Create Fixture for DirectConv3D

Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Change-Id: If0162fe55a89733ffc927a8f2edf68491dfd8daf
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6391
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 171 insertions, 0 deletions

diff --git a/tests/validation/fixtures/DirectConvolution3DFixture.h b/tests/validation/fixtures/DirectConvolution3DFixture.h
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+++ b/tests/validation/fixtures/DirectConvolution3DFixture.h
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+/*
+ * Copyright (c) 2021 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/core/utils/misc/ShapeCalculator.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/reference/ActivationLayer.h"
+#include "tests/validation/reference/Conv3D.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+using namespace arm_compute::misc::shape_calculator;
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DirectConvolution3DValidationGenericFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int stride_z, int pad_x, int pad_y, int pad_z, unsigned int kernel_width, int kernel_height, int kernel_depth,
+               unsigned int num_kernels, bool has_bias, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout)
+    {
+        ARM_COMPUTE_ERROR_ON(data_layout != DataLayout::NDHWC);
+
+        TensorShape       weights_shape(num_kernels, input_shape[0], kernel_width, kernel_height, kernel_depth);
+        const TensorShape bias_shape(num_kernels);
+        const Conv3dInfo  conv3d_info(Size3D(stride_x, stride_y, stride_z), Padding3D(pad_x, pad_y, pad_z), act_info, Size3D(), DimensionRoundingType::FLOOR, false);
+        const TensorShape output_shape = compute_conv3d_shape(input_shape, weights_shape, conv3d_info);
+
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, conv3d_info, has_bias, data_type, data_layout);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, conv3d_info, has_bias, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        switch(tensor.data_type())
+        {
+            case DataType::F16:
+            {
+                arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f };
+                library->fill(tensor, distribution, i);
+                break;
+            }
+            case DataType::F32:
+            {
+                std::uniform_real_distribution<float> distribution(-1.0f, 1.0f);
+                library->fill(tensor, distribution, i);
+                break;
+            }
+            default:
+                library->fill_tensor_uniform(tensor, i);
+        }
+    }
+
+    TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const Conv3dInfo &conv3d_info,
+                              bool has_bias, const DataType &data_type, const DataLayout &data_layout)
+    {
+        // Create tensors
+        TensorType src     = create_tensor<TensorType>(input_shape, data_type, 1, QuantizationInfo(), data_layout);
+        TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, QuantizationInfo(), data_layout);
+        TensorType bias    = has_bias ? create_tensor<TensorType>(bias_shape, data_type, 1, QuantizationInfo()) : TensorType();
+        TensorType dst     = create_tensor<TensorType>(output_shape, data_type, 1, QuantizationInfo(), data_layout);
+
+        add_padding_x({ &src, &dst, &weights }, data_layout);
+
+        if(has_bias)
+        {
+            add_padding_x({ &bias }, data_layout);
+        }
+
+        // Create and configure function
+        FunctionType conv{};
+        conv.configure(&src, &weights, has_bias ? &bias : nullptr, &dst, conv3d_info);
+
+        ARM_COMPUTE_ASSERT(src.info()->is_resizable());
+        ARM_COMPUTE_ASSERT(weights.info()->is_resizable());
+        ARM_COMPUTE_ASSERT(dst.info()->is_resizable());
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        weights.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_ASSERT(!src.info()->is_resizable());
+        ARM_COMPUTE_ASSERT(!weights.info()->is_resizable());
+        ARM_COMPUTE_ASSERT(!dst.info()->is_resizable());
+
+        // Fill tensors
+        fill(AccessorType(src), 0);
+        fill(AccessorType(weights), 1);
+
+        if(has_bias)
+        {
+            ARM_COMPUTE_ASSERT(bias.info()->is_resizable());
+            bias.allocator()->allocate();
+            ARM_COMPUTE_ASSERT(!bias.info()->is_resizable());
+            fill(AccessorType(bias), 2);
+        }
+
+        // Compute Direct Convolution 3D function
+        conv.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const Conv3dInfo &conv3d_info,
+                                      bool has_bias, const DataType &data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src{ input_shape, data_type };
+        SimpleTensor<T> weights{ weights_shape, data_type };
+        SimpleTensor<T> bias{ bias_shape, data_type };
+        SimpleTensor<T> dst{ output_shape, data_type };
+
+        // Fill reference
+        fill(src, 0);
+        fill(weights, 1);
+
+        if(has_bias)
+        {
+            fill(bias, 2);
+        }
+
+        return reference::activation_layer(reference::conv3d<T>(src, weights, bias, dst, conv3d_info), conv3d_info.act_info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DirectConvolution3DValidationFixture : public DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int stride_z, int pad_x, int pad_y, int pad_z, unsigned int kernel_width, int kernel_height, int kernel_depth,
+               unsigned int num_kernels, bool has_bias, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout)
+    {
+        DirectConvolution3DValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, stride_z, pad_x, pad_y, pad_z, kernel_width, kernel_height,
+                                                                                                      kernel_depth, num_kernels, has_bias, act_info, data_type, data_layout);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute