





'''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  _lowerCamelCase				( lowercase						:      Dict[str, torch.Tensor]						)	->	Dict[str, torch.Tensor]:
				_a								= []
				_a								= []
				_a								= []

				for rt in rc.restypes:
								_a								= 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]						)
								_a								= {name: i for i, name in enumerate(lowercase						)}
								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						)

				_a								= torch.tensor(
				    lowercase    ,							dtype=torch.intaa    ,							device=protein["aatype"].device    ,							)
				_a								= torch.tensor(
				    lowercase    ,							dtype=torch.intaa    ,							device=protein["aatype"].device    ,							)
				_a								= torch.tensor(
				    lowercase    ,							dtype=torch.floataa    ,							device=protein["aatype"].device    ,							)
				_a								= 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
				_a								= restype_atomaa_to_atomaa[protein_aatype]
				_a								= restype_atomaa_mask[protein_aatype]

				_a								= residx_atomaa_mask
				_a								= residx_atomaa_to_atomaa.long()

				# create the gather indices for mapping back
				_a								= restype_atomaa_to_atomaa[protein_aatype]
				_a								= residx_atomaa_to_atomaa.long()

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

				_a								= restype_atomaa_mask[protein_aatype]
				_a								= residx_atomaa_mask

				return protein






def  _lowerCamelCase				( lowercase						:      Dict[str, torch.Tensor]						)	->	Dict[str, np.ndarray]:
				_a								= tree_map(lambda lowercase						: torch.tensor(lowercase    ,							device=batch["aatype"].device						)    ,							lowercase    ,							np.ndarray						)
				_a								= tensor_tree_map(lambda lowercase						: np.array(lowercase						)    ,							make_atomaa_masks(lowercase						)						)
				return out







'''simple docstring'''







import argparse
import os
import re


lowerCAmelCase_					:    Any      	=			'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
lowerCAmelCase_					:    List[str]      	=			re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
lowerCAmelCase_					:    Tuple      	=			re.compile(R'\s*\(\s*"(\S[^"]+)"')






def  _lowerCamelCase				( lowercase						:      Any    ,							lowercase						:      bool = False						)	->	Optional[Any]:
				with open(lowercase    ,							"r"    ,							encoding="utf-8"						) as f:
								_a								= f.read()

				_a								= content.split("\n"						)
				_a								= []
				_a								= 0
				while line_idx < len(lowercase						):
								if _re_intro_mapping.search(lines[line_idx]						) is not None:
												_a								= len(re.search(r"^(\s*)\S"    ,							lines[line_idx]						).groups()[0]						) + 8
												# Start of a new mapping!
												while not lines[line_idx].startswith(" " * indent + "("						):
																new_lines.append(lines[line_idx]						)
																line_idx += 1

												_a								= []
												while lines[line_idx].strip() != "]":
																# Blocks either fit in one line or not
																if lines[line_idx].strip() == "(":
																				_a								= line_idx
																				while not lines[line_idx].startswith(" " * indent + ")"						):
																								line_idx += 1
																				blocks.append("\n".join(lines[start_idx : line_idx + 1]						)						)
																else:
																				blocks.append(lines[line_idx]						)
																line_idx += 1

												# Sort blocks by their identifiers
												_a								= sorted(lowercase    ,							key=lambda lowercase						: _re_identifier.search(lowercase						).groups()[0]						)
												new_lines += blocks
								else:
												new_lines.append(lines[line_idx]						)
												line_idx += 1

				if overwrite:
								with open(lowercase    ,							"w"    ,							encoding="utf-8"						) as f:
												f.write("\n".join(lowercase						)						)
				elif "\n".join(lowercase						) != content:
								return True






def  _lowerCamelCase				( lowercase						:      bool = False						)	->	List[str]:
				_a								= [os.path.join(lowercase    ,							lowercase						) for f in os.listdir(lowercase						) if f.endswith(".py"						)]
				_a								= [sort_auto_mapping(lowercase    ,							overwrite=lowercase						) for fname in fnames]

				if not overwrite and any(lowercase						):
								_a								= [f for f, d in zip(lowercase    ,							lowercase						) if d]
								raise ValueError(
								    F'The following files have auto mappings that need sorting: {", ".join(lowercase						)}. Run `make style` to fix'
								    " this."						)


if __name__ == "__main__":
					lowerCAmelCase_					:    Any      	=			argparse.ArgumentParser()
					parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
					lowerCAmelCase_					:    Optional[int]      	=			parser.parse_args()

					sort_all_auto_mappings(not args.check_only)
