COMPMID-563 - Implement reference and CL/NEON validation for Custom_Convolution (Output U8)

Change-Id: I57a6db857474929322206ee7440e088bc0bbbbe2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111080
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>

1 files changed, 144 insertions, 0 deletions

diff --git a/tests/validation/fixtures/ConvolutionFixture.h b/tests/validation/fixtures/ConvolutionFixture.h
new file mode 100644
index 0000000000..3e881a2e99
--- /dev/null
+++ b/tests/validation/fixtures/ConvolutionFixture.h
@@ -0,0 +1,144 @@
+/*
+ * Copyright (c) 2017 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_CONVOLUTION_FIXTURE
+#define ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE
+
+#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/CPP/Convolution.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, const unsigned int filter_size>
+class ConvolutionValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, BorderMode border_mode)
+    {
+        std::mt19937                           gen(library->seed());
+        std::uniform_int_distribution<uint8_t> distribution(0, 255);
+        const uint8_t                          constant_border_value = distribution(gen);
+
+        // Generate random scale value between 0 and 255.
+        const uint32_t scale = distribution(gen);
+
+        switch(filter_size)
+        {
+            case 3:
+            case 5:
+            case 7:
+            case 9:
+                int16_t conv[filter_size * filter_size];
+                create_conv(conv);
+
+                _target    = compute_target(shape, data_type, conv, scale, border_mode, constant_border_value);
+                _reference = compute_reference(shape, data_type, conv, scale, border_mode, constant_border_value);
+                break;
+            default:
+                ARM_COMPUTE_ERROR("Filter Size Not Supported");
+        }
+    }
+
+protected:
+    void create_conv(int16_t *conv)
+    {
+        std::mt19937                           gen(library->seed());
+        std::uniform_int_distribution<int16_t> distribution_int16(-32768, 32767);
+
+        for(unsigned int i = 0; i < filter_size * filter_size; ++i)
+        {
+            conv[i] = distribution_int16(gen);
+        }
+    }
+
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType convolution;
+        convolution.configure(&src, &dst, conv, scale, border_mode, constant_border_value);
+
+        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);
+
+        // Fill tensors
+        fill(AccessorType(src), 0);
+        fill(AccessorType(dst), 1);
+
+        // Compute function
+        convolution.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
+    {
+        ARM_COMPUTE_ERROR_ON(data_type != DataType::U8);
+
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src, 0);
+
+        // Compute reference
+        return reference::convolution<T>(src, conv, scale, border_mode, constant_border_value, filter_size);
+    }
+
+    BorderMode      _border_mode{};
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE */