COMPMID-2641 [NEON] Create a test case for dynamic tensor support
Change-Id: I181e9acffd34ff1c807c65a822cfafb7327b8c8a
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1913
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
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+++ b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
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+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_TEST_UNIT_DYNAMIC_TENSOR
+#define ARM_COMPUTE_TEST_UNIT_DYNAMIC_TENSOR
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/Helpers.h"
+#include "tests/validation/reference/NormalizationLayer.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+template <typename AllocatorType,
+ typename LifetimeMgrType,
+ typename PoolMgrType,
+ typename MemoryMgrType>
+struct MemoryManagementService
+{
+public:
+ MemoryManagementService()
+ : allocator(), lifetime_mgr(nullptr), pool_mgr(nullptr), mm(nullptr), mg(), num_pools(0)
+ {
+ lifetime_mgr = std::make_shared<LifetimeMgrType>();
+ pool_mgr = std::make_shared<PoolMgrType>();
+ mm = std::make_shared<MemoryMgrType>(lifetime_mgr, pool_mgr);
+ mg = MemoryGroup(mm);
+ }
+
+ void populate(size_t pools)
+ {
+ mm->populate(allocator, pools);
+ num_pools = pools;
+ }
+
+ void clear()
+ {
+ mm->clear();
+ num_pools = 0;
+ }
+
+ void validate(bool validate_finalized) const
+ {
+ ARM_COMPUTE_EXPECT(mm->pool_manager() != nullptr, framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(mm->lifetime_manager() != nullptr, framework::LogLevel::ERRORS);
+
+ if(validate_finalized)
+ {
+ ARM_COMPUTE_EXPECT(mm->lifetime_manager()->are_all_finalized(), framework::LogLevel::ERRORS);
+ }
+ ARM_COMPUTE_EXPECT(mm->pool_manager()->num_pools() == num_pools, framework::LogLevel::ERRORS);
+ }
+
+ AllocatorType allocator;
+ std::shared_ptr<LifetimeMgrType> lifetime_mgr;
+ std::shared_ptr<PoolMgrType> pool_mgr;
+ std::shared_ptr<MemoryMgrType> mm;
+ MemoryGroup mg;
+ size_t num_pools;
+};
+} // namespace
+
+/** Simple test case to run a single function with different shapes twice.
+ *
+ * Runs a specified function twice, where the second time the size of the input/output is different
+ * Internal memory of the function and input/output are managed by different services
+ */
+template <typename TensorType,
+ typename AccessorType,
+ typename AllocatorType,
+ typename LifetimeMgrType,
+ typename PoolMgrType,
+ typename MemoryManagerType,
+ typename NormalizationFunctionType>
+class DynamicTensorType3SingleFunction : public framework::Fixture
+{
+ using T = float;
+ using MemoryManagementServiceType = MemoryManagementService<AllocatorType, LifetimeMgrType, PoolMgrType, MemoryManagerType>;
+
+public:
+ template <typename...>
+ void setup(TensorShape input_level0, TensorShape input_level1)
+ {
+ input_l0 = input_level0;
+ input_l1 = input_level1;
+ run();
+ }
+
+protected:
+ void run()
+ {
+ MemoryManagementServiceType serv_internal;
+ MemoryManagementServiceType serv_cross;
+ const size_t num_pools = 1;
+ const bool validate_finalized = true;
+
+ // Create Tensor shapes.
+ TensorShape level_0 = TensorShape(input_l0);
+ TensorShape level_1 = TensorShape(input_l1);
+
+ // Level 0
+ // Create tensors
+ TensorType src = create_tensor<Tensor>(level_0, DataType::F32, 1);
+ TensorType dst = create_tensor<Tensor>(level_0, DataType::F32, 1);
+
+ serv_cross.mg.manage(&src);
+ serv_cross.mg.manage(&dst);
+
+ // Create and configure function
+ NormalizationFunctionType norm_layer(serv_internal.mm);
+ norm_layer.configure(&src, &dst, NormalizationLayerInfo(NormType::CROSS_MAP, 3));
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Populate and validate memory manager
+ serv_cross.populate(num_pools);
+ serv_internal.populate(num_pools);
+ serv_cross.validate(validate_finalized);
+ serv_internal.validate(validate_finalized);
+
+ // Extract lifetime manager meta-data information
+ internal_l0 = serv_internal.lifetime_mgr->info();
+ cross_l0 = serv_cross.lifetime_mgr->info();
+
+ // Acquire memory manager, fill tensors and compute functions
+ serv_cross.mg.acquire();
+ arm_compute::test::library->fill_tensor_value(Accessor(src), 12.f);
+ norm_layer.run();
+ serv_cross.mg.release();
+
+ // Clear manager
+ serv_cross.clear();
+ serv_internal.clear();
+ serv_cross.validate(validate_finalized);
+ serv_internal.validate(validate_finalized);
+
+ // Level 1
+ // Update the tensor shapes
+ src.info()->set_tensor_shape(level_1);
+ dst.info()->set_tensor_shape(level_1);
+ src.info()->set_is_resizable(true);
+ dst.info()->set_is_resizable(true);
+
+ serv_cross.mg.manage(&src);
+ serv_cross.mg.manage(&dst);
+
+ // Re-configure the function
+ norm_layer.configure(&src, &dst, NormalizationLayerInfo(NormType::CROSS_MAP, 3));
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ // Populate and validate memory manager
+ serv_cross.populate(num_pools);
+ serv_internal.populate(num_pools);
+ serv_cross.validate(validate_finalized);
+ serv_internal.validate(validate_finalized);
+
+ // Extract lifetime manager meta-data information
+ internal_l1 = serv_internal.lifetime_mgr->info();
+ cross_l1 = serv_cross.lifetime_mgr->info();
+
+ // Compute functions
+ serv_cross.mg.acquire();
+ arm_compute::test::library->fill_tensor_value(AccessorType(src), 12.f);
+ norm_layer.run();
+ serv_cross.mg.release();
+
+ // Clear manager
+ serv_cross.clear();
+ serv_internal.clear();
+ serv_cross.validate(validate_finalized);
+ serv_internal.validate(validate_finalized);
+ }
+
+public:
+ TensorShape input_l0{}, input_l1{};
+ typename LifetimeMgrType::info_type internal_l0{}, internal_l1{};
+ typename LifetimeMgrType::info_type cross_l0{}, cross_l1{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_UNIT_DYNAMIC_TENSOR */