Coverage for hyper_parallel / core / shard / ops / parallel_tuple_elementwise.py: 83%

1# Copyright 2025 Huawei Technologies Co., Ltd 

2# 

3# Licensed under the Apache License, Version 2.0 (the "License"); 

4# you may not use this file except in compliance with the License. 

5# You may obtain a copy of the License at 

6# 

7# http://www.apache.org/licenses/LICENSE-2.0 

8# 

9# Unless required by applicable law or agreed to in writing, software 

10# distributed under the License is distributed on an "AS IS" BASIS, 

11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

12# See the License for the specific language governing permissions and 

13# limitations under the License. 

14# ============================================================================ 

15""" 

16Element-wise distributed operator implementation. 

17""" 

18 

19from .parallel_ops import DistributedOp 

20 

21class TupleElementWiseDistributedOp(DistributedOp): 

22 """ 

23 Distributed implementation for tuple element-wise operators. 

24 

25 Inherits from DistributedOp and provides element-wise specific implementations. 

26 """ 

27 def infer_layout(self, layouts, extra_args): 

28 """ 

29 Infer output layouts for element-wise operations. 

30 

31 For element-wise operations, all inputs should have the same layout, 

32 and the output will have the same layout. 

33 

34 Args: 

35 primitive: Primitive instance 

36 layouts: Layouts of input tensors 

37 

38 Returns: 

39 tuple: Layout for output tensor. 

40 

41 Raises: 

42 ValueError: If input layouts are not compatible. 

43 """ 

44 if not layouts: 

45 return None 

46 

47 return layouts