



# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


_lowercase: List[Any]      			=		subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8")
_lowercase: Any      			=		subprocess.check_output(F"""git diff --name-only {fork_point_sha}""".split()).decode("utf-8").split()

_lowercase: Tuple      			=		'|'.join(sys.argv[1:])
_lowercase: Any      			=		re.compile(rF"""^({joined_dirs}).*?\.py$""")

_lowercase: List[Any]      			=		[x for x in modified_files if regex.match(x)]
print(" ".join(relevant_modified_files), end="")








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			(						lowerCamelCase_				):






				'''simple docstring'''
				lowercase__    =			[]
				lowercase__    =			[]
				lowercase__    =			[]

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

				lowercase__    =			torch.tensor(
				    lowerCamelCase_		,   dtype=torch.intaa		,   device=protein['''aatype'''].device		,   )
				lowercase__    =			torch.tensor(
				    lowerCamelCase_		,   dtype=torch.intaa		,   device=protein['''aatype'''].device		,   )
				lowercase__    =			torch.tensor(
				    lowerCamelCase_		,   dtype=torch.floataa		,   device=protein['''aatype'''].device		,   )
				lowercase__    =			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
				lowercase__    =			restype_atomaa_to_atomaa[protein_aatype]
				lowercase__    =			restype_atomaa_mask[protein_aatype]

				lowercase__    =			residx_atomaa_mask
				lowercase__    =			residx_atomaa_to_atomaa.long()

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

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

				lowercase__    =			restype_atomaa_mask[protein_aatype]
				lowercase__    =			residx_atomaa_mask

				return protein






def   a			(						lowerCamelCase_				):






				'''simple docstring'''
				lowercase__    =			tree_map(lambda lowerCamelCase_				: torch.tensor(lowerCamelCase_		,   device=batch['''aatype'''].device				)		,   lowerCamelCase_		,   np.ndarray				)
				lowercase__    =			tensor_tree_map(lambda lowerCamelCase_				: np.array(lowerCamelCase_				)		,   make_atomaa_masks(lowerCamelCase_				)				)
				return out




