


'''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      (      lowerCAmelCase    :     Dict[str, torch.Tensor]		):





	"""simple docstring"""







	__magic_name__	:   Optional[Any]					     =					[]
	__magic_name__	:   str					     =					[]
	__magic_name__	:   Optional[Any]					     =					[]

	for rt in rc.restypes:
		__magic_name__	:   Tuple					     =					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]		)
		__magic_name__	:   Optional[int]					     =					{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		)

	__magic_name__	:   Dict					     =					torch.tensor(
	    lowerCAmelCase		,		dtype=torch.intaa		,		device=protein['aatype'].device		,		)
	__magic_name__	:   Union[str, Any]					     =					torch.tensor(
	    lowerCAmelCase		,		dtype=torch.intaa		,		device=protein['aatype'].device		,		)
	__magic_name__	:   Dict					     =					torch.tensor(
	    lowerCAmelCase		,		dtype=torch.floataa		,		device=protein['aatype'].device		,		)
	__magic_name__	:   Optional[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
	__magic_name__	:   Any					     =					restype_atomaa_to_atomaa[protein_aatype]
	__magic_name__	:   int					     =					restype_atomaa_mask[protein_aatype]

	__magic_name__	:   Optional[Any]					     =					residx_atomaa_mask
	__magic_name__	:   Any					     =					residx_atomaa_to_atomaa.long()

	# create the gather indices for mapping back
	__magic_name__	:   Any					     =					restype_atomaa_to_atomaa[protein_aatype]
	__magic_name__	:   Optional[int]					     =					residx_atomaa_to_atomaa.long()

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

	__magic_name__	:   List[str]					     =					restype_atomaa_mask[protein_aatype]
	__magic_name__	:   List[str]					     =					residx_atomaa_mask

	return protein





def lowerCamelCase      (      lowerCAmelCase    :     Dict[str, torch.Tensor]		):





	"""simple docstring"""







	__magic_name__	:   Tuple					     =					tree_map(lambda lowerCAmelCase		: torch.tensor(lowerCAmelCase		,		device=batch['aatype'].device		)		,		lowerCAmelCase		,		np.ndarray		)
	__magic_name__	:   Optional[int]					     =					tensor_tree_map(lambda lowerCAmelCase		: np.array(lowerCAmelCase		)		,		make_atomaa_masks(lowerCAmelCase		)		)
	return out



'''simple docstring'''

import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowerCamelCase	(						lowercase__		,					unittest.TestCase							):



		'''simple docstring'''







		A_     :      Optional[Any]				   =    LxmertTokenizer
		A_     :      List[Any]				   =    LxmertTokenizerFast
		A_     :      int				   =    True
		A_     :      Any				   =    True







		def        __lowerCAmelCase		( self		:						List[str]      )  ->			Tuple:
			super().setUp()

			__magic_name__	:   str					     =					[
			    '[UNK]',
			    '[CLS]',
			    '[SEP]',
			    'want',
			    '##want',
			    '##ed',
			    'wa',
			    'un',
			    'runn',
			    '##ing',
			    ',',
			    'low',
			    'lowest',
			]
			__magic_name__	:   List[str]					     =					os.path.join(self.tmpdirname  ,					VOCAB_FILES_NAMES['vocab_file']      )
			with open(self.vocab_file  ,					'w'  ,					encoding='utf-8'      ) as vocab_writer:
				vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]      )      )







		def        __lowerCAmelCase		( self		:						Any  ,					_A		:						str      )  ->			List[Any]:
			__magic_name__	:   Dict					     =					'UNwant\u00E9d,running'
			__magic_name__	:   Dict					     =					'unwanted, running'
			return input_text, output_text







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Optional[int]:
			__magic_name__	:   Optional[Any]					     =					self.tokenizer_class(self.vocab_file      )

			__magic_name__	:   List[str]					     =					tokenizer.tokenize('UNwant\u00E9d,running'      )
			self.assertListEqual(_A  ,					['un', '##want', '##ed', ',', 'runn', '##ing']      )
			self.assertListEqual(tokenizer.convert_tokens_to_ids(_A      )  ,					[7, 4, 5, 10, 8, 9]      )







		def        __lowerCAmelCase		( self		:						int      )  ->			List[Any]:
			if not self.test_rust_tokenizer:
				return

			__magic_name__	:   Any					     =					self.get_tokenizer()
			__magic_name__	:   Optional[Any]					     =					self.get_rust_tokenizer()

			__magic_name__	:   Union[str, Any]					     =					'I was born in 92000, and this is falsé.'

			__magic_name__	:   List[Any]					     =					tokenizer.tokenize(_A      )
			__magic_name__	:   Dict					     =					rust_tokenizer.tokenize(_A      )
			self.assertListEqual(_A  ,					_A      )

			__magic_name__	:   int					     =					tokenizer.encode(_A  ,					add_special_tokens=_A      )
			__magic_name__	:   Union[str, Any]					     =					rust_tokenizer.encode(_A  ,					add_special_tokens=_A      )
			self.assertListEqual(_A  ,					_A      )

			__magic_name__	:   List[Any]					     =					self.get_rust_tokenizer()
			__magic_name__	:   str					     =					tokenizer.encode(_A      )
			__magic_name__	:   Optional[int]					     =					rust_tokenizer.encode(_A      )
			self.assertListEqual(_A  ,					_A      )