COMPMID-424 Implemented reference implementation and tests for WarpAffine

Change-Id: I4924ab1de17adc3b880a5cc22f2497abbc8e221b
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/85820
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Steven Niu <steven.niu@arm.com>

1 files changed, 78 insertions, 0 deletions

diff --git a/tests/validation/Validation.h b/tests/validation/Validation.h
index 5e5dab0040..f220224991 100644
--- a/tests/validation/Validation.h
+++ b/tests/validation/Validation.h
@@ -188,6 +188,19 @@ void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, U toler
 template <typename T, typename U = AbsoluteTolerance<T>>
 void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const ValidRegion &valid_region, U tolerance_value = U(), float tolerance_number = 0.f);
 
+/** Validate tensors with valid mask.
+ *
+ * - Dimensionality has to be the same.
+ * - All values have to match.
+ *
+ * @note: wrap_range allows cases where reference tensor rounds up to the wrapping point, causing it to wrap around to
+ * zero while the test tensor stays at wrapping point to pass. This may permit true erroneous cases (difference between
+ * reference tensor and test tensor is multiple of wrap_range), but such errors would be detected by
+ * other test cases.
+ */
+template <typename T, typename U = AbsoluteTolerance<T>>
+void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const SimpleTensor<T> &valid_mask, U tolerance_value = U(), float tolerance_number = 0.f);
+
 /** Validate tensors against constant value.
  *
  * - All values have to match.
@@ -435,6 +448,71 @@ void validate_keypoints(T target_first, T target_last, U reference_first, U refe
 }
 
 template <typename T, typename U>
+void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, const SimpleTensor<T> &valid_mask, U tolerance_value, float tolerance_number)
+{
+    int64_t num_mismatches = 0;
+    int64_t num_elements   = 0;
+
+    ARM_COMPUTE_EXPECT_EQUAL(tensor.element_size(), reference.element_size(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT_EQUAL(tensor.data_type(), reference.data_type(), framework::LogLevel::ERRORS);
+
+    if(reference.format() != Format::UNKNOWN)
+    {
+        ARM_COMPUTE_EXPECT_EQUAL(tensor.format(), reference.format(), framework::LogLevel::ERRORS);
+    }
+
+    ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);
+
+    const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
+    const int min_channels = std::min(tensor.num_channels(), reference.num_channels());
+
+    // Iterate over all elements within valid region, e.g. U8, S16, RGB888, ...
+    for(int element_idx = 0; element_idx < min_elements; ++element_idx)
+    {
+        const Coordinates id = index2coord(reference.shape(), element_idx);
+
+        if(valid_mask[element_idx] == 1)
+        {
+            // Iterate over all channels within one element
+            for(int c = 0; c < min_channels; ++c)
+            {
+                const T &target_value    = reinterpret_cast<const T *>(tensor(id))[c];
+                const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];
+
+                if(!compare<U>(target_value, reference_value, tolerance_value))
+                {
+                    ARM_COMPUTE_TEST_INFO("id = " << id);
+                    ARM_COMPUTE_TEST_INFO("channel = " << c);
+                    ARM_COMPUTE_TEST_INFO("target = " << std::setprecision(5) << framework::make_printable(target_value));
+                    ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference_value));
+                    ARM_COMPUTE_TEST_INFO("tolerance = " << std::setprecision(5) << framework::make_printable(static_cast<typename U::value_type>(tolerance_value)));
+                    framework::ARM_COMPUTE_PRINT_INFO();
+
+                    ++num_mismatches;
+                }
+
+                ++num_elements;
+            }
+        }
+        else
+        {
+            ++num_elements;
+        }
+    }
+
+    if(num_elements > 0)
+    {
+        const int64_t absolute_tolerance_number = tolerance_number * num_elements;
+        const float   percent_mismatches        = static_cast<float>(num_mismatches) / num_elements * 100.f;
+
+        ARM_COMPUTE_TEST_INFO(num_mismatches << " values (" << std::fixed << std::setprecision(2) << percent_mismatches
+                              << "%) mismatched (maximum tolerated " << std::setprecision(2) << tolerance_number << "%)");
+        ARM_COMPUTE_EXPECT(num_mismatches <= absolute_tolerance_number, framework::LogLevel::ERRORS);
+    }
+}
+
+template <typename T, typename U>
 bool validate(T target, T reference, U tolerance)
 {
     ARM_COMPUTE_TEST_INFO("reference = " << std::setprecision(5) << framework::make_printable(reference));