Coverage for  / home / jenkins / .local / lib / python3.10 / site-packages / hyper_parallel / platform / mindspore / custom_ops / custom_ops.py: 69%

1# Copyright 2026 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"""MindSpore platform custom ops delegation to DFunction wrappers. 

16 

17.. warning:: 

18 This is an experimental API that subject to change or deletion. 

19""" 

20 

21from hyper_parallel.platform.mindspore.custom_ops.custom_op_impl import ( 

22 NpuDenseLightningIndexerGradKlLossDFunction, 

23 NpuDenseLightningIndexerSoftmaxLseDFunction, 

24 NpuLightningIndexerDFunction, 

25 NpuMhcPostDFunction, 

26 NpuMhcPreClampSinkhornDFunction, 

27 NpuMhcPreSinkhornDFunction, 

28 NpuSparseFlashMlaDFunction, 

29 NpuSparseLightningIndexerGradKlLossDFunction, 

30 NpuSparseLightningIndexerKlLossGradDFunction, 

31 npu_sparse_flash_mla_grad as _npu_sparse_flash_mla_grad, 

32) 

33 

34 

35class MindSporeCustomOps: 

36 """Delegates custom operator calls to DFunction-based implementations.""" 

37 

38 @staticmethod 

39 def npu_dense_lightning_indexer_softmax_lse(*args, **kwargs): 

40 """Compute dense lightning indexer softmax log-sum-exp via custom NPU operator.""" 

41 return NpuDenseLightningIndexerSoftmaxLseDFunction.apply(*args, **kwargs) 

42 

43 @staticmethod 

44 def npu_dense_lightning_indexer_grad_kl_loss(*args, **kwargs): 

45 """Compute dense lightning indexer KL-loss gradient via custom NPU operator.""" 

46 return NpuDenseLightningIndexerGradKlLossDFunction.apply(*args, **kwargs) 

47 

48 @staticmethod 

49 def npu_sparse_lightning_indexer_grad_kl_loss(*args, **kwargs): 

50 """Compute sparse lightning indexer KL-loss gradient via custom NPU operator.""" 

51 return NpuSparseLightningIndexerGradKlLossDFunction.apply(*args, **kwargs) 

52 

53 @staticmethod 

54 def npu_mhc_post(*args, **kwargs): 

55 """Apply the NPU MHC post-processing custom operator.""" 

56 return NpuMhcPostDFunction.apply(*args, **kwargs) 

57 

58 @staticmethod 

59 def npu_mhc_pre_sinkhorn(*args, **kwargs): 

60 """Apply the NPU MHC pre-Sinkhorn custom operator.""" 

61 return NpuMhcPreSinkhornDFunction.apply(*args, **kwargs) 

62 

63 @staticmethod 

64 def npu_mhc_pre_clamp_sinkhorn(*args, **kwargs): 

65 """Apply the clamped NPU MHC pre-Sinkhorn custom operator.""" 

66 return NpuMhcPreClampSinkhornDFunction.apply(*args, **kwargs) 

67 

68 @staticmethod 

69 def npu_lightning_indexer(*args, **kwargs): 

70 """Sparse-attention preprocessing (top-K key selection) via custom NPU operator.""" 

71 return NpuLightningIndexerDFunction.apply(*args, **kwargs) 

72 

73 @staticmethod 

74 def npu_sparse_flash_mla(*args, **kwargs): 

75 """MLA sparse attention (forward + grad + metadata) via custom NPU operator.""" 

76 return NpuSparseFlashMlaDFunction.apply(*args, **kwargs) 

77 

78 @staticmethod 

79 def npu_sparse_flash_mla_grad(*args, **kwargs): 

80 """Raw MLA sparse-attention backward kernel — returns 6 outputs including 

81 ``ori/cmp_softmax_l1_norm``. Stateless passthrough for use inside a 

82 network-defined custom backward (no autograd).""" 

83 return _npu_sparse_flash_mla_grad(*args, **kwargs) 

84 

85 @staticmethod 

86 def npu_sparse_lightning_indexer_kl_loss_grad(*args, **kwargs): 

87 """Sparse lightning indexer KL-loss gradient via custom NPU operator.""" 

88 return NpuSparseLightningIndexerKlLossGradDFunction.apply(*args, **kwargs)