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| author | Viet-Hoa Do <viet-hoa.do@arm.com> | 2023-01-03 17:59:14 +0000 |
|---|---|---|
| committer | Viet-Hoa Do <viet-hoa.do@arm.com> | 2023-01-06 13:45:20 +0000 |
| commit | b3077fbaee868579f9a41888fef1f71286d6757c (patch) | |
| tree | 23e6a6c63dc860697ae8e9301da7ddbb29d62c98 /tests/datasets/ShapeDatasets.h | |
| parent | 3558c5840e7c973e2b1a86ae3a9335b44cad59d4 (diff) | |
| download | ComputeLibrary-b3077fbaee868579f9a41888fef1f71286d6757c.tar.gz | |
LHS broadcasting addition for dynamic fusion
* Binary elementwise operator now can have broadcasting in either
X dimension, Y+Z dimension, or both, in either LHS or RHS
operand.
* Fix bug in CL code to support batching.
Resolves: COMPMID-5704
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I51b04986d30861f255ca9f754adffa0e6c85a26b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8898
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Ramy Elgammal <ramy.elgammal@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Dynamic-Fusion: Ramy Elgammal <ramy.elgammal@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/datasets/ShapeDatasets.h')
| -rw-r--r-- | tests/datasets/ShapeDatasets.h | 18 |
1 files changed, 13 insertions, 5 deletions
diff --git a/tests/datasets/ShapeDatasets.h b/tests/datasets/ShapeDatasets.h index 047457c99e..c1e61444a8 100644 --- a/tests/datasets/ShapeDatasets.h +++ b/tests/datasets/ShapeDatasets.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2022 Arm Limited. + * Copyright (c) 2017-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -308,13 +308,21 @@ public: : ZipDataset<ShapeDataset, ShapeDataset>( ShapeDataset("Shape0", { - TensorShape{ 9U, 9U, 5U }, - TensorShape{ 27U, 13U, 2U }, + TensorShape{ 1U, 3U, 4U, 2U }, // LHS broadcast X + TensorShape{ 6U, 4U, 2U, 3U }, // RHS broadcast X + TensorShape{ 7U, 1U, 1U, 4U }, // LHS broadcast Y, Z + TensorShape{ 8U, 5U, 6U, 3U }, // RHS broadcast Y, Z + TensorShape{ 1U, 1U, 1U, 2U }, // LHS broadcast X, Y, Z + TensorShape{ 2U, 6U, 4U, 3U }, // RHS broadcast X, Y, Z }), ShapeDataset("Shape1", { - TensorShape{ 1U, 1U, 1U }, // Broadcast in X, Y, Z - TensorShape{ 27U, 1U, 1U }, // Broadcast in Y and Z + TensorShape{ 5U, 3U, 4U, 2U }, + TensorShape{ 1U, 4U, 2U, 3U }, + TensorShape{ 7U, 2U, 3U, 4U }, + TensorShape{ 8U, 1U, 1U, 3U }, + TensorShape{ 4U, 7U, 3U, 2U }, + TensorShape{ 1U, 1U, 1U, 3U }, })) { } |