COMPMID-2051 Refactor shape_calculator::calculate_concatenate_shape
Change-Id: Ibf316718d11fa975d75f226925747b21c4efd127
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/974
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
diff --git a/tests/validation/fixtures/ConcatenateLayerFixture.h b/tests/validation/fixtures/ConcatenateLayerFixture.h
index 39d4f9f..d1eed63 100644
--- a/tests/validation/fixtures/ConcatenateLayerFixture.h
+++ b/tests/validation/fixtures/ConcatenateLayerFixture.h
@@ -73,7 +73,7 @@
// Generate more shapes based on the input
for(auto &s : shapes)
{
- // Randomly change the first dimension
+ // Randomly change the dimension
if(mutate_dis(gen))
{
// Decrease the dimension by a small percentage. Don't increase
@@ -144,18 +144,20 @@
return dst;
}
- SimpleTensor<T> compute_reference(const std::vector<TensorShape> &shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type, unsigned int axis)
+ SimpleTensor<T> compute_reference(std::vector<TensorShape> &shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type, unsigned int axis)
{
std::vector<SimpleTensor<T>> srcs;
+ std::vector<TensorShape *> src_ptrs;
// Create and fill tensors
for(size_t j = 0; j < shapes.size(); ++j)
{
srcs.emplace_back(shapes[j], data_type, 1, qinfo[j]);
fill(srcs.back(), j);
+ src_ptrs.emplace_back(&shapes[j]);
}
- const TensorShape dst_shape = calculate_concatenate_shape(shapes, axis);
+ const TensorShape dst_shape = misc::shape_calculator::calculate_concatenate_shape(src_ptrs, axis);
SimpleTensor<T> dst{ dst_shape, data_type, 1, qinfo[shapes.size()] };
return reference::concatenate_layer<T>(srcs, dst, axis);
}
diff --git a/tests/validation/fixtures/DepthConcatenateLayerFixture.h b/tests/validation/fixtures/DepthConcatenateLayerFixture.h
deleted file mode 100644
index edeefa2..0000000
--- a/tests/validation/fixtures/DepthConcatenateLayerFixture.h
+++ /dev/null
@@ -1,183 +0,0 @@
-/*
- * Copyright (c) 2017-2019 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.
- */
-#ifndef ARM_COMPUTE_TEST_DEPTHCONCATENATE_LAYER_FIXTURE
-#define ARM_COMPUTE_TEST_DEPTHCONCATENATE_LAYER_FIXTURE
-
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.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/Helpers.h"
-#include "tests/validation/reference/DepthConcatenateLayer.h"
-
-#include <random>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-template <typename TensorType, typename ITensorType, typename AccessorType, typename FunctionType, typename T>
-class DepthConcatenateLayerValidationFixture : public framework::Fixture
-{
-public:
- template <typename...>
- void setup(TensorShape shape, DataType data_type)
- {
- // Create input shapes
- std::mt19937 gen(library->seed());
- std::uniform_int_distribution<> num_dis(2, 4);
- std::uniform_int_distribution<> offset_dis(0, 20);
-
- const int num_tensors = num_dis(gen);
-
- std::vector<TensorShape> shapes(num_tensors, shape);
-
- // vector holding the quantization info:
- // the last element is the output quantization info
- // all other elements are the quantization info for the input tensors
- std::vector<QuantizationInfo> qinfo(num_tensors + 1, QuantizationInfo());
-
- for(auto &qi : qinfo)
- {
- qi = QuantizationInfo(1.f / 255.f, offset_dis(gen));
- }
-
- std::uniform_int_distribution<> depth_dis(1, 3);
- std::bernoulli_distribution mutate_dis(0.5f);
- std::uniform_real_distribution<> change_dis(-0.25f, 0.f);
-
- // Generate more shapes based on the input
- for(auto &s : shapes)
- {
- // Set the depth of the tensor
- s.set(2, depth_dis(gen));
-
- // Randomly change the first dimension
- if(mutate_dis(gen))
- {
- // Decrease the dimension by a small percentage. Don't increase
- // as that could make tensor too large. Also the change must be
- // an even number. Otherwise out depth concatenate fails.
- s.set(0, s[0] + 2 * static_cast<int>(s[0] * change_dis(gen)));
- }
-
- // Repeat the same as above for the second dimension
- if(mutate_dis(gen))
- {
- s.set(1, s[1] + 2 * static_cast<int>(s[1] * change_dis(gen)));
- }
- }
-
- _target = compute_target(shapes, qinfo, data_type);
- _reference = compute_reference(shapes, qinfo, data_type);
- }
-
-protected:
- template <typename U>
- void fill(U &&tensor, int i)
- {
- library->fill_tensor_uniform(tensor, i);
- }
-
- TensorType compute_target(std::vector<TensorShape> shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type)
- {
- std::vector<TensorType> srcs;
- std::vector<ITensorType *> src_ptrs;
-
- // Create tensors
- srcs.reserve(shapes.size());
-
- for(size_t j = 0; j < shapes.size(); ++j)
- {
- srcs.emplace_back(create_tensor<TensorType>(shapes[j], data_type, 1, qinfo[j]));
- src_ptrs.emplace_back(&srcs.back());
- }
-
- TensorShape dst_shape = misc::shape_calculator::calculate_depth_concatenate_shape(src_ptrs);
- TensorType dst = create_tensor<TensorType>(dst_shape, data_type, 1, qinfo[shapes.size()]);
-
- // Create and configure function
- FunctionType depth_concat;
- depth_concat.configure(src_ptrs, &dst);
-
- for(auto &src : srcs)
- {
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- }
-
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Allocate tensors
- for(auto &src : srcs)
- {
- src.allocator()->allocate();
- ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
- }
-
- dst.allocator()->allocate();
- ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Fill tensors
- int i = 0;
- for(auto &src : srcs)
- {
- fill(AccessorType(src), i++);
- }
-
- // Compute function
- depth_concat.run();
-
- return dst;
- }
-
- SimpleTensor<T> compute_reference(std::vector<TensorShape> shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type)
- {
- std::vector<SimpleTensor<T>> srcs;
-
- // Create and fill tensors
- for(size_t j = 0; j < shapes.size(); ++j)
- {
- srcs.emplace_back(shapes[j], data_type, 1, qinfo[j]);
- fill(srcs.back(), j);
- }
-
- const TensorShape dst_shape = calculate_depth_concatenate_shape(shapes);
- SimpleTensor<T> dst{ dst_shape, data_type, 1, qinfo[shapes.size()] };
-
- return reference::depthconcatenate_layer<T>(srcs, dst);
- }
-
- TensorType _target{};
- SimpleTensor<T> _reference{};
-};
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_DEPTHCONCATENATE_LAYER_FIXTURE */