Add Dynamic Fusion GpuConv2d FP32/FP16 testcase
Resolves: COMPMID-5511
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I0ac0acbf1de7da09f18f7b457307ec3cc99deb3b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8546
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp
index 324b076..f026bfe 100644
--- a/tests/validation/CL/DirectConvolutionLayer.cpp
+++ b/tests/validation/CL/DirectConvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2021 Arm Limited.
+ * Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -132,6 +132,56 @@
validate(CLAccessor(dst), ref_dst);
}
+/** Check whether the case of rectangle kernels i.e. when width and height of the weight_shape are not equal
+ * would lead to successful run
+ */
+TEST_CASE(NonSquareKernel, framework::DatasetMode::PRECOMMIT)
+{
+ auto src_shape = TensorShape(33U, 27U, 3U);
+ auto weights_shape = TensorShape(5U, 7U, 3U, 4U); // non-square kernel
+ const auto bias_shape = TensorShape(4U);
+ auto dst_shape = TensorShape(11U, 12U, 4U);
+ constexpr auto dt = DataType::F32;
+
+ TensorShape src_shape_nhwc(src_shape);
+ TensorShape weights_shape_nhwc(weights_shape);
+ TensorShape dst_shape_nhwc(dst_shape);
+
+ // Non-square shapes are only allowed for NHWC
+ permute(src_shape_nhwc, PermutationVector(2U, 0U, 1U));
+ permute(weights_shape_nhwc, PermutationVector(2U, 0U, 1U));
+ permute(dst_shape_nhwc, PermutationVector(2U, 0U, 1U));
+
+ auto src = create_tensor<CLTensor>(src_shape_nhwc, dt, 1, QuantizationInfo(), DataLayout::NHWC);
+ auto weights = create_tensor<CLTensor>(weights_shape_nhwc, dt, 1, QuantizationInfo(), DataLayout::NHWC);
+ auto dst = create_tensor<CLTensor>(dst_shape_nhwc, dt, 1, QuantizationInfo(), DataLayout::NHWC);
+ const auto conv_info = PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR);
+
+ // Create direct convolution function
+ CLDirectConvolutionLayer conv{};
+ conv.configure(&src, &weights, nullptr, &dst, conv_info);
+
+ src.allocator()->allocate();
+ weights.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ library->fill_tensor_value(CLAccessor(src), 1.f);
+ library->fill_tensor_value(CLAccessor(weights), 1.f);
+
+ conv.run();
+
+ // Compute reference to compare
+ SimpleTensor<float> ref_src{ src_shape, dt };
+ SimpleTensor<float> ref_weights{ weights_shape, dt };
+ SimpleTensor<float> ref_bias{ bias_shape, dt };
+ library->fill_tensor_value(ref_src, 1.f);
+ library->fill_tensor_value(ref_weights, 1.f);
+ // No bias
+ library->fill_tensor_value(ref_bias, 0.f);
+ auto ref_dst = reference::convolution_layer<float>(ref_src, ref_weights, ref_bias, dst_shape, conv_info);
+
+ validate(CLAccessor(dst), ref_dst);
+}
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(