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author | Gian Marco <gianmarco.iodice@arm.com> | 2017-11-08 12:24:09 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | e75a02b60736f37c34388c23c0ccee230f65da59 (patch) | |
tree | f8e9423e40589e99bd8be6c1e740b17792e2058e /tests/datasets/LargeGEMMLowpDataset.h | |
parent | 6c0348f4cbf6e30a715780f50aebf6dd0a2a8fc3 (diff) | |
download | ComputeLibrary-e75a02b60736f37c34388c23c0ccee230f65da59.tar.gz |
COMPMID-675 - Reworked NEGEMMLowp interface/function
The new interface makes NEGEMMLowp able to work with ASYMM8 data types.
Implemented 2 new functions:
- NEGEMMLowpMatrixMultiplyCore
- NEGEMMLowpOutputStage
These functions should make the integration in android NN doable
For more information about GEMMLowp:
https://github.com/google/gemmlowp/blob/master/doc/low-precision.md
Change-Id: Ie2c775f45234f68ca53dba644b3a912b997fd890
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/95504
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Diffstat (limited to 'tests/datasets/LargeGEMMLowpDataset.h')
-rw-r--r-- | tests/datasets/LargeGEMMLowpDataset.h | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/tests/datasets/LargeGEMMLowpDataset.h b/tests/datasets/LargeGEMMLowpDataset.h index 10f79e423d..cc1feb49a2 100644 --- a/tests/datasets/LargeGEMMLowpDataset.h +++ b/tests/datasets/LargeGEMMLowpDataset.h @@ -42,12 +42,12 @@ class LargeGEMMLowpDataset final : public GEMMLowpDataset public: LargeGEMMLowpDataset() { - add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0, 0, 1, 0); - add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4, 3, 2, 0); - add_config(TensorShape(697U, 872U), TensorShape(563U, 697U), TensorShape(563U, 872U), -2, 0, 1, 1, 0); - add_config(TensorShape(1021U, 973U), TensorShape(783U, 1021U), TensorShape(783U, 973U), 5, 13, -6, 2, 2); - add_config(TensorShape(681U, 1023U), TensorShape(213U, 681U), TensorShape(213U, 1023U), -3, -2, 8, 4, 3); - add_config(TensorShape(941U, 1011U), TensorShape(623U, 941U), TensorShape(623U, 1011U), -9, 1, -3, 3, 1); + add_config(TensorShape(923U, 429U), TensorShape(871U, 923U), TensorShape(871U, 429U), 0, 0); + add_config(TensorShape(873U, 513U), TensorShape(784U, 873U), TensorShape(784U, 513U), 0, 4); + add_config(TensorShape(697U, 872U), TensorShape(563U, 697U), TensorShape(563U, 872U), -2, 0); + add_config(TensorShape(1021U, 973U), TensorShape(783U, 1021U), TensorShape(783U, 973U), 5, 13); + add_config(TensorShape(681U, 1023U), TensorShape(213U, 681U), TensorShape(213U, 1023U), -3, -2); + add_config(TensorShape(941U, 1011U), TensorShape(623U, 941U), TensorShape(623U, 1011U), -9, 1); } }; } // namespace datasets |