COMPMID-2670: [CL/GC] Create a test case for dynamic tensor support

Change-Id: I35d28786ee3843ac11c1211aea55328782a99382
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1958
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

10 files changed, 274 insertions, 29 deletions

diff --git a/arm_compute/runtime/BlobLifetimeManager.h b/arm_compute/runtime/BlobLifetimeManager.h
index 586ad10fa0..a7630e437a 100644
--- a/arm_compute/runtime/BlobLifetimeManager.h
+++ b/arm_compute/runtime/BlobLifetimeManager.h
@@ -41,6 +41,9 @@ class IMemoryPool;
 class BlobLifetimeManager : public ISimpleLifetimeManager
 {
 public:
+    using info_type = std::vector<BlobInfo>;
+
+public:
     /** Constructor */
     BlobLifetimeManager();
     /** Prevent instances of this class to be copy constructed */
@@ -51,6 +54,11 @@ public:
     BlobLifetimeManager(BlobLifetimeManager &&) = default;
     /** Allow instances of this class to be moved */
     BlobLifetimeManager &operator=(BlobLifetimeManager &&) = default;
+    /** Accessor to the pool internal configuration meta-data
+     *
+     * @return Lifetime manager internal configuration meta-data
+     */
+    const info_type &info() const;
 
     // Inherited methods overridden:
     std::unique_ptr<IMemoryPool> create_pool(IAllocator *allocator) override;
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCNormalizationLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCNormalizationLayer.h
index 2e68f8edb9..fa10fdd75e 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCNormalizationLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCNormalizationLayer.h
@@ -36,6 +36,7 @@
 
 namespace arm_compute
 {
+// Forward declarations
 class IGCTensor;
 
 /** Basic function to compute a normalization layer. This function calls the following OpenGL ES kernels:
@@ -43,7 +44,6 @@ class IGCTensor;
  * -# @ref GCPixelWiseMultiplicationKernel
  * -# @ref GCFillBorderKernel
  * -# @ref GCNormalizationLayerKernel
- *
  */
 class GCNormalizationLayer : public IFunction
 {
@@ -69,5 +69,5 @@ private:
     GCPixelWiseMultiplicationKernel _multiply_kernel; /**< Pixel multiplication kernel to run */
     GCFillBorderKernel              _border_handler;  /**< Kernel to handle  borders */
 };
-}
+} // namespace arm_compute
 #endif /* __ARM_COMPUTE_GCNORMALIZATIONLAYER_H__ */
diff --git a/arm_compute/runtime/OffsetLifetimeManager.h b/arm_compute/runtime/OffsetLifetimeManager.h
index 748f3b6f81..968e5f224d 100644
--- a/arm_compute/runtime/OffsetLifetimeManager.h
+++ b/arm_compute/runtime/OffsetLifetimeManager.h
@@ -56,7 +56,7 @@ public:
     OffsetLifetimeManager &operator=(OffsetLifetimeManager &&) = default;
     /** Accessor to the pool internal configuration meta-data
      *
-     * @return Pool internal configuration meta-data
+     * @return Lifetime manager internal configuration meta-data
      */
     const info_type &info() const;
 
diff --git a/src/runtime/BlobLifetimeManager.cpp b/src/runtime/BlobLifetimeManager.cpp
index 1323bb3f8c..7a4760a990 100644
--- a/src/runtime/BlobLifetimeManager.cpp
+++ b/src/runtime/BlobLifetimeManager.cpp
@@ -33,13 +33,18 @@
 #include <cmath>
 #include <map>
 
-using namespace arm_compute;
-
+namespace arm_compute
+{
 BlobLifetimeManager::BlobLifetimeManager()
     : _blobs()
 {
 }
 
+const BlobLifetimeManager::info_type &BlobLifetimeManager::info() const
+{
+    return _blobs;
+}
+
 std::unique_ptr<IMemoryPool> BlobLifetimeManager::create_pool(IAllocator *allocator)
 {
     ARM_COMPUTE_ERROR_ON(allocator == nullptr);
@@ -92,3 +97,4 @@ void BlobLifetimeManager::update_blobs_and_mappings()
         ++blob_idx;
     }
 }
+} // namespace arm_compute
diff --git a/src/runtime/CL/CLTensorAllocator.cpp b/src/runtime/CL/CLTensorAllocator.cpp
index 60e1ca8df6..2b5fbb8241 100644
--- a/src/runtime/CL/CLTensorAllocator.cpp
+++ b/src/runtime/CL/CLTensorAllocator.cpp
@@ -128,17 +128,8 @@ void CLTensorAllocator::allocate()
     // Allocate tensor backing memory
     if(_associated_memory_group == nullptr)
     {
-        if(_memory.region() != nullptr && _memory.cl_region()->cl_data().get() != nullptr)
-        {
-            // Memory is already allocated. Reuse it if big enough, otherwise fire an assertion
-            ARM_COMPUTE_ERROR_ON_MSG(info().total_size() > _memory.region()->size(),
-                                     "Reallocation of a bigger memory region is not allowed!");
-        }
-        else
-        {
-            // Perform memory allocation
-            _memory.set_owned_region(allocate_region(CLScheduler::get().context(), info().total_size(), 0));
-        }
+        // Perform memory allocation
+        _memory.set_owned_region(allocate_region(CLScheduler::get().context(), info().total_size(), 0));
     }
     else
     {
diff --git a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
index e76e4f601e..7d1c8182e3 100644
--- a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
+++ b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
@@ -38,7 +38,7 @@ namespace
 {
 constexpr int max_input_tensor_dim = 3;
 } // namespace
-    
+
 CLL2NormalizeLayer::CLL2NormalizeLayer(std::shared_ptr<IMemoryManager> memory_manager)
     : _memory_group(std::move(memory_manager)), _reduce_func(), _normalize_kernel(), _sumsq()
 {
@@ -46,6 +46,9 @@ CLL2NormalizeLayer::CLL2NormalizeLayer(std::shared_ptr<IMemoryManager> memory_ma
 
 void CLL2NormalizeLayer::configure(ICLTensor *input, ICLTensor *output, int axis, float epsilon)
 {
+    // Reset auxiliary tensor
+    _sumsq.allocator()->init(TensorInfo());
+
     // Manage intermediate buffers
     _memory_group.manage(&_sumsq);
 
diff --git a/tests/validation/CL/UNIT/DynamicTensor.cpp b/tests/validation/CL/UNIT/DynamicTensor.cpp
new file mode 100644
index 0000000000..38acbd5c3a
--- /dev/null
+++ b/tests/validation/CL/UNIT/DynamicTensor.cpp
@@ -0,0 +1,105 @@
+/*
+ * 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.
+ */
+#include "arm_compute/runtime/BlobLifetimeManager.h"
+#include "arm_compute/runtime/CL/CLBufferAllocator.h"
+#include "arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h"
+#include "arm_compute/runtime/MemoryGroup.h"
+#include "arm_compute/runtime/MemoryManagerOnDemand.h"
+#include "arm_compute/runtime/PoolManager.h"
+#include "support/ToolchainSupport.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/Globals.h"
+#include "tests/Utils.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/fixtures/UNIT/DynamicTensorFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+using CLL2NormLayerWrapper = SimpleFunctionWrapper<MemoryManagerOnDemand, CLL2NormalizeLayer, ICLTensor>;
+template <>
+void CLL2NormLayerWrapper::configure(ICLTensor *src, ICLTensor *dst)
+{
+    _func.configure(src, dst, 0, 0.0001f);
+}
+} // namespace
+TEST_SUITE(CL)
+TEST_SUITE(UNIT)
+TEST_SUITE(DynamicTensor)
+
+using CLDynamicTensorType3SingleFunction = DynamicTensorType3SingleFunction<CLTensor, CLAccessor, CLBufferAllocator, BlobLifetimeManager, PoolManager, MemoryManagerOnDemand, CLL2NormLayerWrapper>;
+
+/** Tests the memory manager with dynamic input and output tensors.
+ *
+ *  Create and manage the tensors needed to run a simple function. After the function is executed,
+ *  change the input and output size requesting more memory and go through the manage/allocate process.
+ *  The memory manager should be able to update the inner structures and allocate the requested memory
+ * */
+FIXTURE_DATA_TEST_CASE(DynamicTensorType3Single, CLDynamicTensorType3SingleFunction, framework::DatasetMode::ALL,
+                       framework::dataset::zip(framework::dataset::make("Level0Shape", { TensorShape(12U, 11U, 3U), TensorShape(256U, 8U, 12U) }),
+                                               framework::dataset::make("Level1Shape", { TensorShape(67U, 31U, 15U), TensorShape(11U, 2U, 3U) })))
+{
+    ARM_COMPUTE_EXPECT(internal_l0.size() == internal_l1.size(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(cross_l0.size() == cross_l1.size(), framework::LogLevel::ERRORS);
+
+    const unsigned int internal_size = internal_l0.size();
+    const unsigned int cross_size    = cross_l0.size();
+    if(input_l0.total_size() < input_l1.total_size())
+    {
+        for(unsigned int i = 0; i < internal_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(internal_l0[i].size < internal_l1[i].size, framework::LogLevel::ERRORS);
+        }
+        for(unsigned int i = 0; i < cross_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(cross_l0[i].size < cross_l1[i].size, framework::LogLevel::ERRORS);
+        }
+    }
+    else
+    {
+        for(unsigned int i = 0; i < internal_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(internal_l0[i].size == internal_l1[i].size, framework::LogLevel::ERRORS);
+        }
+        for(unsigned int i = 0; i < cross_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(cross_l0[i].size == cross_l1[i].size, framework::LogLevel::ERRORS);
+        }
+    }
+}
+
+TEST_SUITE_END() // DynamicTensor
+TEST_SUITE_END() // UNIT
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/GLES_COMPUTE/UNIT/DynamicTensor.cpp b/tests/validation/GLES_COMPUTE/UNIT/DynamicTensor.cpp
new file mode 100644
index 0000000000..2b972843b8
--- /dev/null
+++ b/tests/validation/GLES_COMPUTE/UNIT/DynamicTensor.cpp
@@ -0,0 +1,105 @@
+/*
+ * 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.
+ */
+#include "arm_compute/runtime/BlobLifetimeManager.h"
+#include "arm_compute/runtime/GLES_COMPUTE/GCBufferAllocator.h"
+#include "arm_compute/runtime/GLES_COMPUTE/functions/GCNormalizationLayer.h"
+#include "arm_compute/runtime/MemoryGroup.h"
+#include "arm_compute/runtime/MemoryManagerOnDemand.h"
+#include "arm_compute/runtime/PoolManager.h"
+#include "support/ToolchainSupport.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/GLES_COMPUTE/GCAccessor.h"
+#include "tests/Globals.h"
+#include "tests/Utils.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/fixtures/UNIT/DynamicTensorFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+using GCNormLayerWrapper = SimpleFunctionWrapper<MemoryManagerOnDemand, GCNormalizationLayer, IGCTensor>;
+template <>
+void GCNormLayerWrapper::configure(IGCTensor *src, IGCTensor *dst)
+{
+    _func.configure(src, dst, NormalizationLayerInfo(NormType::CROSS_MAP, 3));
+}
+} // namespace
+TEST_SUITE(GC)
+TEST_SUITE(UNIT)
+TEST_SUITE(DynamicTensor)
+
+using GCDynamicTensorType3SingleFunction = DynamicTensorType3SingleFunction<GCTensor, GCAccessor, GCBufferAllocator, BlobLifetimeManager, PoolManager, MemoryManagerOnDemand, GCNormLayerWrapper>;
+
+/** Tests the memory manager with dynamic input and output tensors.
+ *
+ *  Create and manage the tensors needed to run a simple function. After the function is executed,
+ *  change the input and output size requesting more memory and go through the manage/allocate process.
+ *  The memory manager should be able to update the inner structures and allocate the requested memory
+ * */
+FIXTURE_DATA_TEST_CASE(DynamicTensorType3Single, GCDynamicTensorType3SingleFunction, framework::DatasetMode::ALL,
+                       framework::dataset::zip(framework::dataset::make("Level0Shape", { TensorShape(12U, 11U, 3U), TensorShape(256U, 8U, 12U) }),
+                                               framework::dataset::make("Level1Shape", { TensorShape(67U, 31U, 15U), TensorShape(11U, 2U, 3U) })))
+{
+    ARM_COMPUTE_EXPECT(internal_l0.size() == internal_l1.size(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(cross_l0.size() == cross_l1.size(), framework::LogLevel::ERRORS);
+
+    const unsigned int internal_size = internal_l0.size();
+    const unsigned int cross_size    = cross_l0.size();
+    if(input_l0.total_size() < input_l1.total_size())
+    {
+        for(unsigned int i = 0; i < internal_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(internal_l0[i].size < internal_l1[i].size, framework::LogLevel::ERRORS);
+        }
+        for(unsigned int i = 0; i < cross_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(cross_l0[i].size < cross_l1[i].size, framework::LogLevel::ERRORS);
+        }
+    }
+    else
+    {
+        for(unsigned int i = 0; i < internal_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(internal_l0[i].size == internal_l1[i].size, framework::LogLevel::ERRORS);
+        }
+        for(unsigned int i = 0; i < cross_size; ++i)
+        {
+            ARM_COMPUTE_EXPECT(cross_l0[i].size == cross_l1[i].size, framework::LogLevel::ERRORS);
+        }
+    }
+}
+
+TEST_SUITE_END() // DynamicTensor
+TEST_SUITE_END() // UNIT
+TEST_SUITE_END() // GC
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/NEON/UNIT/DynamicTensor.cpp b/tests/validation/NEON/UNIT/DynamicTensor.cpp
index 731c6d1650..319aa6a8ee 100644
--- a/tests/validation/NEON/UNIT/DynamicTensor.cpp
+++ b/tests/validation/NEON/UNIT/DynamicTensor.cpp
@@ -36,7 +36,6 @@
 #include "tests/framework/Macros.h"
 #include "tests/framework/datasets/Datasets.h"
 #include "tests/validation/fixtures/UNIT/DynamicTensorFixture.h"
-#include <arm_compute/runtime/OffsetMemoryPool.h>
 
 namespace arm_compute
 {
@@ -44,11 +43,19 @@ namespace test
 {
 namespace validation
 {
+namespace
+{
+using NENormLayerWrapper = SimpleFunctionWrapper<MemoryManagerOnDemand, NENormalizationLayer, ITensor>;
+template <>
+void NENormLayerWrapper::configure(arm_compute::ITensor *src, arm_compute::ITensor *dst)
+{
+    _func.configure(src, dst, NormalizationLayerInfo(NormType::CROSS_MAP, 3));
+}
+} // namespace
 TEST_SUITE(NEON)
 TEST_SUITE(UNIT)
 TEST_SUITE(DynamicTensor)
-
-using NEDynamicTensorType3SingleFunction = DynamicTensorType3SingleFunction<Tensor, Accessor, Allocator, OffsetLifetimeManager, PoolManager, MemoryManagerOnDemand, NENormalizationLayer>;
+using NEDynamicTensorType3SingleFunction = DynamicTensorType3SingleFunction<Tensor, Accessor, Allocator, OffsetLifetimeManager, PoolManager, MemoryManagerOnDemand, NENormLayerWrapper>;
 
 /** Tests the memory manager with dynamic input and output tensors.
  *
diff --git a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
index df12a4aa30..66ef6c4aff 100644
--- a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
+++ b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
@@ -89,6 +89,26 @@ public:
     MemoryGroup                      mg;
     size_t                           num_pools;
 };
+
+template <typename MemoryMgrType, typename FuncType, typename ITensorType>
+class SimpleFunctionWrapper
+{
+public:
+    SimpleFunctionWrapper(std::shared_ptr<MemoryMgrType> mm)
+        : _func(mm)
+    {
+    }
+    void configure(ITensorType *src, ITensorType *dst)
+    {
+    }
+    void run()
+    {
+        _func.run();
+    }
+
+private:
+    FuncType _func;
+};
 } // namespace
 
 /** Simple test case to run a single function with different shapes twice.
@@ -102,7 +122,7 @@ template <typename TensorType,
           typename LifetimeMgrType,
           typename PoolMgrType,
           typename MemoryManagerType,
-          typename NormalizationFunctionType>
+          typename SimpleFunctionWrapperType>
 class DynamicTensorType3SingleFunction : public framework::Fixture
 {
     using T                           = float;
@@ -131,15 +151,15 @@ protected:
 
         // Level 0
         // Create tensors
-        TensorType src = create_tensor<Tensor>(level_0, DataType::F32, 1);
-        TensorType dst = create_tensor<Tensor>(level_0, DataType::F32, 1);
+        TensorType src = create_tensor<TensorType>(level_0, DataType::F32, 1);
+        TensorType dst = create_tensor<TensorType>(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));
+        SimpleFunctionWrapperType layer(serv_internal.mm);
+        layer.configure(&src, &dst);
 
         ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -163,8 +183,8 @@ protected:
 
         // 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();
+        arm_compute::test::library->fill_tensor_value(AccessorType(src), 12.f);
+        layer.run();
         serv_cross.mg.release();
 
         // Clear manager
@@ -184,7 +204,7 @@ protected:
         serv_cross.mg.manage(&dst);
 
         // Re-configure the function
-        norm_layer.configure(&src, &dst, NormalizationLayerInfo(NormType::CROSS_MAP, 3));
+        layer.configure(&src, &dst);
 
         // Allocate tensors
         src.allocator()->allocate();
@@ -203,7 +223,7 @@ protected:
         // Compute functions
         serv_cross.mg.acquire();
         arm_compute::test::library->fill_tensor_value(AccessorType(src), 12.f);
-        norm_layer.run();
+        layer.run();
         serv_cross.mg.release();
 
         // Clear manager