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Diffstat (limited to 'tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h')
-rw-r--r--tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h82
1 files changed, 53 insertions, 29 deletions
diff --git a/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h b/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h
index 34f2647741..dd3519b549 100644
--- a/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h
+++ b/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2023 Arm Limited.
+ * Copyright (c) 2023-2024 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -28,14 +28,13 @@
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-
#include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h"
#include "arm_compute/dynamic_fusion/sketch/attributes/Pool2dAttributes.h"
#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h"
-#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h"
#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h"
-#include "src/dynamic_fusion/utils/Utils.h"
+#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h"
+#include "src/dynamic_fusion/utils/Utils.h"
#include "tests/CL/CLAccessor.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/reference/PoolingLayer.h"
@@ -54,19 +53,20 @@ class DynamicFusionGpuPool2dValidationGenericFixture : public framework::Fixture
public:
void setup(TensorShape input_shape, const Pool2dAttributes &pool_attr, DataType data_type, bool mixed_precision)
{
- _target = compute_target(input_shape, pool_attr, data_type, mixed_precision);
- _reference = compute_reference(input_shape, convert_pool_attr_to_pool_info(pool_attr, mixed_precision), data_type);
+ _target = compute_target(input_shape, pool_attr, data_type, mixed_precision);
+ _reference =
+ compute_reference(input_shape, convert_pool_attr_to_pool_info(pool_attr, mixed_precision), data_type);
}
protected:
template <typename U>
void fill(U &&tensor, int i)
{
- switch(tensor.data_type())
+ switch (tensor.data_type())
{
case DataType::F16:
{
- arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f };
+ arm_compute::utils::uniform_real_distribution_16bit<half> distribution{-1.0f, 1.0f};
library->fill(tensor, distribution, i);
break;
}
@@ -82,7 +82,10 @@ protected:
}
// Given input is in nchw format
- TensorType compute_target(TensorShape input_shape, const Pool2dAttributes &pool_attr, const DataType data_type, bool mixed_precision)
+ TensorType compute_target(TensorShape input_shape,
+ const Pool2dAttributes &pool_attr,
+ const DataType data_type,
+ bool mixed_precision)
{
CLScheduler::get().default_reinit();
@@ -91,8 +94,8 @@ protected:
// Create a new workload sketch
auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
- auto context = GpuWorkloadContext{ &cl_compile_ctx };
- GpuWorkloadSketch sketch{ &context };
+ auto context = GpuWorkloadContext{&cl_compile_ctx};
+ GpuWorkloadSketch sketch{&context};
// Create sketch tensors
auto input_info = context.create_tensor_info(TensorInfo(input_shape, 1, data_type, DataLayout::NHWC));
@@ -101,14 +104,14 @@ protected:
// Create Pool2dSettings
GpuPool2dSettings pool_settings = GpuPool2dSettings().mixed_precision(mixed_precision);
- ITensorInfo *ans_info = FunctionType::create_op(sketch, &input_info, pool_attr, pool_settings);
- GpuOutput::create_op(sketch, ans_info, &dst_info);
+ ITensorInfo *ans_info = FunctionType::create_op(sketch, input_info, pool_attr, pool_settings);
+ GpuOutput::create_op(sketch, ans_info, dst_info);
// Configure runtime
ClWorkloadRuntime runtime;
runtime.configure(sketch);
// (Important) Allocate auxiliary tensor memory if there are any
- for(auto &data : runtime.get_auxiliary_tensors())
+ for (auto &data : runtime.get_auxiliary_tensors())
{
CLTensor *tensor = std::get<0>(data);
TensorInfo info = std::get<1>(data);
@@ -121,8 +124,8 @@ protected:
TensorType t_dst{};
// Initialize user tensors
- t_input.allocator()->init(input_info);
- t_dst.allocator()->init(dst_info);
+ t_input.allocator()->init(*input_info);
+ t_dst.allocator()->init(*dst_info);
// Allocate and fill user tensors
t_input.allocator()->allocate();
@@ -131,7 +134,7 @@ protected:
fill(AccessorType(t_input), 0);
// Run runtime
- runtime.run({ &t_input, &t_dst });
+ runtime.run({&t_input, &t_dst});
return t_dst;
}
@@ -149,36 +152,57 @@ protected:
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DynamicFusionGpuPool2dValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+class DynamicFusionGpuPool2dValidationFixture
+ : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
- void setup(TensorShape input_shape, PoolingType pool_type, Size2D pool_size, Padding2D pad, Size2D stride, bool exclude_padding, DataType data_type)
+ void setup(TensorShape input_shape,
+ PoolingType pool_type,
+ Size2D pool_size,
+ Padding2D pad,
+ Size2D stride,
+ bool exclude_padding,
+ DataType data_type)
{
- DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape,
- Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(exclude_padding),
- data_type, false);
+ DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(
+ input_shape,
+ Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(
+ exclude_padding),
+ data_type, false);
}
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DynamicFusionGpuPool2dMixedPrecisionValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+class DynamicFusionGpuPool2dMixedPrecisionValidationFixture
+ : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
- void setup(TensorShape input_shape, PoolingType pool_type, Size2D pool_size, Padding2D pad, Size2D stride, bool exclude_padding, DataType data_type, bool mixed_precision)
+ void setup(TensorShape input_shape,
+ PoolingType pool_type,
+ Size2D pool_size,
+ Padding2D pad,
+ Size2D stride,
+ bool exclude_padding,
+ DataType data_type,
+ bool mixed_precision)
{
- DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape,
- Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(exclude_padding),
- data_type, mixed_precision);
+ DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(
+ input_shape,
+ Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(
+ exclude_padding),
+ data_type, mixed_precision);
}
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class DynamicFusionGpuPool2dSpecialValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+class DynamicFusionGpuPool2dSpecialValidationFixture
+ : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
void setup(TensorShape input_shape, Pool2dAttributes pool_attr, DataType data_type)
{
- DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, pool_attr, data_type, false);
+ DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(
+ input_shape, pool_attr, data_type, false);
}
};
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-23 10:03:31 +0000