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authorRamy Elgammal <ramelg01@e129512.arm.com>2023-01-11 18:48:04 +0000
committerRamy Elgammal <ramy.elgammal@arm.com>2023-01-25 10:24:23 +0000
commit002e6530f6218b00a28aef9be8b21efb08cf3602 (patch)
treef3e2f9d064b985ffe283512825b34cdd59f29f50 /tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
parentcc2877368d5e15d9ea89d31c84ec651fc0fffd13 (diff)
downloadComputeLibrary-002e6530f6218b00a28aef9be8b21efb08cf3602.tar.gz
Implement dynamic fusion softmax operator
- Return aux tensorInfo by get_aux_tensors() at runtime to init the aux tensor with the right size. - Keep softmax unfusable for this commit - Hence, added Tensor3D to template writer arguments declaration, for sake of keeping dynamic fusion softmax componenets' kernels matching their cl counterparts. Resolves: COMPMID-5523 Change-Id: I667f39545db925f667036ef448302c79a0330373 Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com> Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/483924 Tested-by: bsgcomp <bsgcomp@arm.com> Reviewed-by: Gunes Bayir <gunes.bayir@arm.com> Comments-Addressed: bsgcomp <bsgcomp@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8986 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Jakub Sujak <jakub.sujak@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h')
-rw-r--r--tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h9
1 files changed, 5 insertions, 4 deletions
diff --git a/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
index e2722a1bdc..faed610874 100644
--- a/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
+++ b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h
@@ -131,10 +131,11 @@ protected:
// (Important) Allocate auxiliary tensor memory if there are any
for(auto &data : runtime.get_auxiliary_tensors())
{
- TensorType *tensor = data.first;
- AuxMemoryInfo aux_mem_req = data.second;
- tensor->allocator()->init(*data.first->info(), aux_mem_req.alignment);
- tensor->allocator()->allocate();
+ CLTensor *tensor = std::get<0>(data);
+ TensorInfo info = std::get<1>(data);
+ AuxMemoryInfo aux_mem_req = std::get<2>(data);
+ tensor->allocator()->init(info, aux_mem_req.alignment);
+ tensor->allocator()->allocate(); // Use ACL allocated memory
}
// Construct user tensors