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2048
已合并
[feat] support lstm grad a5 #8768
nextyale创建于 8月17日
[feat] support lstm grad a5 #8768
已合并
nextyale创建于 8月17日
从nextyale/ops-nnlstmA5final合入到cann/ops-nnmaster
共 6 个文件变更+512-28
Mrnn/single_layer_lstm_grad/README.md+22-22
Nice tryNice try8月17日

缺少docs下的aclnnLstmBackward产品支持情况更新

likedislike
Jjisihuai8月17日

ops-nn/docs/zh/op_list.md中存量列表缺失该算子，建议一并补充

likedislike
@@ -4,7 +4,7 @@
4 4 
5| 产品 | 是否支持 |5| 产品 | 是否支持 |
6| :------------------------------------------------------------------------------ | :------: |6| :------------------------------------------------------------------------------ | :------: |
7-| <term>Ascend 950PR/Ascend 950DT</term> | × |7+| <term>Ascend 950PR/Ascend 950DT</term> | √ |
8| <term>Atlas A3 训练系列产品/Atlas A3 推理系列产品</term> | √ |8| <term>Atlas A3 训练系列产品/Atlas A3 推理系列产品</term> | √ |
9| <term>Atlas A2 训练系列产品/Atlas A2 推理系列产品</term> | √ |9| <term>Atlas A2 训练系列产品/Atlas A2 推理系列产品</term> | √ |
10| <term>Atlas 200I/500 A2 推理产品</term> | × |10| <term>Atlas 200I/500 A2 推理产品</term> | × |
@@ -55,89 +55,89 @@ $$
55### 循环 $t = T - 1$ 到 $0$55### 循环 $t = T - 1$ 到 $0$
56 56 
571. **当前隐藏状态梯度**571. **当前隐藏状态梯度**
58- 58+ 
59 $$59 $$
60 \delta\mathbf{h}_t = \frac{\partial L_t}{\partial \mathbf{h}_t} + \delta\mathbf{h}_{\text{next}}60 \delta\mathbf{h}_t = \frac{\partial L_t}{\partial \mathbf{h}_t} + \delta\mathbf{h}_{\text{next}}
61 $$61 $$
622. **当前细胞状态梯度**622. **当前细胞状态梯度**
63- 63+ 
64 $$64 $$
65 \delta\mathbf{c}_t = \delta\mathbf{h}_t \odot \mathbf{o}_t \odot (1 - \tanh^2(\mathbf{c}_t)) + \delta\mathbf{c}_{\text{next}} \odot \mathbf{f}_{\text{next}}65 \delta\mathbf{c}_t = \delta\mathbf{h}_t \odot \mathbf{o}_t \odot (1 - \tanh^2(\mathbf{c}_t)) + \delta\mathbf{c}_{\text{next}} \odot \mathbf{f}_{\text{next}}
66 $$66 $$
673. **门控梯度计算**673. **门控梯度计算**
68- 68+ 
69 $$69 $$
70 \delta\mathbf{o}_t = \delta\mathbf{h}_t \odot \tanh(\mathbf{c}_t) \odot \mathbf{o}_t \odot (1 - \mathbf{o}_t)70 \delta\mathbf{o}_t = \delta\mathbf{h}_t \odot \tanh(\mathbf{c}_t) \odot \mathbf{o}_t \odot (1 - \mathbf{o}_t)
71 $$71 $$
72- 72+ 
73 $$73 $$
74 \delta\mathbf{g}_t = \delta\mathbf{c}_t \odot \mathbf{i}_t \odot (1 - \mathbf{g}_t^2)74 \delta\mathbf{g}_t = \delta\mathbf{c}_t \odot \mathbf{i}_t \odot (1 - \mathbf{g}_t^2)
75 $$75 $$
76- 76+ 
77 $$77 $$
78 \delta\mathbf{i}_t = \delta\mathbf{c}_t \odot \mathbf{g}_t \odot \mathbf{i}_t \odot (1 - \mathbf{i}_t)78 \delta\mathbf{i}_t = \delta\mathbf{c}_t \odot \mathbf{g}_t \odot \mathbf{i}_t \odot (1 - \mathbf{i}_t)
79 $$79 $$
80- 80+ 
81 $$81 $$
82 \delta\mathbf{f}_t = \delta\mathbf{c}_t \odot \mathbf{c}_{t-1} \odot \mathbf{f}_t \odot (1 - \mathbf{f}_t)82 \delta\mathbf{f}_t = \delta\mathbf{c}_t \odot \mathbf{c}_{t-1} \odot \mathbf{f}_t \odot (1 - \mathbf{f}_t)
83 $$83 $$
844. **参数梯度累加**844. **参数梯度累加**
85- 85+ 
86 $$86 $$
87 \frac{\partial L}{\partial \mathbf{W}_f} \mathrel{+}= \delta\mathbf{f}_t \mathbf{z}_t^\top87 \frac{\partial L}{\partial \mathbf{W}_f} \mathrel{+}= \delta\mathbf{f}_t \mathbf{z}_t^\top
88 $$88 $$
89- 89+ 
90 $$90 $$
91 \frac{\partial L}{\partial \mathbf{b}_f} \mathrel{+}= \delta\mathbf{f}_t91 \frac{\partial L}{\partial \mathbf{b}_f} \mathrel{+}= \delta\mathbf{f}_t
92 $$92 $$
93- 93+ 
94 $$94 $$
95 \frac{\partial L}{\partial \mathbf{W}_i} \mathrel{+}= \delta\mathbf{i}_t \mathbf{z}_t^\top95 \frac{\partial L}{\partial \mathbf{W}_i} \mathrel{+}= \delta\mathbf{i}_t \mathbf{z}_t^\top
96 $$96 $$
97- 97+ 
98 $$98 $$
99 \frac{\partial L}{\partial \mathbf{b}_i} \mathrel{+}= \delta\mathbf{i}_t99 \frac{\partial L}{\partial \mathbf{b}_i} \mathrel{+}= \delta\mathbf{i}_t
100 $$100 $$
101- 101+ 
102 $$102 $$
103 \frac{\partial L}{\partial \mathbf{W}_g} \mathrel{+}= \delta\mathbf{g}_t \mathbf{z}_t^\top103 \frac{\partial L}{\partial \mathbf{W}_g} \mathrel{+}= \delta\mathbf{g}_t \mathbf{z}_t^\top
104 $$104 $$
105- 105+ 
106 $$106 $$
107 \frac{\partial L}{\partial \mathbf{b}_g} \mathrel{+}= \delta\mathbf{g}_t107 \frac{\partial L}{\partial \mathbf{b}_g} \mathrel{+}= \delta\mathbf{g}_t
108 $$108 $$
109- 109+ 
110 $$110 $$
111 \frac{\partial L}{\partial \mathbf{W}_o} \mathrel{+}= \delta\mathbf{o}_t \mathbf{z}_t^\top111 \frac{\partial L}{\partial \mathbf{W}_o} \mathrel{+}= \delta\mathbf{o}_t \mathbf{z}_t^\top
112 $$112 $$
113- 113+ 
114 $$114 $$
115 \frac{\partial L}{\partial \mathbf{b}_o} \mathrel{+}= \delta\mathbf{o}_t115 \frac{\partial L}{\partial \mathbf{b}_o} \mathrel{+}= \delta\mathbf{o}_t
116 $$116 $$
1175. **传播到前一时刻**1175. **传播到前一时刻**
118- 118+ 
119 $$119 $$
120- 120+ 
121 \delta\mathbf{z}_t = \mathbf{W}_f^\top \delta\mathbf{f}_t + \mathbf{W}_i^\top \delta\mathbf{i}_t + \mathbf{W}_g^\top \delta\mathbf{g}_t + \mathbf{W}_o^\top \delta\mathbf{o}_t121 \delta\mathbf{z}_t = \mathbf{W}_f^\top \delta\mathbf{f}_t + \mathbf{W}_i^\top \delta\mathbf{i}_t + \mathbf{W}_g^\top \delta\mathbf{g}_t + \mathbf{W}_o^\top \delta\mathbf{o}_t
122 $$122 $$
123- 123+ 
124 $$124 $$
125 \delta\mathbf{h}_{\text{prev}} = \delta\mathbf{z}_t[1:\dim(\mathbf{h}_{t-1})]125 \delta\mathbf{h}_{\text{prev}} = \delta\mathbf{z}_t[1:\dim(\mathbf{h}_{t-1})]
126 $$126 $$
127- 127+ 
128 $$128 $$
129 \delta\mathbf{c}_{\text{prev}} = \delta\mathbf{c}_t \odot \mathbf{f}_t129 \delta\mathbf{c}_{\text{prev}} = \delta\mathbf{c}_t \odot \mathbf{f}_t
130 $$130 $$
1316. **更新传播变量**1316. **更新传播变量**
132- 132+ 
133 $$133 $$
134 \delta\mathbf{h}_{\text{next}} \leftarrow \delta\mathbf{h}_{\text{prev}}134 \delta\mathbf{h}_{\text{next}} \leftarrow \delta\mathbf{h}_{\text{prev}}
135 $$135 $$
136- 136+ 
137 $$137 $$
138 \delta\mathbf{c}_{\text{next}} \leftarrow \delta\mathbf{c}_{\text{prev}}138 \delta\mathbf{c}_{\text{next}} \leftarrow \delta\mathbf{c}_{\text{prev}}
139 $$139 $$
140- 140+ 
141 $$141 $$
142 \mathbf{f}_{\text{next}} \leftarrow \mathbf{f}_t142 \mathbf{f}_{\text{next}} \leftarrow \mathbf{f}_t
143 $$143 $$
Mrnn/single_layer_lstm_grad/docs/aclnnLstmBackward.md+1-1
@@ -3,7 +3,7 @@
3## 产品支持情况3## 产品支持情况
4 4 
5<!-- npu="950" id1 -->5<!-- npu="950" id1 -->
6-- <term>Ascend 950PR/Ascend 950DT</term>：不支持6+- <term>Ascend 950PR/Ascend 950DT</term>：支持
7<!-- end id1 -->7<!-- end id1 -->
8<!-- npu="A3" id2 -->8<!-- npu="A3" id2 -->
9- <term>Atlas A3 训练系列产品/Atlas A3 推理系列产品</term>：支持9- <term>Atlas A3 训练系列产品/Atlas A3 推理系列产品</term>：支持
Arnn/single_layer_lstm_grad/op_host/config/ascend950/single_layer_lstm_grad_binary.json+483-0
@@ -0,0 +1,483 @@
1+{
2+ "op_type": "SingleLayerLstmGrad",
3+ "op_list": [
4+ {
5+ "bin_filename": "SingleLayerLstmGrad_fp32",
6+ "inputs": [
7+ {
8+ "name": "x",
9+ "index": 0,
10+ "dtype": "float32",
11+ "format": "ND",
12+ "paramType": "required",
13+ "shape": [
14+ -2
15+ ]
16+ },
17+ {
18+ "name": "w",
19+ "index": 1,
20+ "dtype": "float32",
21+ "format": "ND",
22+ "paramType": "required",
23+ "shape": [
24+ -2
25+ ]
26+ },
27+ {
28+ "name": "b",
29+ "index": 2,
30+ "dtype": "float32",
31+ "format": "ND",
32+ "paramType": "optional",
33+ "shape": [
34+ -2
35+ ]
36+ },
37+ {
38+ "name": "y",
39+ "index": 3,
40+ "dtype": "float32",
41+ "format": "ND",
42+ "paramType": "optional",
43+ "shape": [
44+ -2
45+ ]
46+ },
47+ {
48+ "name": "init_h",
49+ "index": 4,
50+ "dtype": "float32",
51+ "format": "ND",
52+ "paramType": "required",
53+ "shape": [
54+ -2
55+ ]
56+ },
57+ {
58+ "name": "init_c",
59+ "index": 5,
60+ "dtype": "float32",
61+ "format": "ND",
62+ "paramType": "required",
63+ "shape": [
64+ -2
65+ ]
66+ },
67+ {
68+ "name": "h",
69+ "index": 6,
70+ "dtype": "float32",
71+ "format": "ND",
72+ "paramType": "required",
73+ "shape": [
74+ -2
75+ ]
76+ },
77+ {
78+ "name": "c",
79+ "index": 7,
80+ "dtype": "float32",
81+ "format": "ND",
82+ "paramType": "required",
83+ "shape": [
84+ -2
85+ ]
86+ },
87+ {
88+ "name": "dy",
89+ "index": 8,
90+ "dtype": "float32",
91+ "format": "ND",
92+ "paramType": "required",
93+ "shape": [
94+ -2
95+ ]
96+ },
97+ {
98+ "name": "dh",
99+ "index": 9,
100+ "dtype": "float32",
101+ "format": "ND",
102+ "paramType": "required",
103+ "shape": [
104+ -2
105+ ]
106+ },
107+ {
108+ "name": "dc",
109+ "index": 10,
110+ "dtype": "float32",
111+ "format": "ND",
112+ "paramType": "optional",
113+ "shape": [
114+ -2
115+ ]
116+ },
117+ {
118+ "name": "i",
119+ "index": 11,
120+ "dtype": "float32",
121+ "format": "ND",
122+ "paramType": "required",
123+ "shape": [
124+ -2
125+ ]
126+ },
127+ {
128+ "name": "j",
129+ "index": 12,
130+ "dtype": "float32",
131+ "format": "ND",
132+ "paramType": "required",
133+ "shape": [
134+ -2
135+ ]
136+ },
137+ {
138+ "name": "f",
139+ "index": 13,
140+ "dtype": "float32",
141+ "format": "ND",
142+ "paramType": "required",
143+ "shape": [
144+ -2
145+ ]
146+ },
147+ {
148+ "name": "o",
149+ "index": 14,
150+ "dtype": "float32",
151+ "format": "ND",
152+ "paramType": "required",
153+ "shape": [
154+ -2
155+ ]
156+ },
157+ {
158+ "name": "tanhct",
159+ "index": 15,
160+ "dtype": "float32",
161+ "format": "ND",
162+ "paramType": "required",
163+ "shape": [
164+ -2
165+ ]
166+ },
167+ {
168+ "name": "seq_length",
169+ "index": 16,
170+ "dtype": "float32",
171+ "format": "ND",
172+ "paramType": "optional",
173+ "shape": [
174+ -2
175+ ]
176+ }
177+ ],
178+ "outputs": [
179+ {
180+ "name": "dw",
181+ "index": 0,
182+ "dtype": "float32",
183+ "format": "ND",
184+ "paramType": "required",
185+ "shape": [
186+ -2
187+ ]
188+ },
189+ {
190+ "name": "db",
191+ "index": 1,
192+ "dtype": "float32",
193+ "format": "ND",
194+ "paramType": "required",
195+ "shape": [
196+ -2
197+ ]
198+ },
199+ {
200+ "name": "dx",
201+ "index": 2,
202+ "dtype": "float32",
203+ "format": "ND",
204+ "paramType": "required",
205+ "shape": [
206+ -2
207+ ]
208+ },
209+ {
210+ "name": "dh_prev",
211+ "index": 3,
212+ "dtype": "float32",
213+ "format": "ND",
214+ "paramType": "required",
215+ "shape": [
216+ -2
217+ ]
218+ },
219+ {
220+ "name": "dc_prev",
221+ "index": 4,
222+ "dtype": "float32",
223+ "format": "ND",
224+ "paramType": "required",
225+ "shape": [
226+ -2
227+ ]
228+ }
229+ ],
230+ "attrs": [
231+ {
232+ "name": "direction",
233+ "dtype": "str",
234+ "value": ""
235+ },
236+ {
237+ "name": "gate_order",
238+ "dtype": "str",
239+ "value": ""
240+ }
241+ ]
242+ },
243+ {
244+ "bin_filename": "SingleLayerLstmGrad_fp16",
245+ "inputs": [
246+ {
247+ "name": "x",
248+ "index": 0,
249+ "dtype": "float16",
250+ "format": "ND",
251+ "paramType": "required",
252+ "shape": [
253+ -2
254+ ]
255+ },
256+ {
257+ "name": "w",
258+ "index": 1,
259+ "dtype": "float16",
260+ "format": "ND",
261+ "paramType": "required",
262+ "shape": [
263+ -2
264+ ]
265+ },
266+ {
267+ "name": "b",
268+ "index": 2,
269+ "dtype": "float16",
270+ "format": "ND",
271+ "paramType": "optional",
272+ "shape": [
273+ -2
274+ ]
275+ },
276+ {
277+ "name": "y",
278+ "index": 3,
279+ "dtype": "float16",
280+ "format": "ND",
281+ "paramType": "optional",
282+ "shape": [
283+ -2
284+ ]
285+ },
286+ {
287+ "name": "init_h",
288+ "index": 4,
289+ "dtype": "float16",
290+ "format": "ND",
291+ "paramType": "required",
292+ "shape": [
293+ -2
294+ ]
295+ },
296+ {
297+ "name": "init_c",
298+ "index": 5,
299+ "dtype": "float16",
300+ "format": "ND",
301+ "paramType": "required",
302+ "shape": [
303+ -2
304+ ]
305+ },
306+ {
307+ "name": "h",
308+ "index": 6,
309+ "dtype": "float16",
310+ "format": "ND",
311+ "paramType": "required",
312+ "shape": [
313+ -2
314+ ]
315+ },
316+ {
317+ "name": "c",
318+ "index": 7,
319+ "dtype": "float16",
320+ "format": "ND",
321+ "paramType": "required",
322+ "shape": [
323+ -2
324+ ]
325+ },
326+ {
327+ "name": "dy",
328+ "index": 8,
329+ "dtype": "float16",
330+ "format": "ND",
331+ "paramType": "required",
332+ "shape": [
333+ -2
334+ ]
335+ },
336+ {
337+ "name": "dh",
338+ "index": 9,
339+ "dtype": "float16",
340+ "format": "ND",
341+ "paramType": "required",
342+ "shape": [
343+ -2
344+ ]
345+ },
346+ {
347+ "name": "dc",
348+ "index": 10,
349+ "dtype": "float16",
350+ "format": "ND",
351+ "paramType": "optional",
352+ "shape": [
353+ -2
354+ ]
355+ },
356+ {
357+ "name": "i",
358+ "index": 11,
359+ "dtype": "float16",
360+ "format": "ND",
361+ "paramType": "required",
362+ "shape": [
363+ -2
364+ ]
365+ },
366+ {
367+ "name": "j",
368+ "index": 12,
369+ "dtype": "float16",
370+ "format": "ND",
371+ "paramType": "required",
372+ "shape": [
373+ -2
374+ ]
375+ },
376+ {
377+ "name": "f",
378+ "index": 13,
379+ "dtype": "float16",
380+ "format": "ND",
381+ "paramType": "required",
382+ "shape": [
383+ -2
384+ ]
385+ },
386+ {
387+ "name": "o",
388+ "index": 14,
389+ "dtype": "float16",
390+ "format": "ND",
391+ "paramType": "required",
392+ "shape": [
393+ -2
394+ ]
395+ },
396+ {
397+ "name": "tanhct",
398+ "index": 15,
399+ "dtype": "float16",
400+ "format": "ND",
401+ "paramType": "required",
402+ "shape": [
403+ -2
404+ ]
405+ },
406+ {
407+ "name": "seq_length",
408+ "index": 16,
409+ "dtype": "float16",
410+ "format": "ND",
411+ "paramType": "optional",
412+ "shape": [
413+ -2
414+ ]
415+ }
416+ ],
417+ "outputs": [
418+ {
419+ "name": "dw",
420+ "index": 0,
421+ "dtype": "float16",
422+ "format": "ND",
423+ "paramType": "required",
424+ "shape": [
425+ -2
426+ ]
427+ },
428+ {
429+ "name": "db",
430+ "index": 1,
431+ "dtype": "float16",
432+ "format": "ND",
433+ "paramType": "required",
434+ "shape": [
435+ -2
436+ ]
437+ },
438+ {
439+ "name": "dx",
440+ "index": 2,
441+ "dtype": "float16",
442+ "format": "ND",
443+ "paramType": "required",
444+ "shape": [
445+ -2
446+ ]
447+ },
448+ {
449+ "name": "dh_prev",
450+ "index": 3,
451+ "dtype": "float16",
452+ "format": "ND",
453+ "paramType": "required",
454+ "shape": [
455+ -2
456+ ]
457+ },
458+ {
459+ "name": "dc_prev",
460+ "index": 4,
461+ "dtype": "float16",
462+ "format": "ND",
463+ "paramType": "required",
464+ "shape": [
465+ -2
466+ ]
467+ }
468+ ],
469+ "attrs": [
470+ {
471+ "name": "direction",
472+ "dtype": "str",
473+ "value": ""
474+ },
475+ {
476+ "name": "gate_order",
477+ "dtype": "str",
478+ "value": ""
479+ }
480+ ]
481+ }
482+ ]
483+}
Mrnn/single_layer_lstm_grad/op_host/single_layer_lstm_grad_def.cpp+2-1
@@ -137,8 +137,9 @@ public:
137 aicore_config.DynamicCompileStaticFlag(true).DynamicRankSupportFlag(true).DynamicShapeSupportFlag(true);137 aicore_config.DynamicCompileStaticFlag(true).DynamicRankSupportFlag(true).DynamicShapeSupportFlag(true);
138 this->AICore().AddConfig("ascend910b");138 this->AICore().AddConfig("ascend910b");
139 this->AICore().AddConfig("ascend910_93");139 this->AICore().AddConfig("ascend910_93");
140+ this->AICore().AddConfig("ascend950");
140 }141 }
141};142};
142 143 
143OP_ADD(SingleLayerLstmGrad);144OP_ADD(SingleLayerLstmGrad);
144-} // namespace ops145+} // namespace ops
Mrnn/single_layer_lstm_grad/op_kernel/CMakeLists.txt+3-3
@@ -1,13 +1,13 @@
1# ----------------------------------------------------------------------------1# ----------------------------------------------------------------------------
2# Copyright (c) 2026 Huawei Technologies Co., Ltd.2# Copyright (c) 2026 Huawei Technologies Co., Ltd.
3-# This program is free software, you can redistribute it and/or modify it under the terms and conditions of 3+# This program is free software, you can redistribute it and/or modify it under the terms and conditions of
4# CANN Open Software License Agreement Version 2.0 (the "License").4# CANN Open Software License Agreement Version 2.0 (the "License").
5# Please refer to the License for details. You may not use this file except in compliance with the License.5# Please refer to the License for details. You may not use this file except in compliance with the License.
6-# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, 6+# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
7# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.7# INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
8# See LICENSE in the root of the software repository for the full text of the License.8# See LICENSE in the root of the software repository for the full text of the License.
9# ----------------------------------------------------------------------------9# ----------------------------------------------------------------------------
10 10 
11add_kernel_sources(11add_kernel_sources(
12- COMPUTE_UNITS ascend910b ascend910_9312+ COMPUTE_UNITS ascend910b ascend910_93 ascend950
13)13)
Mscripts/kernel/binary_config/ascendc_config.json+1-1
@@ -663,7 +663,7 @@
663 {"name": "SortedSparseSegmentMeanGrad", "compute_units": ["ascend950"], "auto_sync": false, "impl_mode": "", "compile_options": {"ascend950": ["--cce-no-dcache-flush"]}},663 {"name": "SortedSparseSegmentMeanGrad", "compute_units": ["ascend950"], "auto_sync": false, "impl_mode": "", "compile_options": {"ascend950": ["--cce-no-dcache-flush"]}},
664 {"name":"QuantMax", "compute_units": ["ascend950"], "auto_sync": false},664 {"name":"QuantMax", "compute_units": ["ascend950"], "auto_sync": false},
665 {"name": "GLU", "compute_units": ["ascend950", "ascend910b", "ascend910_93"], "auto_sync": false, "impl_mode": "", "compile_options": {"ascend950": ["-mllvm -cce-aicore-dcci-before-kernel-end=false"]}},665 {"name": "GLU", "compute_units": ["ascend950", "ascend910b", "ascend910_93"], "auto_sync": false, "impl_mode": "", "compile_options": {"ascend950": ["-mllvm -cce-aicore-dcci-before-kernel-end=false"]}},
666- {"name":"SingleLayerLstmGrad", "compute_units": ["ascend910b", "ascend910_93"], "auto_sync" : true},666+ {"name":"SingleLayerLstmGrad", "compute_units": ["ascend910b", "ascend910_93", "ascend950"], "auto_sync" : true},
667 {"name":"HardSwishGrad", "compute_units": ["ascend950"], "auto_sync" : true},667 {"name":"HardSwishGrad", "compute_units": ["ascend950"], "auto_sync" : true},
668 {"name":"PReluGradReduce", "compute_units": ["ascend910_95"], "auto_sync" : true},668 {"name":"PReluGradReduce", "compute_units": ["ascend910_95"], "auto_sync" : true},
669 {"name":"PReluGradUpdate", "compute_units": ["ascend910_95"], "auto_sync" : true},669 {"name":"PReluGradUpdate", "compute_units": ["ascend910_95"], "auto_sync" : true},