






from math import atan, cos, radians, sin, tan

from .haversine_distance import haversine_distance

UpperCAmelCase_ :						List[Any]      =      6_37_81_37.0
UpperCAmelCase_ :						Dict      =      6_35_67_52.31_42_45
UpperCAmelCase_ :						Tuple      =      6_37_81_37

def    SCREAMING_SNAKE_CASE_							(							__magic_name__					:  float	,			__magic_name__					:  float	,			__magic_name__					:  float	,			__magic_name__					:  float					)		->			float:






	"""simple docstring"""



	UpperCamelCase     :str          =	(AXIS_A - AXIS_B) / AXIS_A
	# Parametric latitudes
	# https://en.wikipedia.org/wiki/Latitude#Parametric_(or_reduced)_latitude
	UpperCamelCase     :List[str]          =	atan((1 - flattening) * tan(radians(__magic_name__					)					)					)
	UpperCamelCase     :Union[str, Any]          =	atan((1 - flattening) * tan(radians(__magic_name__					)					)					)

	# Compute central angle between two points
	# using haversine theta. sigma =  haversine_distance / equatorial radius
	UpperCamelCase     :Any          =	haversine_distance(__magic_name__	,			__magic_name__	,			__magic_name__	,			__magic_name__					) / EQUATORIAL_RADIUS

	# Intermediate P and Q values
	UpperCamelCase     :Tuple          =	(b_lata + b_lata) / 2
	UpperCamelCase     :Any          =	(b_lata - b_lata) / 2

	# Intermediate X value
	# X = (sigma - sin(sigma)) * sin^2Pcos^2Q / cos^2(sigma/2)
	UpperCamelCase     :Optional[int]          =	(sin(__magic_name__					) ** 2) * (cos(__magic_name__					) ** 2)
	UpperCamelCase     :Any          =	cos(sigma / 2					) ** 2
	UpperCamelCase     :Union[str, Any]          =	(sigma - sin(__magic_name__					)) * (x_numerator / x_demonimator)

	# Intermediate Y value
	# Y = (sigma + sin(sigma)) * cos^2Psin^2Q / sin^2(sigma/2)
	UpperCamelCase     :int          =	(cos(__magic_name__					) ** 2) * (sin(__magic_name__					) ** 2)
	UpperCamelCase     :Optional[Any]          =	sin(sigma / 2					) ** 2
	UpperCamelCase     :Any          =	(sigma + sin(__magic_name__					)) * (y_numerator / y_denominator)

	return EQUATORIAL_RADIUS * (sigma - ((flattening / 2) * (x_value + y_value)))


if __name__ == "__main__":
	import doctest

	doctest.testmod()


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							)

