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[QNN EP] QNN SDK 2.28.2 #22844
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[QNN EP] QNN SDK 2.28.2 #22844
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…rm implicit bias bug has been fixed.
adrianlizarraga
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Nov 15, 2024
onnxruntime/core/providers/qnn/builder/opbuilder/layer_norm_op_builder.cc
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sophies927
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Nov 18, 2024
adrianlizarraga
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Nov 19, 2024
tools/ci_build/github/azure-pipelines/qnn-ep-nuget-packaging-pipeline.yml
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[QNN EP] [DRAFT] QNN SDK 2.28.2
[QNN EP] QNN SDK 2.28.2
Nov 19, 2024
adrianlizarraga
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Nov 19, 2024
HectorSVC
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Nov 19, 2024
jywu-msft
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Nov 19, 2024
yf711
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Nov 19, 2024
### Description - Updates pipelines to use QNN SDK 2.28.2.241116. - Re-enable LayerNormalization unit tests that failed with accuracy errors with the previous QNN SDK (2.28.0). - Update QNN EP to no longer provide a dummy bias for LayerNorm if the QNN SDK version is >= 2.28.0. ### Motivation and Context Use the latest QNN SDK. This version improves inference latency for certain customer models.
yf711
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Nov 19, 2024
### Description <!-- Describe your changes. --> All three PRs are cherry-picked in this round: 1. [Refactor SkipLayerNorm and handle beta properly (#22862) ](#22862) 2. [[TensorRT EP] Exclude DDS ops from running on TRT (#22875)](#22875) 3. [[QNN EP] QNN SDK 2.28.2 (#22844) ](#22844) ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> --------- Signed-off-by: Liqun Fu <liqfu@microsoft.com> Signed-off-by: Liqun Fu <liqun.fu@microsoft.com> Co-authored-by: Chi Lo <54722500+chilo-ms@users.noreply.github.com> Co-authored-by: liqun Fu <liqfu@microsoft.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com>
mszhanyi
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Nov 22, 2024
### Description - Updates pipelines to use QNN SDK 2.28.2.241116. - Re-enable LayerNormalization unit tests that failed with accuracy errors with the previous QNN SDK (2.28.0). - Update QNN EP to no longer provide a dummy bias for LayerNorm if the QNN SDK version is >= 2.28.0. ### Motivation and Context Use the latest QNN SDK. This version improves inference latency for certain customer models.
guschmue
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Dec 2, 2024
### Description - Updates pipelines to use QNN SDK 2.28.2.241116. - Re-enable LayerNormalization unit tests that failed with accuracy errors with the previous QNN SDK (2.28.0). - Update QNN EP to no longer provide a dummy bias for LayerNorm if the QNN SDK version is >= 2.28.0. ### Motivation and Context Use the latest QNN SDK. This version improves inference latency for certain customer models.
ankitm3k
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Dec 11, 2024
### Description - Updates pipelines to use QNN SDK 2.28.2.241116. - Re-enable LayerNormalization unit tests that failed with accuracy errors with the previous QNN SDK (2.28.0). - Update QNN EP to no longer provide a dummy bias for LayerNorm if the QNN SDK version is >= 2.28.0. ### Motivation and Context Use the latest QNN SDK. This version improves inference latency for certain customer models.
ankitm3k
pushed a commit
to intel/onnxruntime
that referenced
this pull request
Dec 11, 2024
### Description - Updates pipelines to use QNN SDK 2.28.2.241116. - Re-enable LayerNormalization unit tests that failed with accuracy errors with the previous QNN SDK (2.28.0). - Update QNN EP to no longer provide a dummy bias for LayerNorm if the QNN SDK version is >= 2.28.0. ### Motivation and Context Use the latest QNN SDK. This version improves inference latency for certain customer models.
ankitm3k
pushed a commit
to intel/onnxruntime
that referenced
this pull request
Dec 11, 2024
### Description - Updates pipelines to use QNN SDK 2.28.2.241116. - Re-enable LayerNormalization unit tests that failed with accuracy errors with the previous QNN SDK (2.28.0). - Update QNN EP to no longer provide a dummy bias for LayerNorm if the QNN SDK version is >= 2.28.0. ### Motivation and Context Use the latest QNN SDK. This version improves inference latency for certain customer models.
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Description
Motivation and Context
Use the latest QNN SDK. This version improves inference latency for certain customer models.