ,				A__     ,				A__ = 1 / sqrt(2      )      ):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)

 __lowercase							  = 1 - alpha
 __lowercase							  = -2 * _cos
 __lowercase							  = 1 + alpha

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([ba, ba, ba]     ,				[ba, ba, ba]      )
 return filt


def 		_A     (    A__     ,				A__     ,				A__     ,				A__ = 1 / sqrt(2      )     ,				):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)
 __lowercase							  = 10 ** (gain_db / 40)

 __lowercase							  = 1 + alpha * big_a
 __lowercase							  = -2 * _cos
 __lowercase							  = 1 - alpha * big_a
 __lowercase							  = 1 + alpha / big_a
 __lowercase							  = -2 * _cos
 __lowercase							  = 1 - alpha / big_a

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([aa, aa, aa]     ,				[ba, ba, ba]      )
 return filt


def 		_A     (    A__     ,				A__     ,				A__     ,				A__ = 1 / sqrt(2      )     ,				):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)
 __lowercase							  = 10 ** (gain_db / 40)
 __lowercase							  = (big_a + 1) - (big_a - 1) * _cos
 __lowercase							  = (big_a + 1) + (big_a - 1) * _cos
 __lowercase							  = (big_a - 1) - (big_a + 1) * _cos
 __lowercase							  = (big_a - 1) + (big_a + 1) * _cos
 __lowercase							  = 2 * sqrt(A__      ) * alpha

 __lowercase							  = big_a * (pmc + aaa)
 __lowercase							  = 2 * big_a * mpc
 __lowercase							  = big_a * (pmc - aaa)
 __lowercase							  = ppmc + aaa
 __lowercase							  = -2 * pmpc
 __lowercase							  = ppmc - aaa

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([aa, aa, aa]     ,				[ba, ba, ba]      )
 return filt






def 		_A     (    A__     ,				A__     ,				A__     ,				A__ = 1 / sqrt(2      )     ,				):






 """simple docstring"""



 __lowercase							  = tau * frequency / samplerate
 __lowercase							  = sin(A__      )
 __lowercase							  = cos(A__      )
 __lowercase							  = _sin / (2 * q_factor)
 __lowercase							  = 10 ** (gain_db / 40)
 __lowercase							  = (big_a + 1) - (big_a - 1) * _cos
 __lowercase							  = (big_a + 1) + (big_a - 1) * _cos
 __lowercase							  = (big_a - 1) - (big_a + 1) * _cos
 __lowercase							  = (big_a - 1) + (big_a + 1) * _cos
 __lowercase							  = 2 * sqrt(A__      ) * alpha

 __lowercase							  = big_a * (ppmc + aaa)
 __lowercase							  = -2 * big_a * pmpc
 __lowercase							  = big_a * (ppmc - aaa)
 __lowercase							  = pmc + aaa
 __lowercase							  = 2 * mpc
 __lowercase							  = pmc - aaa

 __lowercase							  = IIRFilter(2      )
 filt.set_coefficients([aa, aa, aa]     ,				[ba, ba, ba]      )
 return filt



import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


UpperCAmelCase	      = logging.get_logger(__name__)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	lowercase       =    r'\w+[.]\d+'
	lowercase       =    re.findall(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)
	for pat in pats:
		lowercase       =    key.replace(__SCREAMING_SNAKE_CASE ,							'_'.join(pat.split('.'							)							)							)
	return key






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	lowercase       =    pt_tuple_key[:-1] + ('scale',)
	if (
	    any('norm' in str_ for str_ in pt_tuple_key							)
	    and (pt_tuple_key[-1] == "bias")
	    and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
	    and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
	):
		lowercase       =    pt_tuple_key[:-1] + ('scale',)
		return renamed_pt_tuple_key, pt_tensor
	elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
		lowercase       =    pt_tuple_key[:-1] + ('scale',)
		return renamed_pt_tuple_key, pt_tensor

	# embedding
	if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
		lowercase       =    pt_tuple_key[:-1] + ('embedding',)
		return renamed_pt_tuple_key, pt_tensor

	# conv layer
	lowercase       =    pt_tuple_key[:-1] + ('kernel',)
	if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
		lowercase       =    pt_tensor.transpose(2 ,							3 ,							1 ,							0							)
		return renamed_pt_tuple_key, pt_tensor

	# linear layer
	lowercase       =    pt_tuple_key[:-1] + ('kernel',)
	if pt_tuple_key[-1] == "weight":
		lowercase       =    pt_tensor.T
		return renamed_pt_tuple_key, pt_tensor

	# old PyTorch layer norm weight
	lowercase       =    pt_tuple_key[:-1] + ('weight',)
	if pt_tuple_key[-1] == "gamma":
		return renamed_pt_tuple_key, pt_tensor

	# old PyTorch layer norm bias
	lowercase       =    pt_tuple_key[:-1] + ('bias',)
	if pt_tuple_key[-1] == "beta":
		return renamed_pt_tuple_key, pt_tensor

	return pt_tuple_key, pt_tensor






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE=42							):
	# Step 1: Convert pytorch tensor to numpy
	lowercase       =    {k: v.numpy() for k, v in pt_state_dict.items()}

	# Step 2: Since the model is stateless, get random Flax params
	lowercase       =    flax_model.init_weights(PRNGKey(__SCREAMING_SNAKE_CASE							)							)

	lowercase       =    flatten_dict(__SCREAMING_SNAKE_CASE							)
	lowercase       =    {}

	# Need to change some parameters name to match Flax names
	for pt_key, pt_tensor in pt_state_dict.items():
		lowercase       =    rename_key(__SCREAMING_SNAKE_CASE							)
		lowercase       =    tuple(renamed_pt_key.split('.'							)							)

		# Correctly rename weight parameters
		lowercase  ,					lowercase       =    rename_key_and_reshape_tensor(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)

		if flax_key in random_flax_state_dict:
			if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
				raise ValueError(
				    F'''PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape '''
				    F'''{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}.'''							)

        # also add unexpected weight so that warning is thrown
		lowercase       =    jnp.asarray(__SCREAMING_SNAKE_CASE							)

	return unflatten_dict(__SCREAMING_SNAKE_CASE							)

