






from typing import Dict

import numpy as np
import torch

from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict[str, torch.Tensor]     ):
	snake_case__				:   Any     =						[]
	snake_case__				:   Dict     =						[]
	snake_case__				:   Tuple     =						[]

	for rt in rc.restypes:
		snake_case__				:   Dict     =						rc.restype_name_to_atomaa_names[rc.restype_atoa[rt]]
		restype_atomaa_to_atomaa_list.append([(rc.atom_order[name] if name else 0) for name in atom_names]     )
		snake_case__				:   Dict     =						{name: i for i, name in enumerate(snake_case_     )}
		restype_atomaa_to_atomaa_list.append(
		    [(atom_name_to_idxaa[name] if name in atom_name_to_idxaa else 0) for name in rc.atom_types]     )

		restype_atomaa_mask_list.append([(1.0 if name else 0.0) for name in atom_names]     )

	# Add dummy mapping for restype 'UNK'
	restype_atomaa_to_atomaa_list.append([0] * 14     )
	restype_atomaa_to_atomaa_list.append([0] * 37     )
	restype_atomaa_mask_list.append([0.0] * 14     )

	snake_case__				:   int     =						torch.tensor(
	    snake_case_  ,						dtype=torch.intaa  ,						device=protein["aatype"].device  ,						)
	snake_case__				:   List[str]     =						torch.tensor(
	    snake_case_  ,						dtype=torch.intaa  ,						device=protein["aatype"].device  ,						)
	snake_case__				:   List[Any]     =						torch.tensor(
	    snake_case_  ,						dtype=torch.floataa  ,						device=protein["aatype"].device  ,						)
	snake_case__				:   Optional[Any]     =						protein["aatype"].to(torch.long     )

	# create the mapping for (residx, atom14) --> atom37, i.e. an array
	# with shape (num_res, 14) containing the atom37 indices for this protein
	snake_case__				:   List[Any]     =						restype_atomaa_to_atomaa[protein_aatype]
	snake_case__				:   Any     =						restype_atomaa_mask[protein_aatype]

	snake_case__				:   List[str]     =						residx_atomaa_mask
	snake_case__				:   List[Any]     =						residx_atomaa_to_atomaa.long()

	# create the gather indices for mapping back
	snake_case__				:   Union[str, Any]     =						restype_atomaa_to_atomaa[protein_aatype]
	snake_case__				:   Union[str, Any]     =						residx_atomaa_to_atomaa.long()

	# create the corresponding mask
	snake_case__				:   Tuple     =						torch.zeros([21, 37]  ,						dtype=torch.floataa  ,						device=protein["aatype"].device     )
	for restype, restype_letter in enumerate(rc.restypes     ):
		snake_case__				:   Any     =						rc.restype_atoa[restype_letter]
		snake_case__				:   Optional[Any]     =						rc.residue_atoms[restype_name]
		for atom_name in atom_names:
			snake_case__				:   List[Any]     =						rc.atom_order[atom_name]
			snake_case__				:   Union[str, Any]     =						1

	snake_case__				:   Dict     =						restype_atomaa_mask[protein_aatype]
	snake_case__				:   Any     =						residx_atomaa_mask

	return protein







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict[str, torch.Tensor]     ):
	snake_case__				:   Union[str, Any]     =						tree_map(lambda snake_case_     : torch.tensor(snake_case_  ,						device=batch["aatype"].device     )  ,						snake_case_  ,						np.ndarray     )
	snake_case__				:   int     =						tensor_tree_map(lambda snake_case_     : np.array(snake_case_     )  ,						make_atomaa_masks(snake_case_     )     )
	return out











from __future__ import annotations







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
	snake_case__				:   str     =						[True] * limit
	snake_case__				:   str     =						False
	snake_case__				:   str     =						False
	snake_case__				:   str     =						True

	for i in range(3  ,						int(limit**0.5 + 1     )  ,						2     ):
		snake_case__				:   Optional[Any]     =						i * 2
		while index < limit:
			snake_case__				:   Union[str, Any]     =						False
			snake_case__				:   Any     =						index + i

	snake_case__				:   Optional[Any]     =						[2]

	for i in range(3  ,						snake_case_  ,						2     ):
		if is_prime[i]:
			primes.append(snake_case_     )

	return primes







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int = 1000000     ):
	snake_case__				:   Optional[int]     =						prime_sieve(snake_case_     )
	snake_case__				:   List[Any]     =						0
	snake_case__				:   List[str]     =						0

	for i in range(len(snake_case_     )     ):
		for j in range(i + length  ,						len(snake_case_     )     ):
			snake_case__				:   Dict     =						sum(primes[i:j]     )
			if sol >= ceiling:
				break

			if sol in primes:
				snake_case__				:   Tuple     =						j - i
				snake_case__				:   str     =						sol

	return largest


if __name__ == "__main__":
	print(f"{solution() = }")



