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HectorSVCHectorSVC
authoredAug 11, 2023
[QNN EP] Update QNN to v2.13 (#17079)
### Description Update QNN SDK to v2.13, update some UTs accordingly
·
v1.21.1v1.16.0
1 parent 3e7f70b commit 344c41f

11 files changed

+63
-48
lines changed
 

‎onnxruntime/test/providers/qnn/batch_norm_htp_test.cc

+12
Original file line numberDiff line numberDiff line change
@@ -175,6 +175,12 @@ static void RunBatchNormQDQTest(const TestInputDef<float>& input_def,
175175
// TODO: FIX TRANSLATION!!!
176176
// Check that QNN compiles DQ -> BatchNormalization -> Q as a single unit.
177177
// Use an input of rank 3.
178+
// QNN v2.13
179+
// Inaccuracy detected for output 'output', element 4.
180+
// Output quant params: scale=0.019084848463535309, zero_point=9.
181+
// Expected val: 1.7755576372146606
182+
// QNN QDQ val: 2.9963212013244629 (err 1.2207635641098022)
183+
// CPU QDQ val: 0.82064849138259888 (err 0.95490914583206177)
178184
TEST_F(QnnHTPBackendTests, DISABLED_BatchNorm1D) {
179185
constexpr int64_t num_channels = 2;
180186

@@ -187,6 +193,12 @@ TEST_F(QnnHTPBackendTests, DISABLED_BatchNorm1D) {
187193
// TODO: FIX TRANSLATION!!!
188194
// Check that QNN compiles DQ -> BatchNormalization -> Q as a single unit.
189195
// Use an input of rank 4.
196+
// QNN v2.13
197+
// Inaccuracy detected for output 'output', element 14.
198+
// Output quant params: scale=0.023071292787790298, zero_point=19.
199+
// Expected val: 2.8554618358612061
200+
// QNN QDQ val: 5.3294687271118164 (err 2.4740068912506104)
201+
// CPU QDQ val: 1.6611330509185791 (err 1.194328784942627)
190202
TEST_F(QnnHTPBackendTests, DISABLED_BatchNorm2D) {
191203
constexpr int64_t num_channels = 2;
192204
std::vector<float> input_data = {-8.0f, -6.0f, -4.0f, -2.0f, 0.0f, 1.1f, 3.3f, 8.0f,

‎onnxruntime/test/providers/qnn/conv_test.cc

+4-6
Original file line numberDiff line numberDiff line change
@@ -225,7 +225,7 @@ static void RunHTPConvOpTest(const std::string& conv_op_type, const TestInputDef
225225

226226
// Check that QNN compiles DQ -> Conv -> Q as a single unit.
227227
// Tests bias as a dynamic input.
228-
// TODO: Segfaults when calling graphFinalize().
228+
// TODO: Segfaults when calling graphFinalize(). v2.13
229229
TEST_F(QnnCPUBackendTests, DISABLED_Convf32_dynamic_bias) {
230230
RunCPUConvOpTest("Conv",
231231
TestInputDef<float>({1, 1, 3, 3}, false, 0.0f, 10.0f), // Random dynamic input
@@ -575,8 +575,7 @@ TEST_F(QnnHTPBackendTests, ConvTranspose1DU8U8S32_AutoPadLower) {
575575
13);
576576
}
577577

578-
// TODO: re-enable tests once HTP issues are resolved
579-
TEST_F(QnnHTPBackendTests, DISABLED_ConvU8U8S32_large_input1_padding_bias_initializer) {
578+
TEST_F(QnnHTPBackendTests, ConvU8U8S32_large_input1_padding_bias_initializer) {
580579
RunHTPConvOpTest<uint8_t>("Conv",
581580
TestInputDef<float>({1, 3, 60, 452}, false, 0.f, 10.f), // Dynamic input
582581
TestInputDef<float>({16, 3, 3, 3}, true, -1.f, 1.f), // Static weights
@@ -588,7 +587,7 @@ TEST_F(QnnHTPBackendTests, DISABLED_ConvU8U8S32_large_input1_padding_bias_initia
588587
ExpectedEPNodeAssignment::All);
589588
}
590589

591-
TEST_F(QnnHTPBackendTests, DISABLED_ConvU8S32_large_input2_bias_initializer) {
590+
TEST_F(QnnHTPBackendTests, ConvU8S32_large_input2_bias_initializer) {
592591
RunHTPConvOpTest<uint8_t>("Conv",
593592
TestInputDef<float>({1, 128, 8, 56}, false, 0.f, 10.f), // Dynamic input
594593
TestInputDef<float>({32, 128, 1, 1}, true, -1.f, 1.f), // Random static weights
@@ -600,8 +599,7 @@ TEST_F(QnnHTPBackendTests, DISABLED_ConvU8S32_large_input2_bias_initializer) {
600599
ExpectedEPNodeAssignment::All);
601600
}
602601

603-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
604-
TEST_F(QnnHTPBackendTests, DISABLED_ConvU8U8S32_LargeInput_Dilations_Pads) {
602+
TEST_F(QnnHTPBackendTests, ConvU8U8S32_LargeInput_Dilations_Pads) {
605603
RunHTPConvOpTest<uint8_t>("Conv",
606604
TestInputDef<float>({1, 3, 768, 1152}, false, 0.f, 10.f), // Dynamic input
607605
TestInputDef<float>({64, 3, 7, 7}, true, -1.f, 1.f), // Random static weights

‎onnxruntime/test/providers/qnn/layer_norm_test.cc

+2-2
Original file line numberDiff line numberDiff line change
@@ -122,13 +122,13 @@ static void RunLayerNormQDQTest(const std::vector<int64_t>& input_shape,
122122

123123
// Check that QNN compiles DQ -> LayerNormalization -> Q as a single unit.
124124
// Use an input of rank 3.
125-
// Failed QNN op validation: QnnDsp <E> Param[0] has incorrect Value 3
125+
// QNN HTP only supports axis = -1
126126
// TODO: Use new QDQ accuracy testing approach (see TestQDQModelAccuracy)
127127
TEST_F(QnnHTPBackendTests, TestQDQLayerNorm1DAxis0) {
128128
RunLayerNormQDQTest({1, 2, 3}, {1, 2, 3}, ExpectedEPNodeAssignment::None);
129129
}
130130

131-
// Failed QNN FinalizeGraphs: QnnDsp <E> Failed to finalize graph (id: 1) with err 1002
131+
// QNN v2.13: Failed QNN FinalizeGraphs: QnnDsp <E> Failed to finalize graph (id: 1) with err 1002
132132
//
133133
// TODO: Use new QDQ accuracy testing approach (see TestQDQModelAccuracy)
134134
TEST_F(QnnHTPBackendTests, DISABLED_TestQDQLayerNorm1DAxis2) {

‎onnxruntime/test/providers/qnn/max_pool_test.cpp

+9-6
Original file line numberDiff line numberDiff line change
@@ -128,7 +128,7 @@ TEST_F(QnnCPUBackendTests, MaxPool_Large_Input) {
128128
ExpectedEPNodeAssignment::All);
129129
}
130130

131-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
131+
// QNN v2.13, backendValidateOpConfig() failed for node `MaxPool` of type `PoolMax2d` with error code 4003
132132
TEST_F(QnnCPUBackendTests, DISABLED_MaxPool_Ceil) {
133133
RunMaxPoolOpTest(TestInputDef<float>({1, 2, 3, 3}, false, -10.0f, 10.0f), // Dynamic input with range [-10, 10]
134134
{utils::MakeAttribute("kernel_shape", std::vector<int64_t>{3, 3}),
@@ -141,7 +141,7 @@ TEST_F(QnnCPUBackendTests, DISABLED_MaxPool_Ceil) {
141141
ExpectedEPNodeAssignment::All);
142142
}
143143

144-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
144+
// QNN v2.13, backendValidateOpConfig() failed for node `MaxPool` of type `PoolMax2d` with error code 4003
145145
TEST_F(QnnCPUBackendTests, DISABLED_MaxPool_Large_Input2_Ceil) {
146146
RunMaxPoolOpTest(TestInputDef<float>({1, 128, 16, 113}, false, -10.0f, 10.0f), // Dynamic input with range [-10, 10]
147147
{utils::MakeAttribute("kernel_shape", std::vector<int64_t>{2, 2}),
@@ -171,8 +171,7 @@ TEST_F(QnnHTPBackendTests, MaxPool_Global_HTP_u8) {
171171
ExpectedEPNodeAssignment::All);
172172
}
173173

174-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
175-
TEST_F(QnnHTPBackendTests, DISABLED_MaxPool_Large_Input_HTP_u8) {
174+
TEST_F(QnnHTPBackendTests, MaxPool_Large_Input_HTP_u8) {
176175
RunQDQMaxPoolOpTest<uint8_t>(TestInputDef<float>({1, 125, 8, 56}, false, -10.0f, 10.0f), // Dynamic input with range [-10, 10]
177176
{utils::MakeAttribute("kernel_shape", std::vector<int64_t>{2, 2}),
178177
utils::MakeAttribute("strides", std::vector<int64_t>{2, 2}),
@@ -196,7 +195,11 @@ TEST_F(QnnHTPBackendTests, MaxPool_Ceil_HTP_u8) {
196195
ExpectedEPNodeAssignment::All);
197196
}
198197

199-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
198+
// QNN v2.13: Inaccuracy detected for output 'output', element 58367.
199+
// Output quant params: scale=0.078431375324726105, zero_point=127.
200+
// Expected val: 5.6846914291381836
201+
// QNN QDQ val: -5.3333334922790527 (err 11.018024444580078)
202+
// CPU QDQ val: 5.6470589637756348 (err 0.037632465362548828)
200203
TEST_F(QnnHTPBackendTests, DISABLED_MaxPool_Large_Input2_Ceil_HTP_u8) {
201204
RunQDQMaxPoolOpTest<uint8_t>(TestInputDef<float>({1, 128, 16, 113}, false, -10.0f, 10.0f), // Dynamic input with range [-10, 10]
202205
{utils::MakeAttribute("kernel_shape", std::vector<int64_t>{2, 2}),
@@ -209,7 +212,7 @@ TEST_F(QnnHTPBackendTests, DISABLED_MaxPool_Large_Input2_Ceil_HTP_u8) {
209212
ExpectedEPNodeAssignment::All);
210213
}
211214

212-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
215+
// QNN v2.13: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
213216
TEST_F(QnnHTPBackendTests, DISABLED_MaxPool_LargeInput_1Pads) {
214217
RunQDQMaxPoolOpTest<uint8_t>(TestInputDef<float>({1, 64, 384, 576}, false, -10.0f, 10.0f), // Dynamic input with range [-10, 10]
215218
{utils::MakeAttribute("kernel_shape", std::vector<int64_t>{3, 3}),

‎onnxruntime/test/providers/qnn/resize_test.cc

+18-12
Original file line numberDiff line numberDiff line change
@@ -178,8 +178,6 @@ static void RunQDQResizeOpTest(const TestInputDef<float>& input_def,
178178
// CPU tests:
179179
//
180180

181-
// TODO: Enable QnnCPU tests that use "nearest" mode.
182-
//
183181
// Our non-quantized implementation of Resize uses QNN's ResizeNearestNeighbor operator,
184182
// which is __not__ equivalent to ONNX's Resize operator with a single specific "nearest_mode".
185183
// The following disabled unit tests would pass if we removed the check in QNN EP that expects the
@@ -197,61 +195,68 @@ TEST_F(QnnCPUBackendTests, DISABLED_ResizeUpsampleNearestHalfPixel_rpf) {
197195
ExpectedEPNodeAssignment::All);
198196
}
199197

198+
// QNN v2.13 Failed for Linux
199+
#if defined(_WIN32)
200200
// Upsample that uses "round_prefer_ceil" as the "nearest_mode".
201201
// coordinate_transformation_mode: "half_pixel"
202-
TEST_F(QnnCPUBackendTests, DISABLED_ResizeUpsampleNearestHalfPixel_rpc) {
202+
TEST_F(QnnCPUBackendTests, ResizeUpsampleNearestHalfPixel_rpc) {
203203
RunCPUResizeOpTest(TestInputDef<float>({1, 1, 2, 4}, false, -10.0f, 10.0f),
204204
{1, 1, 7, 5}, "nearest", "half_pixel", "round_prefer_ceil",
205205
ExpectedEPNodeAssignment::All);
206206
}
207207

208208
// Downsample that uses "round_prefer_ceil" as the "nearest_mode".
209209
// coordinate_transformation_mode: "half_pixel"
210-
TEST_F(QnnCPUBackendTests, DISABLED_ResizeDownsampleNearestHalfPixel_rpc) {
210+
TEST_F(QnnCPUBackendTests, ResizeDownsampleNearestHalfPixel_rpc) {
211211
RunCPUResizeOpTest(TestInputDef<float>({1, 1, 2, 4}, false, -10.0f, 10.0f),
212212
{1, 1, 1, 3}, "nearest", "half_pixel", "round_prefer_ceil",
213213
ExpectedEPNodeAssignment::All);
214214
}
215215

216216
// Downsample that uses "round_prefer_floor" as the "nearest_mode".
217217
// coordinate_transformation_mode: "half_pixel"
218-
TEST_F(QnnCPUBackendTests, DISABLED_ResizeDownsampleNearestHalfPixel_rpf) {
218+
TEST_F(QnnCPUBackendTests, ResizeDownsampleNearestHalfPixel_rpf) {
219219
RunCPUResizeOpTest(TestInputDef<float>({1, 1, 2, 4}, false, -10.0f, 10.0f),
220220
{1, 1, 1, 2}, "nearest", "half_pixel", "round_prefer_ceil",
221221
ExpectedEPNodeAssignment::All);
222222
}
223+
#endif
223224

224225
// Upsample that uses "round_prefer_floor" as the "nearest_mode".
225226
// coordinate_transformation_mode: "align_corners"
227+
// QNN v2.13: index #50 don't match, which is 4.67152 from -1.93515
226228
TEST_F(QnnCPUBackendTests, DISABLED_ResizeUpsampleNearestAlignCorners_rpf) {
227229
RunCPUResizeOpTest(TestInputDef<float>({1, 2, 7, 5}, false, -10.0f, 10.0f),
228230
{1, 2, 21, 10}, "nearest", "align_corners", "round_prefer_floor",
229231
ExpectedEPNodeAssignment::All);
230232
}
231233

234+
// QNN v2.13 Failed for Linux
235+
#if defined(_WIN32)
232236
// Upsample that uses "round_prefer_ceil" as the "nearest_mode".
233237
// coordinate_transformation_mode: "align_corners"
234-
TEST_F(QnnCPUBackendTests, DISABLED_ResizeUpsampleNearestAlignCorners_rpc) {
238+
TEST_F(QnnCPUBackendTests, ResizeUpsampleNearestAlignCorners_rpc) {
235239
RunCPUResizeOpTest(TestInputDef<float>({1, 1, 2, 4}, false, -10.0f, 10.0f),
236240
{1, 1, 7, 5}, "nearest", "align_corners", "round_prefer_ceil",
237241
ExpectedEPNodeAssignment::All);
238242
}
239243

240244
// Downsample that uses "round_prefer_ceil" as the "nearest_mode".
241245
// coordinate_transformation_mode: "align_corners"
242-
TEST_F(QnnCPUBackendTests, DISABLED_ResizeDownsampleNearestAlignCorners_rpc) {
246+
TEST_F(QnnCPUBackendTests, ResizeDownsampleNearestAlignCorners_rpc) {
243247
RunCPUResizeOpTest(TestInputDef<float>({1, 1, 2, 4}, false, -10.0f, 10.0f),
244248
{1, 1, 1, 3}, "nearest", "align_corners", "round_prefer_ceil",
245249
ExpectedEPNodeAssignment::All);
246250
}
247251

248252
// Downsample that uses "round_prefer_floor" as the "nearest_mode".
249253
// coordinate_transformation_mode: "align_corners"
250-
TEST_F(QnnCPUBackendTests, DISABLED_ResizeDownsampleNearestAlignCorners_rpf) {
254+
TEST_F(QnnCPUBackendTests, ResizeDownsampleNearestAlignCorners_rpf) {
251255
RunCPUResizeOpTest(TestInputDef<float>({1, 1, 2, 4}, false, -10.0f, 10.0f),
252256
{1, 1, 1, 2}, "nearest", "align_corners", "round_prefer_floor",
253257
ExpectedEPNodeAssignment::All);
254258
}
259+
#endif
255260

256261
//
257262
// Cpu tests that use the "linear" mode.
@@ -309,10 +314,11 @@ TEST_F(QnnHTPBackendTests, ResizeU8_2xNearestAsymmetricFloor) {
309314
// QNN's own Resize operator (instead of ResizeNearestNeighbor), but it doesn't support the "asymmetric" coordinate
310315
// transform mode.
311316
//
312-
// Expected: contains 192 values, where each value and its corresponding value in 16-byte object
313-
// <C0-00 00-00 00-00 00-00 40-05 D6-27 BB-01 00-00> are an almost-equal pair
314-
// Actual : 16 - byte object<C0 - 00 00 - 00 00 - 00 00 - 00 40 - 04 E9 - 1B BB - 01 00 - 00>,
315-
// where the value pair(0.15, 0.501) at index #1 don't match, which is 0.351 from 0.15
317+
// QNN v2.13: Inaccuracy detected for output 'output', element 189.
318+
// Output quant params: scale=0.078431375324726105, zero_point=127.
319+
// Expected val: -2.663428783416748
320+
// QNN QDQ val: 7.4509806632995605 (err 10.114409446716309)
321+
// CPU QDQ val: -2.6666667461395264 (err 0.0032379627227783203)
316322
TEST_F(QnnHTPBackendTests, DISABLED_ResizeU8_2xNearestAsymmetricCeil) {
317323
RunQDQResizeOpTest<uint8_t>(TestInputDef<float>({1, 3, 4, 4}, false, -10.0f, 10.0f),
318324
{1, 3, 8, 8}, "nearest", "asymmetric", "ceil",

‎onnxruntime/test/providers/qnn/simple_op_htp_test.cc

+12-16
Original file line numberDiff line numberDiff line change
@@ -244,17 +244,9 @@ TEST_F(QnnHTPBackendTests, UnaryOp_Cos) {
244244
11, ExpectedEPNodeAssignment::All);
245245
}
246246

247-
// TODO: Inaccuracy when computing cos(-1.88436)
248-
//
249-
// cos(-1.88436f) fp32 cpu ep = -0.308450460
250-
// cos(-1.88436f) qdq cpu ep = -0.298039228
251-
// cos(-1.88436f) qdq QNN ep = -0.321568638
252-
//
253-
// QNN error: 0.013118177652359009, CPU error: 0.010411232709884644
254-
//
255-
// input quant params: scale=0.0246399231, zero_point=127
256-
// output quant params: scale=0.00784313772, zero_point=127
257-
TEST_F(QnnHTPBackendTests, DISABLED_UnaryOp_Cos_Inaccurate) {
247+
// Check that QNN compiles DQ -> Cos -> Q as a single unit.
248+
// Use an input of rank 3.
249+
TEST_F(QnnHTPBackendTests, UnaryOp_Cos_Inaccurate) {
258250
RunQDQUnaryOpTest(TestInputDef<float>({1, 2, 3}, false, {-3.14159f, -1.88436f, -0.542863f, 0.0f, 1.05622f, 3.14159f}),
259251
"Cos", {},
260252
11, ExpectedEPNodeAssignment::All);
@@ -449,15 +441,15 @@ TEST_F(QnnHTPBackendTests, BinaryOp_Sub4D) {
449441

450442
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
451443
// Enable when this is fixed.
452-
TEST_F(QnnHTPBackendTests, DISABLED_BinaryOp_Sub4D_LargeInputs) {
444+
TEST_F(QnnHTPBackendTests, BinaryOp_Sub4D_LargeInputs) {
453445
RunQDQBinaryOpTest<uint8_t>("Sub", TestInputDef<float>({1, 3, 768, 1152}, false, -1.0f, 1.0f),
454446
TestInputDef<float>({1, 3, 768, 1152}, false, -1.0f, 1.0f),
455447
17, ExpectedEPNodeAssignment::All);
456448
}
457449

458450
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
459451
// Enable when this is fixed.
460-
TEST_F(QnnHTPBackendTests, DISABLED_BinaryOp_Sub4D_Broadcast) {
452+
TEST_F(QnnHTPBackendTests, BinaryOp_Sub4D_Broadcast) {
461453
RunQDQBinaryOpTest<uint8_t>("Sub", TestInputDef<float>({1, 3, 768, 1152}, false, -1.0f, 1.0f),
462454
TestInputDef<float>({3, 1, 1}, true, {1.0f, 0.5f, -0.3f}),
463455
17, ExpectedEPNodeAssignment::All);
@@ -470,8 +462,12 @@ TEST_F(QnnHTPBackendTests, BinaryOp_Div4D_SmallInputs) {
470462
17, ExpectedEPNodeAssignment::All);
471463
}
472464

473-
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
474-
// Enable when this is fixed.
465+
// TODO: Enable when this is fixed.
466+
// QNN v2.13: Inaccuracy detected for output 'output', element 2551923.
467+
// Output quant params: scale=4100.92626953125, zero_point=126.
468+
// Expected val: -277957.3125
469+
// QNN QDQ val: 0 (err 277957.3125)
470+
// CPU QDQ val: -516716.71875 (err 238759.40625)
475471
TEST_F(QnnHTPBackendTests, DISABLED_BinaryOp_Div4D_LargeInputs) {
476472
RunQDQBinaryOpTest<uint8_t>("Div", TestInputDef<float>({1, 3, 768, 1152}, false, -1.0f, 1.0f),
477473
TestInputDef<float>({1, 3, 768, 1152}, false, -1.0f, 1.0f),
@@ -481,7 +477,7 @@ TEST_F(QnnHTPBackendTests, DISABLED_BinaryOp_Div4D_LargeInputs) {
481477
// TODO: Certain large input sizes cause the QNN graph to fail to finalize with error 1002 (QNN_COMMON_ERROR_MEM_ALLOC).
482478
// Enable when this is fixed.
483479
// Fails accuracy when input0 has dims [1,3,768,768]
484-
TEST_F(QnnHTPBackendTests, DISABLED_BinaryOp_Div4D_Broadcast) {
480+
TEST_F(QnnHTPBackendTests, BinaryOp_Div4D_Broadcast) {
485481
RunQDQBinaryOpTest<uint8_t>("Div", TestInputDef<float>({1, 3, 768, 1152}, false, -1.0f, 1.0f),
486482
TestInputDef<float>({3, 1, 1}, true, {1.0f, 0.5f, -0.3f}),
487483
17, ExpectedEPNodeAssignment::All);

‎tools/ci_build/github/azure-pipelines/android-arm64-v8a-QNN-crosscompile-ci-pipeline.yml

+1-1
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@ parameters:
33
- name: QnnSdk
44
displayName: QNN SDK version
55
type: string
6-
default: qnn-v2.12.0.230626
6+
default: qnn-v2.13.1.230730
77

88
jobs:
99
- job: Build_QNN_EP

‎tools/ci_build/github/azure-pipelines/linux-qnn-ci-pipeline.yml

+1-1
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@ parameters:
33
- name: QnnSdk
44
displayName: QNN SDK version
55
type: string
6-
default: qnn-v2.12.0.230626
6+
default: qnn-v2.13.1.230730
77

88
jobs:
99
- job: Build_QNN_EP

‎tools/ci_build/github/azure-pipelines/qnn-ep-nuget-packaging-pipeline.yml

+2-2
Original file line numberDiff line numberDiff line change
@@ -2,12 +2,12 @@ parameters:
22
- name: qnn_sdk_path_win
33
displayName: QNN Windows SDK path
44
type: string
5-
default: C:\data\qnnsdk\qnn-v2.12.1.230626_win
5+
default: C:\data\qnnsdk\qnn-v2.13.1.230730_win
66

77
- name: qnn_sdk_info
88
displayName: QNN SDK Version Information
99
type: string
10-
default: qnn-v2.12.1.230626_win
10+
default: qnn-v2.13.1.230730_win
1111

1212
- name: ort_package_version
1313
displayName: OnnxRuntime Nuget package version

‎tools/ci_build/github/azure-pipelines/win-qnn-arm64-ci-pipeline.yml

+1-1
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@ parameters:
33
- name: QnnSdk
44
displayName: QNN SDK version
55
type: string
6-
default: qnn-v2.12.1.230626_win
6+
default: qnn-v2.13.1.230730_win
77

88
jobs:
99
- job: 'build'

‎tools/ci_build/github/azure-pipelines/win-qnn-ci-pipeline.yml

+1-1
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@ parameters:
33
- name: QnnSdk
44
displayName: QNN SDK version
55
type: string
6-
default: qnn-v2.12.1.230626_win
6+
default: qnn-v2.13.1.230730_win
77

88
jobs:
99
- job: 'build'

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