





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      UpperCAmelCase_    (    _UpperCAmelCase							:Dict				)	->				int:
     '''simple docstring'''


     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(_A				)}
          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(
         _A  ,						dtype=torch.intaa  ,						device=protein['''aatype'''].device  ,						)
     A_          =       torch.tensor(
         _A  ,						dtype=torch.intaa  ,						device=protein['''aatype'''].device  ,						)
     A_          =       torch.tensor(
         _A  ,						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      UpperCAmelCase_    (    _UpperCAmelCase							:Dict				)	->				Any:
     '''simple docstring'''


     A_          =       tree_map(lambda _UpperCAmelCase				: torch.tensor(_A  ,						device=batch['''aatype'''].device				)  ,						_A  ,						np.ndarray				)
     A_          =       tensor_tree_map(lambda _UpperCAmelCase				: np.array(_A				)  ,						make_atomaa_masks(_A				)				)
     return out







'''simple docstring'''







import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class 						UpperCamelCase__       (			SCREAMING_SNAKE_CASE_     ,       unittest.TestCase						):



     """simple docstring"""






     __magic_name__           =     RoFormerTokenizer
     __magic_name__           =     RoFormerTokenizerFast
     __magic_name__           =     True
     __magic_name__           =     True







     def a						(			self ):

            '''simple docstring'''

            super().setUp()







     def a						(			self   ,						**snake_case__ ):

            '''simple docstring'''

            return self.tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'   ,						**snake_case__ )







     def a						(			self   ,						**snake_case__ ):

            '''simple docstring'''

            return self.rust_tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'   ,						**snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[Any]       =							'永和服装饰品有限公司,今天天气非常好'
            _lowerCAmelCase     :				str       =							'永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'
            return input_text, output_text







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Optional[int]       =							self.get_tokenizer()
            _lowerCAmelCase      ,  _lowerCAmelCase     :				int       =							self.get_chinese_input_output_texts()
            _lowerCAmelCase     :				List[Any]       =							tokenizer.tokenize(snake_case__ )

            self.assertListEqual(snake_case__   ,						output_text.split() )

            _lowerCAmelCase     :				Optional[Any]       =							tokens + [tokenizer.unk_token]
            _lowerCAmelCase     :				List[str]       =							[2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__ )   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				List[Any]       =							self.get_rust_tokenizer()
            _lowerCAmelCase      ,  _lowerCAmelCase     :				Any       =							self.get_chinese_input_output_texts()
            _lowerCAmelCase     :				Optional[int]       =							tokenizer.tokenize(snake_case__ )
            self.assertListEqual(snake_case__   ,						output_text.split() )
            _lowerCAmelCase     :				Tuple       =							tokens + [tokenizer.unk_token]
            _lowerCAmelCase     :				List[Any]       =							[2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__ )   ,						snake_case__ )







     def a						(			self ):

            '''simple docstring'''

            pass







     def a						(			self ):

            '''simple docstring'''

            pass







     def a						(			self ):

            '''simple docstring'''

            pass

