

"""simple docstring"""


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     a__    (    __SCREAMING_SNAKE_CASE )	->	Dict[str, torch.Tensor]:
		__lowerCAmelCase:       Optional[Any]          =			[]
		__lowerCAmelCase:       Dict          =			[]
		__lowerCAmelCase:       Optional[int]          =			[]

		for rt in rc.restypes:
				__lowerCAmelCase:       Any          =			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] )
				__lowerCAmelCase:       Any          =			{name: i for i, name in enumerate(__SCREAMING_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] * 1_4 )
		restype_atomaa_to_atomaa_list.append([0] * 3_7 )
		restype_atomaa_mask_list.append([0.0] * 1_4 )

		__lowerCAmelCase:       int          =			torch.tensor(
		    __SCREAMING_SNAKE_CASE					, dtype=torch.intaa					, device=protein["aatype"].device					, )
		__lowerCAmelCase:       Optional[int]          =			torch.tensor(
		    __SCREAMING_SNAKE_CASE					, dtype=torch.intaa					, device=protein["aatype"].device					, )
		__lowerCAmelCase:       List[Any]          =			torch.tensor(
		    __SCREAMING_SNAKE_CASE					, dtype=torch.floataa					, device=protein["aatype"].device					, )
		__lowerCAmelCase:       int          =			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
		__lowerCAmelCase:       Union[str, Any]          =			restype_atomaa_to_atomaa[protein_aatype]
		__lowerCAmelCase:       Union[str, Any]          =			restype_atomaa_mask[protein_aatype]

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

		# create the gather indices for mapping back
		__lowerCAmelCase:       List[Any]          =			restype_atomaa_to_atomaa[protein_aatype]
		__lowerCAmelCase:       Dict          =			residx_atomaa_to_atomaa.long()

		# create the corresponding mask
		__lowerCAmelCase:       Tuple          =			torch.zeros([2_1, 3_7]					, dtype=torch.floataa					, device=protein["aatype"].device )
		for restype, restype_letter in enumerate(rc.restypes ):
				__lowerCAmelCase:       Union[str, Any]          =			rc.restype_atoa[restype_letter]
				__lowerCAmelCase:       Union[str, Any]          =			rc.residue_atoms[restype_name]
				for atom_name in atom_names:
						__lowerCAmelCase:       Optional[int]          =			rc.atom_order[atom_name]
						__lowerCAmelCase:       Optional[int]          =			1

		__lowerCAmelCase:       Union[str, Any]          =			restype_atomaa_mask[protein_aatype]
		__lowerCAmelCase:       List[Any]          =			residx_atomaa_mask

		return protein






def     a__    (    __SCREAMING_SNAKE_CASE )	->	Dict[str, np.ndarray]:
		__lowerCAmelCase:       Optional[Any]          =			tree_map(lambda __SCREAMING_SNAKE_CASE : torch.tensor(__SCREAMING_SNAKE_CASE					, device=batch["aatype"].device )					, __SCREAMING_SNAKE_CASE					, np.ndarray )
		__lowerCAmelCase:       List[Any]          =			tensor_tree_map(lambda __SCREAMING_SNAKE_CASE : np.array(__SCREAMING_SNAKE_CASE )					, make_atomaa_masks(__SCREAMING_SNAKE_CASE ) )
		return out





"""simple docstring"""


from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url






@pytest.mark.parametrize("repo_id"					, ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path"					, ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parametrize("revision"					, [None, "v2"] )
def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE )	->	List[str]:
		__lowerCAmelCase:       Optional[Any]          =			hf_hub_url(repo_id=__SCREAMING_SNAKE_CASE					, path=__SCREAMING_SNAKE_CASE					, revision=__SCREAMING_SNAKE_CASE )
		assert url == F"https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(__SCREAMING_SNAKE_CASE )}"


