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author | Sang-Hoon Park <sang-hoon.park@arm.com> | 2021-02-03 10:32:59 +0000 |
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committer | Sang-Hoon Park <sang-hoon.park@arm.com> | 2021-03-08 17:00:45 +0000 |
commit | 668ccdcfb81bfab3a2d44cd1ddd956e83a2dfb09 (patch) | |
tree | d139e1a770bcfc182f1aef38a1b908d634f9bb1c /tests/validation/fixtures/ElementWiseUnaryFixture.h | |
parent | 201e0fee596dafcf9c869a550fae29779aad2394 (diff) | |
download | ComputeLibrary-668ccdcfb81bfab3a2d44cd1ddd956e83a2dfb09.tar.gz |
Add dynamic tensor support to CpuElementwise
The kernels and operators for binary and unary operations
are now capable of being configured with dynamic shapes and
computing windows at run-time.
Additionally, changing arguments' names is done
for consistency.
Partially Implements: COMPMID-4127
Change-Id: I48e5038692db667dec7cb2b2906fe5683214fe19
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4973
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/validation/fixtures/ElementWiseUnaryFixture.h')
-rw-r--r-- | tests/validation/fixtures/ElementWiseUnaryFixture.h | 35 |
1 files changed, 31 insertions, 4 deletions
diff --git a/tests/validation/fixtures/ElementWiseUnaryFixture.h b/tests/validation/fixtures/ElementWiseUnaryFixture.h index 8cffef48f6..9729907630 100644 --- a/tests/validation/fixtures/ElementWiseUnaryFixture.h +++ b/tests/validation/fixtures/ElementWiseUnaryFixture.h @@ -44,11 +44,12 @@ class ElementWiseUnaryValidationFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape input_shape, DataType input_data_type, bool in_place, ElementWiseUnary op) + void setup(TensorShape input_shape, DataType input_data_type, bool in_place, ElementWiseUnary op, bool use_dynamic_shape = false) { - _op = op; - _target = compute_target(input_shape, input_data_type, in_place); - _reference = compute_reference(input_shape, input_data_type); + _op = op; + _target = compute_target(input_shape, input_data_type, in_place); + _reference = compute_reference(input_shape, input_data_type); + _use_dynamic_shape = use_dynamic_shape; } protected: @@ -131,10 +132,24 @@ protected: TensorType *actual_dst = in_place ? &src : &dst; + // if _use_dynamic_shape is true, this fixture will test scenario for dynamic shapes. + // - At configure time, all input tensors are marked as dynamic using set_tensor_dynamic() + // - After configure, tensors are marked as static for run using set_tensor_static() + // - The tensors with static shape are given to run() + if(_use_dynamic_shape) + { + set_tensor_dynamic(src); + } + // Create and configure function FunctionType elwiseunary_layer; elwiseunary_layer.configure(&src, actual_dst); + if(_use_dynamic_shape) + { + set_tensor_static(src); + } + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); src.allocator()->allocate(); ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -175,6 +190,7 @@ protected: TensorType _target{}; SimpleTensor<T> _reference{}; ElementWiseUnary _op{}; + bool _use_dynamic_shape{ false }; }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> @@ -189,6 +205,17 @@ public: }; template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class RsqrtDynamicShapeValidationFixture : public ElementWiseUnaryValidationFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type) + { + ElementWiseUnaryValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, false, ElementWiseUnary::RSQRT, true); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> class ExpValidationFixture : public ElementWiseUnaryValidationFixture<TensorType, AccessorType, FunctionType, T> { public: |