Remove tests/benchmark_examples, tests/validate_examples and corresponding build options
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Change-Id: I8c6f753d3ef3a95327967f62e00309eb32ba7470
diff --git a/tests/SConscript b/tests/SConscript
index c8de603..d1f72ba 100644
--- a/tests/SConscript
+++ b/tests/SConscript
@@ -30,12 +30,8 @@
# vars is imported from arm_compute:
variables = [
- #FIXME: Remove before release!
- BoolVariable("benchmark_examples", "Build benchmark examples programs", True),
- BoolVariable("validate_examples", "Build validate examples programs", True),
- #FIXME Switch the following two options to False before releasing
- BoolVariable("validation_tests", "Build validation test programs", True),
- BoolVariable("benchmark_tests", "Build benchmark test programs", True),
+ BoolVariable("validation_tests", "Build validation test programs", False),
+ BoolVariable("benchmark_tests", "Build benchmark test programs", False),
("test_filter", "Pattern to specify the tests' filenames to be compiled", "*.cpp")
]
@@ -80,20 +76,10 @@
test_env.Append(LIBS = ["arm_compute_graph", "arm_compute", "arm_compute_core"])
arm_compute_lib = arm_compute_graph_so
-#FIXME Delete before release
-if env['internal_only']:
- test_env.Append(CPPDEFINES=['INTERNAL_ONLY'])
-
-test_env.Append(CPPPATH = ["#3rdparty/include"])
-test_env.Append(LIBPATH = ["#3rdparty/%s/%s" % (env['os'], env['arch'])])
-
common_files = Glob('*.cpp')
common_objects = [test_env.StaticObject(f) for f in common_files]
files_benchmark = Glob('benchmark/*.cpp')
-#FIXME Delete before release
-if env['internal_only']:
- files_benchmark += Glob('../3rdparty/tests/benchmark/*.cpp')
# Add unit tests
files_validation = Glob('validation/UNIT/*/*.cpp')
@@ -110,23 +96,14 @@
files_benchmark += Glob('benchmark/CL/*/' + filter_pattern)
files_benchmark += Glob('benchmark/CL/' + filter_pattern)
- #FIXME Delete before release
- if env['internal_only']:
- files_benchmark += Glob('../3rdparty/tests/benchmark/CL/' + filter_pattern)
files_validation += Glob('validation/CL/*/' + filter_pattern)
files_validation += Glob('validation/CL/' + filter_pattern)
- #FIXME Delete before release
- if env['internal_only']:
- files_validation += Glob('../3rdparty/tests/validation/CL/' + filter_pattern)
if env['neon']:
filter_pattern = test_env['test_filter']
files_benchmark += Glob('benchmark/NEON/*/' + filter_pattern)
files_benchmark += Glob('benchmark/NEON/' + filter_pattern)
- #FIXME Delete before release
- if env['internal_only']:
- files_benchmark += Glob('../3rdparty/tests/benchmark/NEON/' + filter_pattern)
files_validation += Glob('validation/NEON/*/' + filter_pattern)
files_validation += Glob('validation/NEON/' + filter_pattern)
@@ -167,74 +144,3 @@
Default(arm_compute_validation)
Export('arm_compute_validation')
- #FIXME: Remove before release!
- if test_env['validate_examples']:
- files_validate_examples = [ test_env.Object('validate_examples/RunExample.cpp') ] + [ x for x in common_objects if not "main.o" in str(x)]
- arm_compute_validate_examples = []
- if test_env['neon']:
- for file in Glob("validate_examples/neon_*.cpp"):
- example = "validate_" + os.path.basename(os.path.splitext(str(file))[0])
- arm_compute_validate_examples += [ test_env.Program(example, [ test_env.Object(source=file, target=example) ] + files_validate_examples, LIBS = [ arm_compute_validation_framework]) ]
- if test_env['opencl']:
- cl_examples = []
- files = Glob("validate_examples/cl_*.cpp")
- if test_env['neon']:
- files += Glob("validate_examples/neoncl_*.cpp")
- for file in files:
- example = "validate_" + os.path.basename(os.path.splitext(str(file))[0])
- cl_examples += [ test_env.Program(example, [ test_env.Object(source=file, target=example) ] + files_validate_examples, LIBS = test_env["LIBS"] + [ arm_compute_validation_framework ]) ]
- arm_compute_validate_examples += cl_examples
- if test_env['opencl'] and test_env['neon']:
- graph_utils = test_env.Object(source="../utils/GraphUtils.cpp", target="GraphUtils")
- for file in Glob("validate_examples/graph_*.cpp"):
- example = "validate_" + os.path.basename(os.path.splitext(str(file))[0])
- if env['os'] in ['android', 'bare_metal'] or env['standalone']:
- prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils]+ files_validate_examples, LIBS = test_env["LIBS"] + [ arm_compute_validation_framework ], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--whole-archive',arm_compute_lib,'-Wl,--no-whole-archive'])
- arm_compute_validate_examples += [ prog ]
- else:
- #-Wl,--allow-shlib-undefined: Ignore dependencies of dependencies
- prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils]+ files_validate_examples, LIBS = test_env["LIBS"] + ["arm_compute_graph", arm_compute_validation_framework], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--allow-shlib-undefined'] )
- arm_compute_validate_examples += [ prog ]
- arm_compute_validate_examples = install_bin(arm_compute_validate_examples)
- Depends(arm_compute_validate_examples, arm_compute_validation_framework)
- Depends(arm_compute_validate_examples, arm_compute_test_framework)
- Depends(arm_compute_validate_examples, arm_compute_lib)
- Default(arm_compute_validate_examples)
- Export('arm_compute_validate_examples')
-
-#FIXME: Remove before release!
-if test_env['benchmark_examples']:
- files_benchmark_examples = test_env.Object('benchmark_examples/RunExample.cpp')
- graph_utils = test_env.Object(source="../utils/GraphUtils.cpp", target="GraphUtils")
- graph_params = test_env.Object(source="../utils/CommonGraphOptions.cpp", target="CommonGraphOptions")
- arm_compute_benchmark_examples = []
- for examples_folder in [ "../examples", "../3rdparty/examples"]:
- if test_env['neon']:
- for file in Glob("%s/neon_*.cpp" % examples_folder):
- example = "benchmark_" + os.path.basename(os.path.splitext(str(file))[0])
- arm_compute_benchmark_examples += [ test_env.Program(example, [ test_env.Object(source=file, target=example) ] + files_benchmark_examples) ]
- if test_env['opencl']:
- cl_examples = []
- files = Glob("%s/cl_*.cpp" % examples_folder)
- if test_env['neon']:
- files += Glob("%s/neoncl_*.cpp" % examples_folder)
- for file in files:
- example = "benchmark_" + os.path.basename(os.path.splitext(str(file))[0])
- cl_examples += [ test_env.Program(example, [ test_env.Object(source=file, target=example) ] + files_benchmark_examples, LIBS = test_env["LIBS"]) ]
- arm_compute_benchmark_examples += cl_examples
-
- # Graph examples
- for file in Glob("%s/graph_*.cpp" % examples_folder ):
- example = "benchmark_" + os.path.basename(os.path.splitext(str(file))[0])
- if env['os'] in ['android', 'bare_metal'] or env['standalone']:
- prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils, graph_params]+ files_benchmark_examples, LIBS = test_env["LIBS"], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--whole-archive',arm_compute_lib,'-Wl,--no-whole-archive'])
- arm_compute_benchmark_examples += [ prog ]
- else:
- #-Wl,--allow-shlib-undefined: Ignore dependencies of dependencies
- prog = test_env.Program(example, [ test_env.Object(source=file, target=example), graph_utils, graph_params]+ files_benchmark_examples, LIBS = test_env["LIBS"] + ["arm_compute_graph"], LINKFLAGS=test_env["LINKFLAGS"]+['-Wl,--allow-shlib-undefined'] )
- arm_compute_benchmark_examples += [ prog ]
- arm_compute_benchmark_examples = install_bin(arm_compute_benchmark_examples)
- Depends(arm_compute_benchmark_examples, arm_compute_test_framework)
- Depends(arm_compute_benchmark_examples, arm_compute_lib)
- Default(arm_compute_benchmark_examples)
- Export('arm_compute_benchmark_examples')
diff --git a/tests/benchmark_examples/RunExample.cpp b/tests/benchmark_examples/RunExample.cpp
deleted file mode 100644
index a7a8be0..0000000
--- a/tests/benchmark_examples/RunExample.cpp
+++ /dev/null
@@ -1,183 +0,0 @@
-/*
- * Copyright (c) 2018-2019 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.
- */
-#include "utils/Utils.h"
-//FIXME / INTERNAL_ONLY: This file should not be released!
-
-#define BENCHMARK_EXAMPLES
-#include "utils/Utils.cpp"
-
-#include "arm_compute/runtime/Scheduler.h"
-#include "tests/framework/Framework.h"
-#include "tests/framework/Macros.h"
-#include "tests/framework/command_line/CommonOptions.h"
-#include "tests/framework/instruments/Instruments.h"
-#include "utils/command_line/CommandLineParser.h"
-
-#ifdef ARM_COMPUTE_CL
-#include "arm_compute/runtime/CL/CLHelpers.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#endif /* ARM_COMPUTE_CL */
-#ifdef ARM_COMPUTE_GC
-#include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h"
-#endif /* ARM_COMPUTE_GC */
-
-#include <libgen.h>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-
-namespace
-{
-std::string command_line(int argc, char **argv)
-{
- std::stringstream ss;
- for(int i = 0; i < argc; i++)
- {
- ss << argv[i] << " ";
- }
- return ss.str();
-}
-} // namespace
-namespace arm_compute
-{
-namespace utils
-{
-static std::unique_ptr<Example> g_example = nullptr;
-static std::vector<char *> g_example_argv = {};
-class ExampleTest : public arm_compute::test::framework::TestCase
-{
-public:
- ExampleTest() = default;
- void do_setup() override
- {
- ARM_COMPUTE_ERROR_ON_NULLPTR(g_example.get());
- _is_setup = g_example->do_setup(g_example_argv.size(), &g_example_argv[0]);
- }
- void do_run() override
- {
- if(_is_setup)
- {
- g_example->do_run();
- }
- }
- void do_teardown() override
- {
- if(_is_setup)
- {
- g_example->do_teardown();
- }
- g_example = nullptr;
- }
-
-private:
- bool _is_setup{ false };
-};
-
-int run_example(int argc, char **argv, std::unique_ptr<Example> example)
-{
- utils::CommandLineParser parser;
- framework::CommonOptions options(parser);
- auto example_args = parser.add_option<utils::ListOption<std::string>>("example_args");
- example_args->set_help("Arguments to pass to the example separated by commas (e.g: arg0,arg1,arg2)");
- framework::Framework &framework = framework::Framework::get();
-
- parser.parse(argc, argv);
-
- if(options.help->is_set() && options.help->value())
- {
- parser.print_help(argv[0]);
- return 0;
- }
-
- std::vector<std::unique_ptr<framework::Printer>> printers = options.create_printers();
- g_example = std::move(example);
- g_example_argv.clear();
- g_example_argv.emplace_back(argv[0]);
- for(auto &arg : example_args->value())
- {
- g_example_argv.emplace_back(const_cast<char *>(arg.c_str())); // NOLINT
- }
-
- if(options.log_level->value() > framework::LogLevel::NONE)
- {
- for(auto &p : printers)
- {
- p->print_global_header();
- }
- }
-
-#ifdef ARM_COMPUTE_CL
- if(opencl_is_available())
- {
- auto ctx_dev_err = create_opencl_context_and_device();
- ARM_COMPUTE_ERROR_ON_MSG(std::get<2>(ctx_dev_err) != CL_SUCCESS, "Failed to create OpenCL context");
- CLScheduler::get()
- .default_init_with_context(std::get<1>(ctx_dev_err), std::get<0>(ctx_dev_err));
- }
-#endif /* ARM_COMPUTE_CL */
-
- if(options.log_level->value() >= framework::LogLevel::CONFIG)
- {
- for(auto &p : printers)
- {
- p->print_entry("Version", build_information());
- p->print_entry("CommandLine", command_line(argc, argv));
-#ifdef ARM_COMPUTE_CL
- if(opencl_is_available())
- {
- p->print_entry("CL_DEVICE_VERSION", CLKernelLibrary::get().get_device_version());
- }
- else
- {
- p->print_entry("CL_DEVICE_VERSION", "Unavailable");
- }
-#endif /* ARM_COMPUTE_CL */
- p->print_entry("Iterations", support::cpp11::to_string(options.iterations->value()));
- }
- }
-
- framework.init(options.instruments->value(), options.iterations->value(), framework::DatasetMode::ALL, "", "", options.log_level->value());
- for(auto &p : printers)
- {
- framework.add_printer(p.get());
- }
- framework.set_throw_errors(options.throw_errors->value());
- arm_compute::test::framework::detail::TestSuiteRegistrar suite{ "Examples" };
- framework.add_test_case<ExampleTest>(basename(argv[0]), framework::DatasetMode::ALL, arm_compute::test::framework::TestCaseFactory::Status::ACTIVE);
-
- //func(argc, argv);
- bool success = framework.run();
- if(options.log_level->value() > framework::LogLevel::NONE)
- {
- for(auto &p : printers)
- {
- p->print_global_footer();
- }
- }
-
- return (success ? 0 : 1);
-}
-
-} // namespace utils
-} // namespace arm_compute
diff --git a/tests/validate_examples/RunExample.cpp b/tests/validate_examples/RunExample.cpp
deleted file mode 100644
index 41ed851..0000000
--- a/tests/validate_examples/RunExample.cpp
+++ /dev/null
@@ -1,207 +0,0 @@
-/*
- * Copyright (c) 2018 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 "utils/Utils.h"
-//FIXME / INTERNAL_ONLY: This file should not be released!
-
-#define BENCHMARK_EXAMPLES
-#include "utils/Utils.cpp"
-
-#include "ValidateExample.h"
-#include "arm_compute/runtime/Scheduler.h"
-#include "tests/AssetsLibrary.h"
-#include "tests/Globals.h"
-#include "tests/framework/Framework.h"
-#include "tests/framework/Macros.h"
-#include "tests/framework/command_line/CommonOptions.h"
-#include "tests/framework/instruments/Instruments.h"
-#include "utils/command_line/CommandLineParser.h"
-
-#ifdef ARM_COMPUTE_CL
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#endif /* ARM_COMPUTE_CL */
-#ifdef ARM_COMPUTE_GC
-#include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h"
-#endif /* ARM_COMPUTE_GC */
-
-#include <libgen.h>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-
-namespace arm_compute
-{
-namespace test
-{
-std::unique_ptr<AssetsLibrary> library;
-} // namespace test
-namespace utils
-{
-static std::unique_ptr<ValidateExample> g_example = nullptr;
-static std::vector<char *> g_example_argv = {};
-
-namespace
-{
-std::string command_line(int argc, char **argv)
-{
- std::stringstream ss;
- for(int i = 0; i < argc; i++)
- {
- ss << argv[i] << " ";
- }
- return ss.str();
-}
-
-template <bool validate>
-class ExampleTest : public arm_compute::test::framework::TestCase
-{
-public:
- ExampleTest() = default;
- void do_setup() override
- {
- ARM_COMPUTE_ERROR_ON_NULLPTR(g_example.get());
- _is_setup = g_example->do_setup(g_example_argv.size(), &g_example_argv[0]);
- }
- void do_run() override
- {
- if(_is_setup)
- {
- g_example->do_run();
- }
- }
- void do_teardown() override
- {
- if(_is_setup)
- {
- if(validate)
- {
- g_example->do_validate();
- }
- g_example->do_teardown();
- }
- g_example = nullptr;
- }
-
-private:
- bool _is_setup{ false };
-};
-
-} // namespace
-int run_example(int argc, char **argv, std::unique_ptr<ValidateExample> example)
-{
- utils::CommandLineParser parser;
- framework::CommonOptions options(parser);
- auto example_args = parser.add_option<utils::ListOption<std::string>>("example_args");
- example_args->set_help("Arguments to pass to the example separated by commas (e.g: arg0,arg1,arg2)");
- auto seed = parser.add_option<utils::SimpleOption<std::random_device::result_type>>("seed", std::random_device()());
- seed->set_help("Global seed for random number generation");
- auto validate = parser.add_option<utils::SimpleOption<int>>("validate", 1);
- validate->set_help("Enable / disable output validation (0/1)");
-
- framework::Framework &framework = framework::Framework::get();
-
- parser.parse(argc, argv);
-
- if(options.help->is_set() && options.help->value())
- {
- parser.print_help(argv[0]);
- return 0;
- }
-
- std::vector<std::unique_ptr<framework::Printer>> printers = options.create_printers();
- g_example = std::move(example);
- g_example_argv.clear();
- g_example_argv.emplace_back(argv[0]);
- for(auto &arg : example_args->value())
- {
- g_example_argv.emplace_back(const_cast<char *>(arg.c_str())); // NOLINT
- }
-
- library = support::cpp14::make_unique<AssetsLibrary>("." /* Only using random values */, seed->value());
-
- if(options.log_level->value() > framework::LogLevel::NONE)
- {
- for(auto &p : printers)
- {
- p->print_global_header();
- }
- }
-
- if(options.log_level->value() >= framework::LogLevel::CONFIG)
- {
- for(auto &p : printers)
- {
- p->print_entry("Version", build_information());
- p->print_entry("CommandLine", command_line(argc, argv));
- p->print_entry("Seed", support::cpp11::to_string(seed->value()));
-#ifdef ARM_COMPUTE_CL
- if(opencl_is_available())
- {
- if(!CLScheduler::get().is_initialised())
- {
- CLScheduler::get().default_init();
- }
- p->print_entry("CL_DEVICE_VERSION", CLKernelLibrary::get().get_device_version());
- }
- else
- {
- p->print_entry("CL_DEVICE_VERSION", "Unavailable");
- }
-#endif /* ARM_COMPUTE_CL */
- p->print_entry("Iterations", support::cpp11::to_string(options.iterations->value()));
- g_example->print_parameters(*p);
- }
- }
-
- framework.init(options.instruments->value(), options.iterations->value(), framework::DatasetMode::ALL, "", "", options.log_level->value());
- for(auto &p : printers)
- {
- framework.add_printer(p.get());
- }
-
- framework.set_throw_errors(options.throw_errors->value());
- arm_compute::test::framework::detail::TestSuiteRegistrar suite{ "Examples" };
- if(validate->value() != 0)
- {
- framework.add_test_case<ExampleTest<true>>(basename(argv[0]), framework::DatasetMode::ALL, arm_compute::test::framework::TestCaseFactory::Status::ACTIVE);
- }
- else
- {
- framework.add_test_case<ExampleTest<false>>(basename(argv[0]), framework::DatasetMode::ALL, arm_compute::test::framework::TestCaseFactory::Status::ACTIVE);
- }
-
- //func(argc, argv);
- bool success = framework.run();
- if(options.log_level->value() > framework::LogLevel::NONE)
- {
- for(auto &p : printers)
- {
- p->print_global_footer();
- }
- }
-
- return (success ? 0 : 1);
-}
-
-} // namespace utils
-} // namespace arm_compute
diff --git a/tests/validate_examples/ValidateExample.h b/tests/validate_examples/ValidateExample.h
deleted file mode 100644
index 2721508..0000000
--- a/tests/validate_examples/ValidateExample.h
+++ /dev/null
@@ -1,85 +0,0 @@
-/*
- * Copyright (c) 2016-2018 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 __VALIDATE_EXAMPLE_H__
-#define __VALIDATE_EXAMPLE_H__
-
-#include "utils/Utils.h"
-namespace arm_compute
-{
-namespace test
-{
-namespace framework
-{
-class Printer;
-} // namespace framework
-} // namespace test
-namespace utils
-{
-/** Abstract ValidateExample class.
- *
- * All examples with a validation stage have to inherit from this class.
- */
-class ValidateExample
-{
-public:
- /** Setup the example.
- *
- * @param[in] argc Argument count.
- * @param[in] argv Argument values.
- */
- virtual bool do_setup(int argc, char **argv)
- {
- return true;
- };
- /** Run the example. */
- virtual void do_run() {};
- /** Run reference implementation and validate against the target output
- */
- virtual void do_validate()
- {
- }
- /** Teardown the example. */
- virtual void do_teardown() {};
- /** Print the example parameters
- *
- * @param[in,out] printer Printer to use to print the parameters
- */
- virtual void print_parameters(test::framework::Printer &printer)
- {
- }
-
- /** Default destructor */
- virtual ~ValidateExample() = default;
-};
-/** Run an example and handle the potential exceptions it throws
- *
- * @param[in] argc Number of command line arguments
- * @param[in] argv Command line arguments
- * @param[in] example Example to run
- */
-int run_example(int argc, char **argv, std::unique_ptr<ValidateExample> example);
-
-} // namespace utils
-} // namespace arm_compute
-#endif /* __VALIDATE_EXAMPLE_H__ */
diff --git a/tests/validate_examples/cl_gemm.cpp b/tests/validate_examples/cl_gemm.cpp
deleted file mode 100644
index 4e406cb..0000000
--- a/tests/validate_examples/cl_gemm.cpp
+++ /dev/null
@@ -1,426 +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_CL /* Needed by Utils.cpp to handle OpenCL exceptions properly */
-#error "This example needs to be built with -DARM_COMPUTE_CL"
-#endif /* ARM_COMPUTE_CL */
-
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
-#include "arm_compute/runtime/CL/CLFunctions.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-
-#include "tests/AssetsLibrary.h"
-#include "tests/CL/CLAccessor.h"
-#include "tests/Globals.h"
-#include "tests/IAccessor.h"
-#include "tests/SimpleTensor.h"
-#include "tests/validation/Validation.h"
-#include "tests/validation/reference/GEMM.h"
-#include "tests/validation/reference/GEMMLowp.h"
-
-#include "utils/TypePrinter.h"
-#include "utils/Utils.h"
-#include "utils/command_line/CommandLineOptions.h"
-#include "utils/command_line/CommandLineParser.h"
-
-#include "ValidateExample.h"
-
-#include <cstdlib>
-
-using namespace arm_compute;
-using namespace utils;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-constexpr float abs_tolerance_f32(0.0001f); /**< F32 Absolute tolerance value for comparing reference's output against implementation's output for
- * floating point data types in case using relative tolerance fails because of small values */
-RelativeTolerance<float> tolerance_f32(0.001f); /**< F32 Tolerance value for comparing reference's output against implementation's output for floating point data types */
-RelativeTolerance<half_float::half> tolerance_f16(half(0.2)); /**< F16 Tolerance value for comparing reference's output against implementation's output for floating point data types */
-constexpr float tolerance_num_f16 = 0.02f; /**< F16 Tolerance number */
-
-namespace arm_compute
-{
-DataType data_type_from_name(const std::string &name)
-{
- static const std::map<std::string, DataType> data_types =
- {
- { "f16", DataType::F16 },
- { "f32", DataType::F32 },
- { "qasymm8", DataType::QASYMM8 },
- };
-
-#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED
- try
- {
-#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */
- return data_types.at(utility::tolower(name));
-
-#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED
- }
- catch(const std::out_of_range &)
- {
- throw std::invalid_argument(name);
- }
-#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */
-}
-
-inline ::std::istream &operator>>(::std::istream &stream, DataType &data_type)
-{
- std::string value;
- stream >> value;
- data_type = data_type_from_name(value);
- return stream;
-}
-} // namespace arm_compute
-namespace
-{
-class GEMMCommandLineOptions final
-{
-public:
- explicit GEMMCommandLineOptions(CommandLineParser &parser) noexcept
- : help(parser.add_option<ToggleOption>("help")),
- add_bias(parser.add_option<ToggleOption>("add_bias")),
- M(parser.add_option<SimpleOption<int>>("m", 7)),
- N(parser.add_option<SimpleOption<int>>("n", 3)),
- K(parser.add_option<SimpleOption<int>>("k", 5)),
- B(parser.add_option<SimpleOption<int>>("b", 1)),
- alpha(parser.add_option<SimpleOption<float>>("alpha", 1.f)),
- beta(parser.add_option<SimpleOption<float>>("beta", 0.f)),
- offset_src0(parser.add_option<SimpleOption<int>>("offset_i0", 10)),
- offset_src1(parser.add_option<SimpleOption<int>>("offset_i1", 10)),
- offset_dst(parser.add_option<SimpleOption<int>>("offset_o", 10)),
- scale_src0(parser.add_option<SimpleOption<float>>("scale_i0", 1.f / 255)),
- scale_src1(parser.add_option<SimpleOption<float>>("scale_i1", 1.f / 255)),
- scale_dst(parser.add_option<SimpleOption<float>>("scale_o", 1.f / 255)),
- data_type()
- {
- // Setup data type
- const std::set<arm_compute::DataType> supported_data_types
- {
- DataType::F16,
- DataType::F32,
- DataType::QASYMM8,
- };
- data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32);
-
- // Setup help strings
- help->set_help("Show this help message");
- add_bias->set_help("Add bias to the GEMM. Used when running in QASYMM8");
- M->set_help("M value");
- N->set_help("N value");
- K->set_help("K value");
- B->set_help("B value - number of batches");
- alpha->set_help("Alpha value");
- beta->set_help("Beta value");
- offset_src0->set_help("Offset of first input. Used when running in QASYMM8");
- offset_src1->set_help("Offset of second input. Used when running in QASYMM8");
- offset_dst->set_help("Offset of output. Used when running in QASYMM8");
- scale_src0->set_help("Scale of first input. Used when running in QASYMM8");
- scale_src1->set_help("Scale of second input. Used when running in QASYMM8");
- scale_dst->set_help("Scale of output. Used when running in QASYMM8");
- data_type->set_help("Data type to use");
- }
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- GEMMCommandLineOptions(const GEMMCommandLineOptions &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- GEMMCommandLineOptions &operator=(const GEMMCommandLineOptions &) = delete;
- /** Allow instances of this class to be moved */
- GEMMCommandLineOptions(GEMMCommandLineOptions &&) noexcept(true) = default;
- /** Allow instances of this class to be moved */
- GEMMCommandLineOptions &operator=(GEMMCommandLineOptions &&) noexcept(true) = default;
- /** Default destructor */
- ~GEMMCommandLineOptions() = default;
-
-public:
- ToggleOption *help;
- ToggleOption *add_bias;
- SimpleOption<int> *M;
- SimpleOption<int> *N;
- SimpleOption<int> *K;
- SimpleOption<int> *B;
- SimpleOption<float> *alpha;
- SimpleOption<float> *beta;
- SimpleOption<int> *offset_src0;
- SimpleOption<int> *offset_src1;
- SimpleOption<int> *offset_dst;
- SimpleOption<float> *scale_src0;
- SimpleOption<float> *scale_src1;
- SimpleOption<float> *scale_dst;
- EnumOption<arm_compute::DataType> *data_type;
-};
-} // namespace
-
-class CLGEMMValidateExample : public ValidateExample
-{
-public:
- bool do_setup(int argc, char **argv) override
- {
- CLScheduler::get().default_init();
-
- // Parse options
- CommandLineParser parser;
- GEMMCommandLineOptions gemm_options(parser);
- parser.parse(argc, argv);
-
- // Print help
- const bool print_help = gemm_options.help->is_set() ? gemm_options.help->value() : false;
- if(print_help)
- {
- parser.print_help(argv[0]);
- return false;
- }
-
- // Consume parameters
- consume_params(gemm_options);
- print_parameters_internal();
-
- // Calculate re-quantization parameters
- if(data_type == DataType::QASYMM8)
- {
- float multiplier = scale_src0 * scale_src1 / scale_dst;
- quantization::calculate_quantized_multiplier_less_than_one(multiplier, &dst_multiplier, &dst_shift);
- }
-
- // Initialize GEMM inputs/outputs
- src0.allocator()->init(TensorInfo(TensorShape(K, M, B), 1, data_type));
- src1.allocator()->init(TensorInfo(TensorShape(N, K, B), 1, data_type));
- src2.allocator()->init(TensorInfo(TensorShape(N, M, B), 1, data_type));
- init_sgemm_output(dst, src0, src1, data_type);
-
- // Configure function
- if(data_type == DataType::QASYMM8)
- {
- src0.info()->set_quantization_info(QuantizationInfo(scale_src0, offset_src0));
- src1.info()->set_quantization_info(QuantizationInfo(scale_src1, offset_src1));
- dst.info()->set_quantization_info(QuantizationInfo(scale_dst, offset_dst));
- biases.allocator()->init(TensorInfo(TensorShape(N), 1, DataType::S32));
- init_sgemm_output(tmp_dst, src0, src1, DataType::S32);
-
- // Configure GEMMlowp matrix multiply function
- mm_gemmlowp.configure(&src0, &src1, nullptr, &tmp_dst);
-
- // Configure GEMMlowp output stage
- mm_gemmlowp_output_stage.configure(&tmp_dst, add_bias ? &biases : nullptr, &dst, dst_multiplier, dst_shift, offset_dst);
- tmp_dst.allocator()->allocate();
- biases.allocator()->allocate();
- fill(CLAccessor(biases), 3);
- }
- else
- {
- // Configure matrix multiply function
- mm_gemm.configure(&src0, &src1, &src2, &dst, alpha, beta);
- }
-
- // Allocate all the tensors
- src0.allocator()->allocate();
- src1.allocator()->allocate();
- dst.allocator()->allocate();
- src2.allocator()->allocate();
-
- fill(CLAccessor(src0), 0);
- fill(CLAccessor(src1), 1);
- fill(CLAccessor(src2), 2);
-
- return true;
- }
-
- void print_parameters_internal()
- {
- std::cout << "Datatype : " << string_from_data_type(data_type) << "\n";
- std::cout << "M : " << support::cpp11::to_string(M) << "\n";
- std::cout << "N : " << support::cpp11::to_string(N) << "\n";
- std::cout << "K : " << support::cpp11::to_string(K) << "\n";
- std::cout << "B : " << support::cpp11::to_string(B) << "\n";
- if(data_type == DataType::QASYMM8)
- {
- std::cout << "Scale_Src0 : " << support::cpp11::to_string(scale_src0) << "\n";
- std::cout << "Offset_Src0 : " << support::cpp11::to_string(offset_src0) << "\n";
- std::cout << "Scale_Scr1 : " << support::cpp11::to_string(scale_src1) << "\n";
- std::cout << "Offset_Src1 : " << support::cpp11::to_string(offset_src1) << "\n";
- std::cout << "Scale_Dst : " << support::cpp11::to_string(scale_dst) << "\n";
- std::cout << "Offset_Dst : " << support::cpp11::to_string(offset_dst) << "\n";
- std::cout << "Bias : " << support::cpp11::to_string(add_bias) << "\n";
- }
- else
- {
- std::cout << "Alpha : " << support::cpp11::to_string(alpha) << "\n";
- std::cout << "Beta : " << support::cpp11::to_string(beta) << "\n";
- }
- }
-
- void do_validate() override
- {
- switch(data_type)
- {
- case DataType::F16:
- {
- SimpleTensor<half> ref_src0 = { TensorShape(K, M, B), data_type, 1 };
- SimpleTensor<half> ref_src1 = { TensorShape(N, K, B), data_type, 1 };
- SimpleTensor<half> ref_src2 = { TensorShape(N, M, B), data_type, 1 };
-
- fill(ref_src0, 0);
- fill(ref_src1, 1);
- fill(ref_src2, 2);
-
- SimpleTensor<half> ref_dst = reference::gemm<half>(ref_src0, ref_src1, ref_src2, alpha, beta);
- validate(CLAccessor(dst), ref_dst, tolerance_f16, tolerance_num_f16);
- break;
- }
- case DataType::F32:
- {
- SimpleTensor<float> ref_src0 = { TensorShape(K, M, B), data_type, 1 };
- SimpleTensor<float> ref_src1 = { TensorShape(N, K, B), data_type, 1 };
- SimpleTensor<float> ref_src2 = { TensorShape(N, M, B), data_type, 1 };
-
- fill(ref_src0, 0);
- fill(ref_src1, 1);
- fill(ref_src2, 2);
-
- SimpleTensor<float> ref_dst = reference::gemm<float>(ref_src0, ref_src1, ref_src2, alpha, beta);
- validate(CLAccessor(dst), ref_dst, tolerance_f32, 0.f, abs_tolerance_f32);
- break;
- }
- case DataType::QASYMM8:
- {
- SimpleTensor<uint8_t> ref_src0{ TensorShape(K, M, B), data_type, 1 };
- SimpleTensor<uint8_t> ref_src1{ TensorShape(N, K, B), data_type, 1 };
- SimpleTensor<uint8_t> ref_dst;
-
- // Fill reference
- fill(ref_src0, 0);
- fill(ref_src1, 1);
-
- SimpleTensor<int32_t> ref_tmp_dst = reference::gemmlowp_matrix_multiply_core<int32_t, uint8_t>(ref_src0, ref_src1, TensorShape(N, M, B), offset_src0, offset_src1);
-
- if(add_bias)
- {
- SimpleTensor<int32_t> biases{ TensorShape(N), DataType::S32, 1 };
- // Fill bias
- fill(biases, 3);
- ref_dst = reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(ref_tmp_dst, biases, dst_multiplier, dst_shift, offset_dst);
- }
- else
- {
- ref_dst = reference::gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint<int32_t>(ref_tmp_dst, dst_multiplier, dst_shift, offset_dst);
- }
- validate(CLAccessor(dst), ref_dst);
- break;
- }
- default:
- break;
- }
- }
- void do_run() override
- {
- // Execute the function
- if(data_type == DataType::QASYMM8)
- {
- // Run gemmlowp
- mm_gemmlowp.run();
- // Run output stage
- mm_gemmlowp_output_stage.run();
- }
- else
- {
- // Run gemm
- mm_gemm.run();
- }
-
- // Make sure all the OpenCL jobs are done executing:
- CLScheduler::get().sync();
- }
-
-private:
- template <typename U>
- void fill(U &&tensor, int i)
- {
- switch(tensor.data_type())
- {
- case DataType::F16:
- case DataType::F32:
- {
- std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
- library->fill(tensor, distribution, i);
- break;
- }
- case DataType::S32:
- case DataType::QASYMM8:
- {
- std::uniform_int_distribution<> distribution(-6000, 6000);
- library->fill(tensor, distribution, i);
- break;
- }
- default:
- library->fill_tensor_uniform(tensor, i);
- }
- }
-
- void consume_params(const GEMMCommandLineOptions &opts)
- {
- ARM_COMPUTE_ERROR_ON(opts.M->value() <= 0);
- ARM_COMPUTE_ERROR_ON(opts.N->value() <= 0);
- ARM_COMPUTE_ERROR_ON(opts.K->value() <= 0);
- ARM_COMPUTE_ERROR_ON(opts.B->value() <= 0);
- M = opts.M->value();
- N = opts.N->value();
- K = opts.K->value();
- B = opts.B->value();
- alpha = opts.alpha->value();
- beta = opts.beta->value();
- offset_src0 = opts.offset_src0->value();
- offset_src1 = opts.offset_src1->value();
- offset_dst = opts.offset_dst->value();
- scale_src0 = opts.scale_src0->value();
- scale_src1 = opts.scale_src1->value();
- scale_dst = opts.scale_dst->value();
- add_bias = opts.add_bias->is_set() ? opts.add_bias->value() : true;
- data_type = opts.data_type->value();
- }
-
- CLTensor src0{}, src1{}, src2{}, dst{};
- CLTensor tmp_dst{}, biases{};
-
- CLGEMM mm_gemm{};
- CLGEMMLowpMatrixMultiplyCore mm_gemmlowp{};
- CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint mm_gemmlowp_output_stage{};
-
- size_t M{ 7 }, N{ 3 }, K{ 5 }, B{ 1 };
- DataType data_type{ DataType::F32 };
- float alpha{ 1.0 }, beta{ 0.0 };
- int offset_src0{ 10 }, offset_src1{ 10 }, offset_dst{ 10 };
- float scale_src0{ 1.0f / 255 }, scale_src1{ 1.0f / 255 }, scale_dst{ 1.0f / 255 };
- int32_t dst_multiplier{ 0 }, dst_shift{ 0 };
- bool add_bias{ true };
-};
-
-/** Main program for gemm test
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments
- *
- */
-int main(int argc, char **argv)
-{
- return utils::run_example<CLGEMMValidateExample>(argc, argv);
-}
diff --git a/tests/validate_examples/graph_convolution.cpp b/tests/validate_examples/graph_convolution.cpp
deleted file mode 100644
index 1ab6691..0000000
--- a/tests/validate_examples/graph_convolution.cpp
+++ /dev/null
@@ -1,398 +0,0 @@
-/*
- * Copyright (c) 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.
- */
-#include "arm_compute/graph.h"
-
-#include "support/ToolchainSupport.h"
-
-#include "tests/NEON/Accessor.h"
-#include "tests/validation/Validation.h"
-#include "tests/validation/reference/ConvolutionLayer.h"
-#include "tests/validation/reference/Permute.h"
-
-#include "utils/CommonGraphOptions.h"
-#include "utils/GraphUtils.h"
-#include "utils/Utils.h"
-
-#include "ValidateExample.h"
-#include "graph_validate_utils.h"
-
-#include <utility>
-
-using namespace arm_compute::utils;
-using namespace arm_compute::graph::frontend;
-using namespace arm_compute::graph_utils;
-using namespace arm_compute::graph;
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-/** Convolution command line options used to configure the graph examples
- *
- * (Similar to common options)
- * The options in this object get populated when "parse()" is called on the parser used to construct it.
- * The expected workflow is:
- *
- * CommandLineParser parser;
- * CommonOptions options( parser );
- * parser.parse(argc, argv);
- */
-class ConvolutionOptions final : public CommonGraphValidateOptions
-{
-public:
- explicit ConvolutionOptions(CommandLineParser &parser) noexcept
- : CommonGraphValidateOptions(parser),
- width(parser.add_option<SimpleOption<int>>("width", 9)),
- height(parser.add_option<SimpleOption<int>>("height", 9)),
- channels(parser.add_option<SimpleOption<int>>("channels", 1)),
- batch(parser.add_option<SimpleOption<int>>("batch", 1)),
- weights_width(parser.add_option<SimpleOption<int>>("weights_width", 3)),
- weights_height(parser.add_option<SimpleOption<int>>("weights_height", 3)),
- OFM(parser.add_option<SimpleOption<int>>("OFM", 1)),
- padding_top(parser.add_option<SimpleOption<int>>("padding_top", 0)),
- padding_left(parser.add_option<SimpleOption<int>>("padding_left", 0)),
- padding_bottom(parser.add_option<SimpleOption<int>>("padding_bottom", 0)),
- padding_right(parser.add_option<SimpleOption<int>>("padding_right", 0)),
- stride_x(parser.add_option<SimpleOption<int>>("stride_x", 1)),
- stride_y(parser.add_option<SimpleOption<int>>("stride_y", 1)),
- padding_mode(),
- conv_mode(),
- data_layout(),
- scale(parser.add_option<SimpleOption<float>>("scale", 1.0f)),
- offset(parser.add_option<SimpleOption<int>>("offset", 0)),
- weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)),
- weights_offset(parser.add_option<SimpleOption<int>>("weights_offset", 0)),
- output_scale(parser.add_option<SimpleOption<float>>("output_scale", 1.0f)),
- output_offset(parser.add_option<SimpleOption<int>>("output_offset", 0)),
- input_range_low(parser.add_option<SimpleOption<uint64_t>>("input_range_low")),
- input_range_high(parser.add_option<SimpleOption<uint64_t>>("input_range_high")),
- weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")),
- weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high")),
- input_npy(parser.add_option<SimpleOption<std::string>>("input_image")),
- output_npy(parser.add_option<SimpleOption<std::string>>("reference_image")),
- weights_npy(parser.add_option<SimpleOption<std::string>>("weights_npy")),
- bias_npy(parser.add_option<SimpleOption<std::string>>("bias_image"))
- {
- const std::set<ConvolutionPaddingMode> available_padding_modes
- {
- ConvolutionPaddingMode::Valid,
- ConvolutionPaddingMode::Same
- };
-
- const std::set<arm_compute::graph::ConvolutionMethod> supported_convolution_methods
- {
- arm_compute::graph::ConvolutionMethod::Default,
- arm_compute::graph::ConvolutionMethod::GEMM,
- arm_compute::graph::ConvolutionMethod::Winograd,
- arm_compute::graph::ConvolutionMethod::Direct
- };
-
- const std::set<DataLayout> supported_data_layouts
- {
- DataLayout::NHWC,
- DataLayout::NCHW,
- };
-
- padding_mode = parser.add_option<EnumOption<ConvolutionPaddingMode>>("padding_mode", available_padding_modes, ConvolutionPaddingMode::Valid);
- conv_mode = parser.add_option<EnumOption<arm_compute::graph::ConvolutionMethod>>("convolution_method", supported_convolution_methods, arm_compute::graph::ConvolutionMethod::Default);
- data_layout = parser.add_option<EnumOption<DataLayout>>("layout", supported_data_layouts, DataLayout::NHWC);
-
- padding_mode->set_help("Set padding mode");
- help->set_help("Show this help message");
- width->set_help("Set Input dimension width");
- height->set_help("Set Input dimension height");
- channels->set_help("Set Input dimension channels");
- batch->set_help("Set Input dimension batch");
- weights_width->set_help("Set weights_dimensions width");
- weights_height->set_help("Set weights_dimensions height");
- OFM->set_help("Set OFM");
- padding_top->set_help("Set padding top");
- padding_bottom->set_help("Set padding bottom");
- padding_left->set_help("Set padding left");
- padding_right->set_help("Set padding right");
- stride_x->set_help("Set padding stride x");
- stride_y->set_help("Set padding stride y");
- conv_mode->set_help("Set convolution method");
- scale->set_help("Quantization scale from QASYMM8");
- offset->set_help("Quantization offset from QASYMM8");
- weights_scale->set_help("Quantization scale from QASYMM8");
- weights_offset->set_help("Quantization offset from QASYMM8");
- output_scale->set_help("Quantization scale from QASYMM8");
- output_offset->set_help("Quantization offset from QASYMM8");
- input_npy->set_help("Use input .npy instead");
- output_npy->set_help("Use .npy as a reference");
- input_range_low->set_help("Lower bound for input randomization range");
- input_range_high->set_help("Lower bound for input randomization range");
- weights_range_low->set_help("Lower bound for input randomization range");
- weights_range_high->set_help("Lower bound for input randomization range");
- }
-
- /** Fill out the supplied parameters with user supplied parameters
- *
- * @param[out] os Output stream.
- * @param[in] common_params Example parameters to output
- *
- * @return None.
- */
- void consume_parameters(ExampleParams &common_params)
- {
- common_params.input.width = width->value();
- common_params.input.height = height->value();
- common_params.input.fm = channels->value();
- common_params.input.batch = batch->value();
- common_params.input.quant_info = QuantizationInfo(scale->value(), offset->value());
- common_params.input.npy = input_npy->value();
- common_params.input.range_low = input_range_low->value();
- common_params.input.range_high = input_range_high->value();
-
- common_params.weights.width = weights_width->value();
- common_params.weights.height = weights_height->value();
- common_params.weights.fm = OFM->value();
- common_params.weights.npy = weights_npy->value();
- common_params.weights.quant_info = QuantizationInfo(weights_scale->value(), weights_offset->value());
- common_params.weights.range_low = weights_range_low->value();
- common_params.weights.range_high = weights_range_high->value();
-
- common_params.bias.npy = bias_npy->value();
-
- common_params.output.quant_info = QuantizationInfo(output_scale->value(), output_offset->value());
- common_params.output.npy = output_npy->value();
-
- common_params.convolution.padding_mode = padding_mode->value();
- common_params.convolution.padding_top = padding_top->value();
- common_params.convolution.padding_bottom = padding_bottom->value();
- common_params.convolution.padding_left = padding_left->value();
- common_params.convolution.padding_right = padding_right->value();
- common_params.convolution.padding_stride_x = stride_x->value();
- common_params.convolution.padding_stride_y = stride_y->value();
-
- common_params.data_type = data_type->value();
- common_params.data_layout = data_layout->value();
- common_params.convolution_method = conv_mode->value();
- }
-
- void print_parameters(::std::ostream &os, const ExampleParams &common_params) override
- {
- os << "Threads : " << common_params.common_params.threads << std::endl;
- os << "Target : " << common_params.common_params.target << std::endl;
- os << "Data type : " << common_params.data_type << std::endl;
- os << "Input dimensions(X,Y, Channels, Batch) : (" << common_params.input.width << "," << common_params.input.height << "," << common_params.input.fm << "," << common_params.input.batch << ")"
- << std::endl;
- os << "Weight dimensions(X,Y, Channels(same as input), OFM) : (" << common_params.weights.width << "," << common_params.weights.height << "," << common_params.input.fm << "," <<
- common_params.weights.fm << ")" << std::endl;
- os << "Padding(top, bottom, left, right) (stride x, stride y) : (" << common_params.convolution.padding_top << "," << common_params.convolution.padding_bottom << "," <<
- common_params.convolution.padding_left << "," << common_params.convolution.padding_right << ") (" << common_params.convolution.padding_stride_x << "," << common_params.convolution.padding_stride_y <<
- ")" << std::endl;
- os << "Padding Mode: " << common_params.convolution.padding_mode << std::endl;
- os << "Convolution Method: " << common_params.convolution_method << std::endl;
- }
-
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- ConvolutionOptions(const ConvolutionOptions &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- ConvolutionOptions &operator=(const ConvolutionOptions &) = delete;
- /** Allow instances of this class to be moved */
- ConvolutionOptions(ConvolutionOptions &&) noexcept(true) = default;
- /** Allow instances of this class to be moved */
- ConvolutionOptions &operator=(ConvolutionOptions &&) noexcept(true) = default;
- /** Default destructor */
- ~ConvolutionOptions() override = default;
-
-private:
- SimpleOption<int> *width; /**< Input width */
- SimpleOption<int> *height; /**< Input height */
- SimpleOption<int> *channels; /**< Input channels */
- SimpleOption<int> *batch; /**< Input batch */
- SimpleOption<int> *weights_width; /**< weights width */
- SimpleOption<int> *weights_height; /**< weights height */
- SimpleOption<int> *OFM; /**< Output Feature Map */
- SimpleOption<int> *padding_top; /**< Padding top */
- SimpleOption<int> *padding_left; /**< Padding left */
- SimpleOption<int> *padding_bottom; /**< Padding bottom */
- SimpleOption<int> *padding_right; /**< Padding right */
- SimpleOption<int> *stride_x; /**< Padding stride x */
- SimpleOption<int> *stride_y; /**< Padding stride y */
- EnumOption<ConvolutionPaddingMode> *padding_mode; /**< Padding mode */
- EnumOption<arm_compute::graph::ConvolutionMethod> *conv_mode; /**< Convolution method */
- EnumOption<arm_compute::DataLayout> *data_layout; /**< Graph data layout */
- SimpleOption<float> *scale; /**< Input Quantization scale from QASYMM8 */
- SimpleOption<int> *offset; /**< Input Quantization offset from QASYMM8 */
- SimpleOption<float> *weights_scale; /**< Weights Quantization scale from QASYMM8 */
- SimpleOption<int> *weights_offset; /**< Weights Quantization offset from QASYMM8 */
- SimpleOption<float> *output_scale; /**< Output Quantization scale from QASYMM8 */
- SimpleOption<int> *output_offset; /**< Output Quantization offset from QASYMM8 */
- SimpleOption<uint64_t> *input_range_low; /**< Lower bound for input randomization range */
- SimpleOption<uint64_t> *input_range_high; /**< Upper bound for input randomization range */
- SimpleOption<uint64_t> *weights_range_low; /**< Lower bound for weights randomization range */
- SimpleOption<uint64_t> *weights_range_high; /**< Upper bound for weights randomization range */
-
- SimpleOption<std::string> *input_npy; /**< Use input .npy image */
- SimpleOption<std::string> *output_npy; /**< Use output .npy image to verify*/
- SimpleOption<std::string> *weights_npy; /**< Use weights .npy image */
- SimpleOption<std::string> *bias_npy; /**< Use bias .npy image */
-};
-
-/** ConvolutionLayer Graph example validation accessor class */
-template <typename D>
-class ConvolutionVerifyAccessor final : public VerifyAccessor<D>
-{
- using BaseClassType = VerifyAccessor<D>;
- using BaseClassType::BaseClassType;
- using BaseClassType::_params;
- using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type;
-
- SimpleTensor<D> reference(SimpleTensor<D> &src, SimpleTensor<D> &weights, SimpleTensor<TBias> &bias, const TensorShape &output_shape) override
- {
- // Calculate padding information
- const PadStrideInfo padding_info = calculate_convolution_padding(_params);
-
- //Calculate reference
- return reference::convolution_layer<D>(src, weights, bias, output_shape, padding_info, Size2D(1, 1),
- 1, _params.output.quant_info);
- }
-
- float relative_tolerance() override
- {
- const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance
- {
- {
- arm_compute::graph::Target::CL,
- { { DataType::F16, 0.2f },
- { DataType::F32, 0.5f },
- { DataType::QASYMM8, 1.0f }
- }
- },
- {
- arm_compute::graph::Target::NEON,
- { { DataType::F16, 0.2f },
- { DataType::F32, 0.01f },
- { DataType::QASYMM8, 0.0f }
- }
- }
- };
-
- if(_params.convolution_method == arm_compute::graph::ConvolutionMethod::Winograd
- && _params.data_type == DataType::F32
- && _params.common_params.target == arm_compute::graph::Target::NEON)
- {
- return 0.05f;
- }
- else
- {
- return relative_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
- }
-
- float absolute_tolerance() override
- {
- const std::map<Target, const std::map<DataType, float>> absolute_tolerance
- {
- {
- Target::CL,
- { { DataType::F16, 0.0f },
- { DataType::F32, 0.0001f },
- { DataType::QASYMM8, 0.0f }
- }
- },
- {
- Target::NEON,
- { { DataType::F16, 0.2f },
- { DataType::F32, 0.002f },
- { DataType::QASYMM8, 0.0f }
- }
- }
- };
-
- return absolute_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-
- float tolerance_number() override
- {
- const std::map<Target, const std::map<DataType, float>> absolute_tolerance
- {
- {
- Target::CL,
- { { DataType::F16, 0.07f },
- { DataType::F32, 0.07f },
- { DataType::QASYMM8, 0.0f }
- }
- },
- {
- Target::NEON,
- { { DataType::F16, 0.07f },
- { DataType::F32, 0.0f },
- { DataType::QASYMM8, 0.0f }
- }
- }
- };
-
- return absolute_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-};
-
-} // namespace
-
-class GraphConvolutionValidateExample final : public GraphValidateExample<ConvolutionLayer, ConvolutionOptions, ConvolutionVerifyAccessor>
-{
- using GraphValidateExample::graph;
-
-public:
- GraphConvolutionValidateExample()
- : GraphValidateExample("Convolution Graph example")
- {
- }
-
- ConvolutionLayer GraphFunctionLayer(ExampleParams ¶ms) override
- {
- const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info);
- const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info);
-
- const PixelValue weights_lower = PixelValue(params.weights.range_low, params.data_type, params.weights.quant_info);
- const PixelValue weights_upper = PixelValue(params.weights.range_high, params.data_type, params.weights.quant_info);
-
- // Calculate padding information
- const PadStrideInfo padding_info = calculate_convolution_padding(params);
-
- return ConvolutionLayer(params.weights.width, params.weights.height, params.weights.fm,
- get_accessor(params.weights, weights_lower, weights_upper, 1),
- get_accessor(params.bias, lower, upper, 2),
- padding_info, 1, params.weights.quant_info, params.output.quant_info);
- }
-};
-
-/** Main program for Graph Convolution test
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( Input dimensions [width, height, channels, batch]
- * Weights dimensions [width, height, OFM]
- * Padding [top,bottom,left,right, Stride x, Stride y, mode [Valid / Same / Manual] )
- * Convolution Method[ Auto/GEMM/Winograd/Direct]
- * Verification[tolerance_number,absolute_tolerance,relative_tolerance] )
- *
- */
-int main(int argc, char **argv)
-{
- return arm_compute::utils::run_example<GraphConvolutionValidateExample>(argc, argv);
-}
diff --git a/tests/validate_examples/graph_depthwiseconvolution.cpp b/tests/validate_examples/graph_depthwiseconvolution.cpp
deleted file mode 100644
index 3ea33e1..0000000
--- a/tests/validate_examples/graph_depthwiseconvolution.cpp
+++ /dev/null
@@ -1,394 +0,0 @@
-/*
- * Copyright (c) 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.
- */
-#include "arm_compute/graph.h"
-
-#include "support/ToolchainSupport.h"
-
-#include "tests/NEON/Accessor.h"
-#include "tests/validation/Validation.h"
-#include "tests/validation/reference/DepthwiseConvolutionLayer.h"
-#include "tests/validation/reference/Permute.h"
-
-#include "utils/CommonGraphOptions.h"
-#include "utils/GraphUtils.h"
-#include "utils/Utils.h"
-
-#include "ValidateExample.h"
-#include "graph_validate_utils.h"
-
-#include <utility>
-
-using namespace arm_compute::utils;
-using namespace arm_compute::graph::frontend;
-using namespace arm_compute::graph_utils;
-using namespace arm_compute::graph;
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-/** Depthwise Convolution command line options used to configure the graph examples
- *
- * (Similar to common options)
- * The options in this object get populated when "parse()" is called on the parser used to construct it.
- * The expected workflow is:
- *
- * CommandLineParser parser;
- * CommonOptions options( parser );
- * parser.parse(argc, argv);
- */
-class DepthConvolutionOptions final : public CommonGraphValidateOptions
-{
-public:
- explicit DepthConvolutionOptions(CommandLineParser &parser) noexcept
- : CommonGraphValidateOptions(parser),
- width(parser.add_option<SimpleOption<int>>("width", 9)),
- height(parser.add_option<SimpleOption<int>>("height", 9)),
- channels(parser.add_option<SimpleOption<int>>("channels", 1)),
- batch(parser.add_option<SimpleOption<int>>("batch", 1)),
- weights_width(parser.add_option<SimpleOption<int>>("weights_width", 3)),
- weights_height(parser.add_option<SimpleOption<int>>("weights_height", 3)),
- padding_top(parser.add_option<SimpleOption<int>>("padding_top", 0)),
- padding_left(parser.add_option<SimpleOption<int>>("padding_left", 0)),
- padding_bottom(parser.add_option<SimpleOption<int>>("padding_bottom", 0)),
- padding_right(parser.add_option<SimpleOption<int>>("padding_right", 0)),
- stride_x(parser.add_option<SimpleOption<int>>("stride_x", 1)),
- stride_y(parser.add_option<SimpleOption<int>>("stride_y", 1)),
- padding_mode(),
- conv_mode(),
- depth_multiplier(parser.add_option<SimpleOption<int>>("depth_multiplier", 1)),
- data_layout(),
- scale(parser.add_option<SimpleOption<float>>("scale", 1.0f)),
- offset(parser.add_option<SimpleOption<int>>("offset", 0)),
- weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)),
- weights_offset(parser.add_option<SimpleOption<int>>("weights_offset", 0)),
- output_scale(parser.add_option<SimpleOption<float>>("output_scale", 1.0f)),
- output_offset(parser.add_option<SimpleOption<int>>("output_offset", 0)),
- input_range_low(parser.add_option<SimpleOption<uint64_t>>("input_range_low")),
- input_range_high(parser.add_option<SimpleOption<uint64_t>>("input_range_high")),
- weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")),
- weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high")),
- input_npy(parser.add_option<SimpleOption<std::string>>("input_image")),
- output_npy(parser.add_option<SimpleOption<std::string>>("reference_image")),
- weights_npy(parser.add_option<SimpleOption<std::string>>("weights_npy")),
- bias_npy(parser.add_option<SimpleOption<std::string>>("bias_image"))
- {
- const std::set<ConvolutionPaddingMode> available_padding_modes
- {
- ConvolutionPaddingMode::Valid,
- ConvolutionPaddingMode::Same
- };
-
- const std::set<arm_compute::graph::DepthwiseConvolutionMethod> supported_convolution_methods
- {
- arm_compute::graph::DepthwiseConvolutionMethod::Default,
- arm_compute::graph::DepthwiseConvolutionMethod::GEMV,
- arm_compute::graph::DepthwiseConvolutionMethod::Optimized3x3,
- };
-
- const std::set<DataLayout> supported_data_layouts
- {
- DataLayout::NHWC,
- DataLayout::NCHW,
- };
-
- padding_mode = parser.add_option<EnumOption<ConvolutionPaddingMode>>("padding_mode", available_padding_modes, ConvolutionPaddingMode::Valid);
- conv_mode = parser.add_option<EnumOption<arm_compute::graph::DepthwiseConvolutionMethod>>("convolution_method", supported_convolution_methods,
- arm_compute::graph::DepthwiseConvolutionMethod::Default);
- data_layout = parser.add_option<EnumOption<DataLayout>>("layout", supported_data_layouts, DataLayout::NHWC);
-
- padding_mode->set_help("Set padding mode");
- width->set_help("Set Input dimension width");
- height->set_help("Set Input dimension height");
- channels->set_help("Set Input dimension channels");
- batch->set_help("Set Input dimension batch");
- weights_width->set_help("Set weights_dimensions width");
- weights_height->set_help("Set weights_dimensions height");
- padding_top->set_help("Set padding top");
- padding_bottom->set_help("Set padding bottom");
- padding_left->set_help("Set padding left");
- padding_right->set_help("Set padding right");
- stride_x->set_help("Set padding stride x");
- stride_y->set_help("Set padding stride y");
- conv_mode->set_help("Set convolution method");
- data_layout->set_help("Data layout to use");
- scale->set_help("Quantization scale from QASYMM8");
- offset->set_help("Quantization offset from QASYMM8");
- output_scale->set_help("Quantization scale from QASYMM8");
- output_offset->set_help("Quantization offset from QASYMM8");
- input_npy->set_help("Use input .npy instead");
- output_npy->set_help("Use .npy as a reference");
- input_range_low->set_help("Lower bound for input randomization range");
- input_range_high->set_help("Lower bound for input randomization range");
- weights_scale->set_help("Quantization scale from QASYMM8");
- weights_offset->set_help("Quantization offset from QASYMM8");
- weights_range_low->set_help("Lower bound for input randomization range");
- weights_range_high->set_help("Lower bound for input randomization range");
- depth_multiplier->set_help("Depth multiplier");
- }
-
- /** Fill out the supplied parameters with user supplied parameters
- *
- * @param[out] os Output stream.
- * @param[in] common_params Example parameters to output
- *
- * @return None.
- */
- void consume_parameters(ExampleParams &common_params)
- {
- common_params.input.width = width->value();
- common_params.input.height = height->value();
- common_params.input.fm = channels->value();
- common_params.input.batch = batch->value();
- common_params.input.quant_info = QuantizationInfo(scale->value(), offset->value());
- common_params.input.npy = input_npy->value();
- common_params.input.range_low = input_range_low->value();
- common_params.input.range_high = input_range_high->value();
-
- common_params.weights.width = weights_width->value();
- common_params.weights.height = weights_height->value();
- common_params.weights.npy = weights_npy->value();
- common_params.weights.range_low = weights_range_low->value();
- common_params.weights.range_high = weights_range_high->value();
- common_params.weights.quant_info = QuantizationInfo(weights_scale->value(), weights_offset->value());
-
- common_params.bias.npy = bias_npy->value();
-
- common_params.output.quant_info = QuantizationInfo(output_scale->value(), output_offset->value());
- common_params.output.npy = output_npy->value();
-
- common_params.convolution.padding_mode = padding_mode->value();
- common_params.convolution.padding_top = padding_top->value();
- common_params.convolution.padding_bottom = padding_bottom->value();
- common_params.convolution.padding_left = padding_left->value();
- common_params.convolution.padding_right = padding_right->value();
- common_params.convolution.padding_stride_x = stride_x->value();
- common_params.convolution.padding_stride_y = stride_y->value();
- common_params.convolution.depth_multiplier = depth_multiplier->value();
-
- common_params.data_type = data_type->value();
- common_params.data_layout = data_layout->value();
- common_params.depth_convolution_method = conv_mode->value();
- }
-
- void print_parameters(::std::ostream &os, const ExampleParams &common_params) override
- {
- os << "Threads : " << common_params.common_params.threads << std::endl;
- os << "Target : " << common_params.common_params.target << std::endl;
- os << "Data type : " << common_params.data_type << std::endl;
- os << "Input dimensions(X,Y, Channels, Batch) : (" << common_params.input.width << "," << common_params.input.height << "," << common_params.input.fm << "," << common_params.input.batch << ")"
- << std::endl;
- os << "Weight dimensions(X,Y, Channels(same as input)) : (" << common_params.weights.width << "," << common_params.weights.height << "," << common_params.input.fm << ","
- << ")" << std::endl;
- os << "Padding(top, bottom, left, right) (stride x, stride y) : (" << common_params.convolution.padding_top << "," << common_params.convolution.padding_bottom << "," <<
- common_params.convolution.padding_left << "," << common_params.convolution.padding_right << ") (" << common_params.convolution.padding_stride_x << "," << common_params.convolution.padding_stride_y <<
- ")" << std::endl;
- os << "Padding Mode: " << common_params.convolution.padding_mode << std::endl;
- os << "Convolution Method: " << common_params.depth_convolution_method << std::endl;
- os << "Depth multiplier: " << common_params.convolution.depth_multiplier;
- }
-
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- DepthConvolutionOptions(const DepthConvolutionOptions &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- DepthConvolutionOptions &operator=(const DepthConvolutionOptions &) = delete;
- /** Allow instances of this class to be moved */
- DepthConvolutionOptions(DepthConvolutionOptions &&) noexcept(true) = default;
- /** Allow instances of this class to be moved */
- DepthConvolutionOptions &operator=(DepthConvolutionOptions &&) noexcept(true) = default;
- /** Default destructor */
- ~DepthConvolutionOptions() override = default;
-
-private:
- SimpleOption<int> *width; /**< Input width */
- SimpleOption<int> *height; /**< Input height */
- SimpleOption<int> *channels; /**< Input channels */
- SimpleOption<int> *batch; /**< Input batch */
- SimpleOption<int> *weights_width; /**< weights width */
- SimpleOption<int> *weights_height; /**< weights height */
- SimpleOption<int> *padding_top; /**< Padding top */
- SimpleOption<int> *padding_left; /**< Padding left */
- SimpleOption<int> *padding_bottom; /**< Padding bottom */
- SimpleOption<int> *padding_right; /**< Padding right */
- SimpleOption<int> *stride_x; /**< Padding stride x */
- SimpleOption<int> *stride_y; /**< Padding stride y */
- EnumOption<ConvolutionPaddingMode> *padding_mode; /**< Padding mode */
- EnumOption<arm_compute::graph::DepthwiseConvolutionMethod> *conv_mode; /**< Convolution method */
- SimpleOption<int> *depth_multiplier; /**< Depth multiplier */
- EnumOption<arm_compute::DataLayout> *data_layout; /**< Graph data layout */
- SimpleOption<float> *scale; /**< Input Quantization scale from QASYMM8 */
- SimpleOption<int> *offset; /**< Input Quantization offset from QASYMM8 */
- SimpleOption<float> *weights_scale; /**< Weights Quantization scale from QASYMM8 */
- SimpleOption<int> *weights_offset; /**< Weights Quantization offset from QASYMM8 */
- SimpleOption<float> *output_scale; /**< Output Quantization scale from QASYMM8 */
- SimpleOption<int> *output_offset; /**< Output Quantization offset from QASYMM8 */
- SimpleOption<uint64_t> *input_range_low; /**< Lower bound for input randomization range */
- SimpleOption<uint64_t> *input_range_high; /**< Upper bound for input randomization range */
- SimpleOption<uint64_t> *weights_range_low; /**< Lower bound for weights randomization range */
- SimpleOption<uint64_t> *weights_range_high; /**< Upper bound for weights randomization range */
-
- SimpleOption<std::string> *input_npy; /**< Use input .npy image */
- SimpleOption<std::string> *output_npy; /**< Use output .npy image to verify*/
- SimpleOption<std::string> *weights_npy; /**< Use weights .npy image */
- SimpleOption<std::string> *bias_npy; /**< Use bias .npy image */
-};
-
-/** DepthwiseConvolutionLayer Graph example validation accessor class */
-template <typename D>
-class DepthConvolutionVerifyAccessor final : public VerifyAccessor<D>
-{
-public:
- using BaseClassType = VerifyAccessor<D>;
- using BaseClassType::BaseClassType;
- using BaseClassType::_params;
- using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type;
-
-public:
- SimpleTensor<D> reference(SimpleTensor<D> &src, SimpleTensor<D> &weights, SimpleTensor<TBias> &bias, const TensorShape &output_shape) override
- {
- // Calculate padding information
- const PadStrideInfo padding_info = calculate_convolution_padding(_params);
-
- //Calculate reference
- return reference::depthwise_convolution<D>(src, weights, bias, output_shape, padding_info,
- _params.convolution.depth_multiplier,
- Size2D(1U, 1U),
- _params.output.quant_info);
- }
-
- float relative_tolerance() override
- {
- const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance
- {
- {
- arm_compute::graph::Target::CL,
- { { DataType::F16, 0.01f },
- { DataType::F32, 0.01f },
- { DataType::QASYMM8, 0.0f }
- }
- },
- {
- arm_compute::graph::Target::NEON,
- { { DataType::F16, 0.01f },
- { DataType::F32, 0.01f },
- { DataType::QASYMM8, 1.0f }
- }
- }
- };
-
- return relative_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-
- float absolute_tolerance() override
- {
- const std::map<Target, const std::map<DataType, float>> absolute_tolerance
- {
- {
- Target::CL,
- { { DataType::F16, 0.0f },
- { DataType::F32, 0.0000f },
- { DataType::QASYMM8, 0.0f }
- }
- },
- {
- Target::NEON,
- { { DataType::F16, 0.2f },
- { DataType::F32, 0.002f },
- { DataType::QASYMM8, 0.0f }
- }
- }
- };
-
- return absolute_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-
- float tolerance_number() override
- {
- const std::map<Target, const std::map<DataType, float>> absolute_tolerance
- {
- {
- Target::CL,
- { { DataType::F16, 0.05f },
- { DataType::F32, 0.00f },
- { DataType::QASYMM8, 0.0f }
- }
- },
- {
- Target::NEON,
- { { DataType::F16, 0.05f },
- { DataType::F32, 0.0f },
- { DataType::QASYMM8, 0.0f }
- }
- }
- };
-
- return absolute_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-};
-
-} // namespace
-
-class GraphDepthwiseConvolutionValidateExample final : public GraphValidateExample<DepthwiseConvolutionLayer, DepthConvolutionOptions, DepthConvolutionVerifyAccessor>
-{
- using GraphValidateExample::graph;
-
-public:
- GraphDepthwiseConvolutionValidateExample()
- : GraphValidateExample("DepthWiseConvolution Graph example")
- {
- }
-
- DepthwiseConvolutionLayer GraphFunctionLayer(ExampleParams ¶ms) override
- {
- const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info);
- const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info);
-
- const PixelValue weights_lower = PixelValue(params.weights.range_low, params.data_type, params.weights.quant_info);
- const PixelValue weights_upper = PixelValue(params.weights.range_high, params.data_type, params.weights.quant_info);
-
- // Calculate padding information
- const PadStrideInfo padding_info = calculate_convolution_padding(params);
-
- return DepthwiseConvolutionLayer(params.weights.width, params.weights.height,
- get_accessor(params.weights, weights_lower, weights_upper, 1),
- get_accessor(params.bias, lower, upper, 2),
- padding_info, params.convolution.depth_multiplier, params.weights.quant_info, params.output.quant_info);
- }
-};
-
-/** Main program for Graph Depthwise Convolution test
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( Input dimensions [width, height, channels, batch]
- * Weights dimensions [width, height, channels]
- * Padding [top,bottom,left,right, Stride x, Stride y, mode [Valid / Same / Manual] )
- * Convolution Method[ Default/GEMV/Optimized3x3]
- * Verification[tolerance_number,absolute_tolerance,relative_tolerance] )
- *
- */
-int main(int argc, char **argv)
-{
- return arm_compute::utils::run_example<GraphDepthwiseConvolutionValidateExample>(argc, argv);
-}
diff --git a/tests/validate_examples/graph_fully_connected.cpp b/tests/validate_examples/graph_fully_connected.cpp
deleted file mode 100644
index 645fa8b..0000000
--- a/tests/validate_examples/graph_fully_connected.cpp
+++ /dev/null
@@ -1,315 +0,0 @@
-/*
- * Copyright (c) 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.
- */
-#include "arm_compute/graph.h"
-
-#include "support/ToolchainSupport.h"
-
-#include "tests/NEON/Accessor.h"
-#include "tests/validation/Validation.h"
-#include "tests/validation/reference/FullyConnectedLayer.h"
-#include "tests/validation/reference/Permute.h"
-
-#include "utils/CommonGraphOptions.h"
-#include "utils/GraphUtils.h"
-#include "utils/Utils.h"
-
-#include "ValidateExample.h"
-#include "graph_validate_utils.h"
-
-#include <utility>
-
-using namespace arm_compute::utils;
-using namespace arm_compute::graph::frontend;
-using namespace arm_compute::graph_utils;
-using namespace arm_compute::graph;
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-/** Fully connected command line options used to configure the graph examples
- *
- * (Similar to common options)
- * The options in this object get populated when "parse()" is called on the parser used to construct it.
- * The expected workflow is:
- *
- * CommandLineParser parser;
- * CommonOptions options( parser );
- * parser.parse(argc, argv);
- */
-class FullyConnectedOptions final : public CommonGraphValidateOptions
-{
-public:
- explicit FullyConnectedOptions(CommandLineParser &parser) noexcept
- : CommonGraphValidateOptions(parser),
- width(parser.add_option<SimpleOption<int>>("width", 3)),
- batch(parser.add_option<SimpleOption<int>>("batch", 1)),
- input_scale(parser.add_option<SimpleOption<float>>("input_scale", 1.0f)),
- input_offset(parser.add_option<SimpleOption<int>>("input_offset", 0)),
- weights_scale(parser.add_option<SimpleOption<float>>("weights_scale", 1.0f)),
- weights_offset(parser.add_option<SimpleOption<int>>("weights_offset", 0)),
- output_scale(parser.add_option<SimpleOption<float>>("output_scale", 1.0f)),
- output_offset(parser.add_option<SimpleOption<int>>("output_offset", 0)),
- num_outputs(parser.add_option<SimpleOption<int>>("num_outputs", 1)),
- input_range_low(parser.add_option<SimpleOption<uint64_t>>("input_range_low")),
- input_range_high(parser.add_option<SimpleOption<uint64_t>>("input_range_high")),
- weights_range_low(parser.add_option<SimpleOption<uint64_t>>("weights_range_low")),
- weights_range_high(parser.add_option<SimpleOption<uint64_t>>("weights_range_high"))
- {
- width->set_help("Set Input dimension width");
- batch->set_help("Set Input dimension batch");
- input_scale->set_help("Quantization scale from QASYMM8");
- input_offset->set_help("Quantization offset from QASYMM8");
- weights_scale->set_help("Quantization scale from QASYMM8");
- weights_offset->set_help("Quantization offset from QASYMM8");
- output_scale->set_help("Quantization scale from QASYMM8");
- output_offset->set_help("Quantization offset from QASYMM8");
- num_outputs->set_help("Number of outputs.");
- input_range_low->set_help("Lower bound for input randomization range");
- input_range_high->set_help("Lower bound for input randomization range");
- weights_range_low->set_help("Lower bound for input randomization range");
- weights_range_high->set_help("Lower bound for input randomization range");
- }
-
- /** Fill out the supplied parameters with user supplied parameters
- *
- * @param[out] os Output stream.
- * @param[in] common_params Example parameters to output
- *
- * @return None.
- */
- void consume_parameters(ExampleParams &common_params)
- {
- common_params.input.width = width->value();
- common_params.input.batch = batch->value();
- common_params.input.quant_info = QuantizationInfo(input_scale->value(), input_offset->value());
- common_params.input.range_low = input_range_low->value();
- common_params.input.range_high = input_range_high->value();
-
- common_params.weights.quant_info = QuantizationInfo(weights_scale->value(), weights_offset->value());
- common_params.weights.range_low = weights_range_low->value();
- common_params.weights.range_high = weights_range_high->value();
-
- common_params.output.quant_info = QuantizationInfo(output_scale->value(), output_offset->value());
-
- common_params.data_type = data_type->value();
- common_params.fully_connected.num_outputs = num_outputs->value();
- }
-
- void print_parameters(::std::ostream &os, const ExampleParams &common_params) override
- {
- os << "Threads : " << common_params.common_params.threads << std::endl;
- os << "Target : " << common_params.common_params.target << std::endl;
- os << "Data type : " << common_params.data_type << std::endl;
- os << "Input dimensions(X,Y, Channels, Batch) : (" << common_params.input.width << "," << common_params.input.height << "," << common_params.input.fm << "," << common_params.input.batch << ")"
- << std::endl;
- os << "Number of outputs : " << common_params.fully_connected.num_outputs << std::endl;
- }
-
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- FullyConnectedOptions(const FullyConnectedOptions &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- FullyConnectedOptions &operator=(const FullyConnectedOptions &) = delete;
- /** Allow instances of this class to be moved */
- FullyConnectedOptions(FullyConnectedOptions &&) noexcept(true) = default;
- /** Allow instances of this class to be moved */
- FullyConnectedOptions &operator=(FullyConnectedOptions &&) noexcept(true) = default;
- /** Default destructor */
- ~FullyConnectedOptions() override = default;
-
-private:
- SimpleOption<int> *width; /**< Input width */
- SimpleOption<int> *batch; /**< Input batch */
- SimpleOption<float> *input_scale; /**< Input Quantization scale from QASSYMM8 */
- SimpleOption<int> *input_offset; /**< Input Quantization offset from QASSYMM8 */
- SimpleOption<float> *weights_scale; /**< Weights Quantization scale from QASSYMM8 */
- SimpleOption<int> *weights_offset; /**< Weights Quantization offset from QASSYMM8 */
- SimpleOption<float> *output_scale; /**< Output Quantization scale from QASSYMM8 */
- SimpleOption<int> *output_offset; /**< Output Quantization offset from QASSYMM8 */
- SimpleOption<int> *num_outputs; /**< Number of outputs. */
- SimpleOption<uint64_t> *input_range_low; /**< Lower bound for input randomization range */
- SimpleOption<uint64_t> *input_range_high; /**< Upper bound for input randomization range */
- SimpleOption<uint64_t> *weights_range_low; /**< Lower bound for weights randomization range */
- SimpleOption<uint64_t> *weights_range_high; /**< Upper bound for weights randomization range */
-};
-
-/** Fully Connected Layer Graph example validation accessor class */
-template <typename D>
-class FullyConnectedVerifyAccessor final : public VerifyAccessor<D>
-{
- using BaseClassType = VerifyAccessor<D>;
- using BaseClassType::BaseClassType;
- using BaseClassType::_params;
- using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type;
-
- // Inherited methods overriden:
- void create_tensors(arm_compute::test::SimpleTensor<D> &src,
- arm_compute::test::SimpleTensor<D> &weights,
- arm_compute::test::SimpleTensor<TBias> &bias,
- ITensor &tensor) override
- {
- // Calculate Tensor shapes for verification
- const TensorShape input_shape = TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch);
- const TensorDescriptor input_descriptor = TensorDescriptor(input_shape, _params.data_type, _params.input.quant_info);
- const TensorDescriptor weights_descriptor = FullyConnectedLayerNode::compute_weights_descriptor(input_descriptor,
- _params.fully_connected.num_outputs,
- _params.fully_connected.info,
- _params.weights.quant_info);
- const TensorDescriptor output_desciptor = FullyConnectedLayerNode::compute_output_descriptor(input_descriptor, _params.fully_connected.num_outputs, _params.output.quant_info);
-
- //Create Input tensors
- src = SimpleTensor<D> { input_descriptor.shape, _params.data_type, 1, input_descriptor.quant_info };
- weights = SimpleTensor<D> { weights_descriptor.shape, _params.data_type, 1, weights_descriptor.quant_info };
- bias = SimpleTensor<TBias> { TensorShape(tensor.info()->tensor_shape().x()), _params.data_type, 1, _params.input.quant_info };
- }
-
- TensorShape output_shape(ITensor &tensor) override
- {
- ARM_COMPUTE_UNUSED(tensor);
-
- const TensorShape input_shape = TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch);
- const TensorDescriptor input_descriptor = TensorDescriptor(input_shape, _params.data_type, _params.input.quant_info);
- const TensorDescriptor output_desciptor = FullyConnectedLayerNode::compute_output_descriptor(input_descriptor, _params.fully_connected.num_outputs, _params.output.quant_info);
-
- return output_desciptor.shape;
- }
-
- arm_compute::test::SimpleTensor<D> reference(arm_compute::test::SimpleTensor<D> &src,
- arm_compute::test::SimpleTensor<D> &weights,
- arm_compute::test::SimpleTensor<TBias> &bias,
- const arm_compute::TensorShape &output_shape) override
- {
- return reference::fully_connected_layer<D>(src, weights, bias, output_shape, _params.output.quant_info);
- }
-
- float relative_tolerance() override
- {
- const std::map<arm_compute::graph::Target, const std::map<DataType, float>> relative_tolerance
- {
- {
- arm_compute::graph::Target::CL,
- { { DataType::F16, 0.2f },
- { DataType::F32, 0.05f },
- { DataType::QASYMM8, 1.0f }
- }
- },
- {
- arm_compute::graph::Target::NEON,
- { { DataType::F16, 0.2f },
- { DataType::F32, 0.01f },
- { DataType::QASYMM8, 1.0f }
- }
- }
- };
-
- return relative_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-
- float absolute_tolerance() override
- {
- const std::map<Target, const std::map<DataType, float>> absolute_tolerance
- {
- {
- Target::CL,
- { { DataType::F16, 0.0f },
- { DataType::F32, 0.0001f },
- { DataType::QASYMM8, 1.0f }
- }
- },
- {
- Target::NEON,
- { { DataType::F16, 0.3f },
- { DataType::F32, 0.1f },
- { DataType::QASYMM8, 1.0f }
- }
- }
- };
-
- return absolute_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-
- float tolerance_number() override
- {
- const std::map<Target, const std::map<DataType, float>> absolute_tolerance
- {
- {
- Target::CL,
- { { DataType::F16, 0.07f },
- { DataType::F32, 0.07f },
- { DataType::QASYMM8, 0.0f }
- }
- },
- {
- Target::NEON,
- { { DataType::F16, 0.07f },
- { DataType::F32, 0.0f },
- { DataType::QASYMM8, 0.0f }
- }
- }
- };
-
- return absolute_tolerance.at(_params.common_params.target).at(_params.data_type);
- }
-};
-
-} // namespace
-
-class GraphFullyConnectedValidateExample final : public GraphValidateExample<FullyConnectedLayer, FullyConnectedOptions, FullyConnectedVerifyAccessor>
-{
- using GraphValidateExample::graph;
-
-public:
- GraphFullyConnectedValidateExample()
- : GraphValidateExample("Fully_connected Graph example")
- {
- }
-
- FullyConnectedLayer GraphFunctionLayer(ExampleParams ¶ms) override
- {
- const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info);
- const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info);
-
- const PixelValue weights_lower = PixelValue(params.weights.range_low, params.data_type, params.weights.quant_info);
- const PixelValue weights_upper = PixelValue(params.weights.range_high, params.data_type, params.weights.quant_info);
-
- return FullyConnectedLayer(params.fully_connected.num_outputs,
- get_random_accessor(weights_lower, weights_upper, 1),
- get_random_accessor(lower, upper, 2),
- params.fully_connected.info, params.weights.quant_info, params.output.quant_info);
- }
-};
-
-/** Main program for Graph fully_connected test
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( Input dimensions [width, batch]
- * Fully connected [num_outputs,type]
- * Verification[tolerance_number,absolute_tolerance,relative_tolerance] )
- *
- */
-int main(int argc, char **argv)
-{
- return arm_compute::utils::run_example<GraphFullyConnectedValidateExample>(argc, argv);
-}
diff --git a/tests/validate_examples/graph_validate_utils.h b/tests/validate_examples/graph_validate_utils.h
deleted file mode 100644
index 13cc4fa..0000000
--- a/tests/validate_examples/graph_validate_utils.h
+++ /dev/null
@@ -1,696 +0,0 @@
-/*
- * Copyright (c) 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 __GRAPH_VALIDATE_UTILS_H__
-#define __GRAPH_VALIDATE_UTILS_H__
-
-#include "arm_compute/graph.h"
-
-#include "ValidateExample.h"
-#include "utils/command_line/CommandLineParser.h"
-
-namespace arm_compute
-{
-namespace utils
-{
-/*Available Padding modes */
-enum class ConvolutionPaddingMode
-{
- Valid,
- Same,
- Manual
-};
-
-/** Stream Input operator for the ConvolutionPaddingMode type
- *
- * @param[in] stream Input stream.
- * @param[out] Mode Convolution parameters to output
- *
- * @return input stream.
- */
-inline ::std::istream &operator>>(::std::istream &stream, ConvolutionPaddingMode &Mode)
-{
- static const std::map<std::string, ConvolutionPaddingMode> modes =
- {
- { "valid", ConvolutionPaddingMode::Valid },
- { "same", ConvolutionPaddingMode::Same },
- { "manual", ConvolutionPaddingMode::Manual }
- };
- std::string value;
- stream >> value;
-#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED
- try
- {
-#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */
- Mode = modes.at(arm_compute::utility::tolower(value));
-#ifndef ARM_COMPUTE_EXCEPTIONS_DISABLED
- }
- catch(const std::out_of_range &)
- {
- throw std::invalid_argument(value);
- }
-#endif /* ARM_COMPUTE_EXCEPTIONS_DISABLED */
-
- return stream;
-}
-
-/** Formatted output of the ConvolutionPaddingMode type
- *
- * @param[out] os Output stream.
- * @param[in] Mode ConvolutionPaddingMode to output
- *
- * @return Modified output stream.
- */
-inline ::std::ostream &operator<<(::std::ostream &os, ConvolutionPaddingMode Mode)
-{
- switch(Mode)
- {
- case ConvolutionPaddingMode::Valid:
- os << "Valid";
- break;
- case ConvolutionPaddingMode::Same:
- os << "Same";
- break;
- case ConvolutionPaddingMode::Manual:
- os << "Manual";
- break;
- default:
- throw std::invalid_argument("Unsupported padding mode format");
- }
-
- return os;
-}
-
-/** Structure holding all the input tensor graph parameters */
-struct TensorParams
-{
- int width{ 1 };
- int height{ 1 };
- int fm{ 1 };
- int batch{ 1 };
- QuantizationInfo quant_info{ 1.0f, 0 };
- std::string npy{};
- uint64_t range_low{ 0 };
- uint64_t range_high{ 16 };
-};
-
-/** Structure holding all the verification graph parameters */
-struct VerificationParams
-{
- float absolute_tolerance{ -1.f };
- float relative_tolerance{ -1.f };
- float tolerance_number{ -1.f };
-};
-
-/** Structure holding all the common graph parameters */
-struct FrameworkParams
-{
- bool help{ false };
- int threads{ 0 };
- arm_compute::graph::Target target{ arm_compute::graph::Target::NEON };
-};
-
-/** Structure holding all the graph Example parameters */
-struct CommonParams
-{
- FrameworkParams common_params{};
- TensorParams input{};
- TensorParams weights{};
- TensorParams bias{};
- TensorParams output{};
- VerificationParams verification{};
- arm_compute::DataType data_type{ DataType::F32 };
-};
-
-/** Structure holding all the Convolution layer graph parameters */
-struct ConvolutionParams
-{
- int depth_multiplier{ 1 };
- /** Padding graph parameters */
- int padding_top{ 0 };
- int padding_bottom{ 0 };
- int padding_left{ 0 };
- int padding_right{ 0 };
- int padding_stride_x{ 0 };
- int padding_stride_y{ 0 };
- ConvolutionPaddingMode padding_mode{ ConvolutionPaddingMode::Valid };
- struct
- {
- struct
- {
- int X{ 0 };
- int Y{ 0 };
- } stride{};
- ConvolutionPaddingMode mode{ ConvolutionPaddingMode::Valid };
- } padding{};
-};
-
-/** Structure holding all the fully_connected layer graph parameters */
-struct FullyConnectedParams
-{
- FullyConnectedLayerInfo info{};
- int num_outputs{ 1 };
-};
-
-/** Structure holding all the graph Example parameters */
-struct ExampleParams : public CommonParams
-{
- FullyConnectedParams fully_connected{};
- ConvolutionParams convolution{};
- arm_compute::graph::DepthwiseConvolutionMethod depth_convolution_method{ arm_compute::graph::DepthwiseConvolutionMethod::Default };
- arm_compute::graph::ConvolutionMethod convolution_method{ arm_compute::graph::ConvolutionMethod::Default };
- arm_compute::DataLayout data_layout{ DataLayout::NCHW };
-};
-
-/** Calculate stride information.
- *
- * Depending on the selected padding mode create the desired PadStrideInfo
- *
- * @param[in] params Convolution parameters supplied by the user.
- *
- * @return PadStrideInfo with the correct padding mode.
- */
-inline PadStrideInfo calculate_convolution_padding(ExampleParams params)
-{
- switch(params.convolution.padding_mode)
- {
- case ConvolutionPaddingMode::Manual:
- {
- return PadStrideInfo(params.convolution.padding_stride_x, params.convolution.padding_stride_y, params.convolution.padding_left, params.convolution.padding_right, params.convolution.padding_top,
- params.convolution.padding_bottom, DimensionRoundingType::FLOOR);
- }
- case ConvolutionPaddingMode::Valid:
- {
- return PadStrideInfo();
- }
- case ConvolutionPaddingMode::Same:
- {
- return arm_compute::calculate_same_pad(TensorShape(params.input.width, params.input.height), TensorShape(params.weights.width, params.weights.height),
- PadStrideInfo(params.convolution.padding_stride_x,
- params.convolution.padding_stride_y));
- }
- default:
- ARM_COMPUTE_ERROR("NOT SUPPORTED!");
- }
-}
-/** CommonGraphValidateOptions command line options used to configure the graph examples
- *
- * (Similar to common options)
- * The options in this object get populated when "parse()" is called on the parser used to construct it.
- * The expected workflow is:
- *
- * CommandLineParser parser;
- * CommonOptions options( parser );
- * parser.parse(argc, argv);
- */
-class CommonGraphValidateOptions
-{
-public:
- explicit CommonGraphValidateOptions(CommandLineParser &parser) noexcept
- : help(parser.add_option<ToggleOption>("help")),
- threads(parser.add_option<SimpleOption<int>>("threads")),
- target(),
- data_type(),
- absolute_tolerance(parser.add_option<SimpleOption<float>>("abs_tolerance", -1.0f)),
- relative_tolerance(parser.add_option<SimpleOption<float>>("rel_tolerance", -1.0f)),
- tolerance_number(parser.add_option<SimpleOption<float>>("tolerance_num", -1.0f))
- {
- const std::set<arm_compute::graph::Target> supported_targets
- {
- arm_compute::graph::Target::NEON,
- arm_compute::graph::Target::CL,
- arm_compute::graph::Target::GC,
- };
-
- const std::set<arm_compute::DataType> supported_data_types
- {
- DataType::F16,
- DataType::F32,
- DataType::QASYMM8,
- };
-
- target = parser.add_option<EnumOption<arm_compute::graph::Target>>("target", supported_targets, arm_compute::graph::Target::NEON);
- data_type = parser.add_option<EnumOption<DataType>>("type", supported_data_types, DataType::F32);
-
- target->set_help("Target to execute on");
- data_type->set_help("Data type to use");
- help->set_help("Show this help message");
- absolute_tolerance->set_help("Absolute tolerance used for verification");
- relative_tolerance->set_help("Absolute tolerance used for verification");
- tolerance_number->set_help("Absolute tolerance used for verification");
- ;
- }
-
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CommonGraphValidateOptions(const CommonGraphValidateOptions &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- CommonGraphValidateOptions &operator=(const CommonGraphValidateOptions &) = delete;
- /** Allow instances of this class to be moved */
- CommonGraphValidateOptions(CommonGraphValidateOptions &&) noexcept(true) = default;
- /** Allow instances of this class to be moved */
- CommonGraphValidateOptions &operator=(CommonGraphValidateOptions &&) noexcept(true) = default;
- /** Default destructor */
- virtual ~CommonGraphValidateOptions() = default;
-
- void consume_common_parameters(CommonParams &common_params)
- {
- common_params.common_params.help = help->is_set() ? help->value() : false;
- common_params.common_params.threads = threads->value();
- common_params.common_params.target = target->value();
-
- common_params.verification.absolute_tolerance = absolute_tolerance->value();
- common_params.verification.relative_tolerance = relative_tolerance->value();
- common_params.verification.tolerance_number = tolerance_number->value();
- }
-
- /** Formatted output of the ExampleParams type
- *
- * @param[out] os Output stream.
- * @param[in] common_params Example parameters to output
- *
- * @return None.
- */
- virtual void print_parameters(::std::ostream &os, const ExampleParams &common_params)
- {
- os << "Threads : " << common_params.common_params.threads << std::endl;
- os << "Target : " << common_params.common_params.target << std::endl;
- os << "Data type : " << common_params.data_type << std::endl;
- }
-
- ToggleOption *help; /**< show help message */
- SimpleOption<int> *threads; /**< Number of threads option */
- EnumOption<arm_compute::graph::Target> *target; /**< Graph execution target */
- EnumOption<arm_compute::DataType> *data_type; /**< Graph data type */
- SimpleOption<float> *absolute_tolerance; /**< Absolute tolerance used in verification */
- SimpleOption<float> *relative_tolerance; /**< Relative tolerance used in verification */
- SimpleOption<float> *tolerance_number; /**< Tolerance number used in verification */
-};
-
-/** Consumes the consume_common_graph_parameters graph options and creates a structure containing any information
- *
- * @param[in] options Options to consume
- * @param[out] common_params params structure to consume.
- *
- * @return consume_common_graph_parameters structure containing the common graph parameters
- */
-void consume_common_graph_parameters(CommonGraphValidateOptions &options, CommonParams &common_params)
-{
- common_params.common_params.help = options.help->is_set() ? options.help->value() : false;
- common_params.common_params.threads = options.threads->value();
- common_params.common_params.target = options.target->value();
-
- common_params.verification.absolute_tolerance = options.absolute_tolerance->value();
- common_params.verification.relative_tolerance = options.relative_tolerance->value();
- common_params.verification.tolerance_number = options.tolerance_number->value();
-}
-
-/** Generates appropriate accessor according to the specified graph parameters
- *
- * @param[in] tensor Tensor parameters
- * @param[in] lower Lower random values bound
- * @param[in] upper Upper random values bound
- * @param[in] seed Random generator seed
- *
- * @return An appropriate tensor accessor
- */
-inline std::unique_ptr<graph::ITensorAccessor> get_accessor(const TensorParams &tensor, PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0)
-{
- if(!tensor.npy.empty())
- {
- return arm_compute::support::cpp14::make_unique<arm_compute::graph_utils::NumPyBinLoader>(tensor.npy);
- }
- else
- {
- return arm_compute::support::cpp14::make_unique<arm_compute::graph_utils::RandomAccessor>(lower, upper, seed);
- }
-}
-
-/** Graph example validation accessor class */
-template <typename D>
-class VerifyAccessor : public graph::ITensorAccessor
-{
-public:
- using TBias = typename std::conditional<std::is_same<typename std::decay<D>::type, uint8_t>::value, int32_t, D>::type;
- /** Constructor
- *
- * @param[in] params Convolution parameters
- */
- explicit VerifyAccessor(ExampleParams ¶ms)
- : _params(std::move(params))
- {
- }
- // Inherited methods overriden:
- bool access_tensor(ITensor &tensor) override
- {
- if(_params.output.npy.empty())
- {
- arm_compute::test::SimpleTensor<D> src;
- arm_compute::test::SimpleTensor<D> weights;
- arm_compute::test::SimpleTensor<TBias> bias;
-
- //Create Input tensors
- create_tensors(src, weights, bias, tensor);
-
- //Fill the tensors with random values
- fill_tensor(src, 0, static_cast<D>(_params.input.range_low), static_cast<D>(_params.input.range_high));
- fill_tensor(weights, 1, static_cast<D>(_params.weights.range_low), static_cast<D>(_params.weights.range_high));
- fill_tensor(bias, 2, static_cast<TBias>(_params.input.range_low), static_cast<TBias>(_params.input.range_high));
-
- arm_compute::test::SimpleTensor<D> output = reference(src, weights, bias, output_shape(tensor));
-
- validate(tensor, output);
- }
- else
- {
- //The user provided a reference file use an npy accessor to validate
- arm_compute::graph_utils::NumPyAccessor(_params.output.npy, tensor.info()->tensor_shape(), tensor.info()->data_type()).access_tensor(tensor);
- }
- return false;
- }
-
- /** Create reference tensors.
- *
- * Validate the given tensor against the reference result.
- *
- * @param[out] src The tensor with the source data.
- * @param[out] weights The tensor with the weigths data.
- * @param[out] bias The tensor with the bias data.
- * @param[in] tensor Tensor result of the actual operation passed into the Accessor.
- *
- * @return None.
- */
- virtual void create_tensors(arm_compute::test::SimpleTensor<D> &src,
- arm_compute::test::SimpleTensor<D> &weights,
- arm_compute::test::SimpleTensor<TBias> &bias,
- ITensor &tensor)
- {
- //Create Input tensors
- src = arm_compute::test::SimpleTensor<D> { TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch), _params.data_type, 1, _params.input.quant_info };
- weights = arm_compute::test::SimpleTensor<D> { TensorShape(_params.weights.width, _params.weights.height, _params.weights.fm), _params.data_type, 1, _params.weights.quant_info };
- bias = arm_compute::test::SimpleTensor<TBias> { TensorShape(_params.input.height), _params.data_type, 1, _params.input.quant_info };
- }
-
- /** Calculate reference output tensor shape.
- *
- * @param[in] tensor Tensor result of the actual operation passed into the Accessor.
- *
- * @return output tensor shape.
- */
- virtual TensorShape output_shape(ITensor &tensor)
- {
- return arm_compute::graph_utils::permute_shape(tensor.info()->tensor_shape(), _params.data_layout, DataLayout::NCHW);
- }
-
- /** Calculate reference tensor.
- *
- * Validate the given tensor against the reference result.
- *
- * @param[in] src The tensor with the source data.
- * @param[in] weights The tensor with the weigths data.
- * @param[in] bias The tensor with the bias data.
- * @param[in] output_shape Shape of the output tensor.
- *
- * @return Tensor with the reference output.
- */
- virtual arm_compute::test::SimpleTensor<D> reference(arm_compute::test::SimpleTensor<D> &src,
- arm_compute::test::SimpleTensor<D> &weights,
- arm_compute::test::SimpleTensor<TBias> &bias,
- const arm_compute::TensorShape &output_shape) = 0;
-
- /** Fill QASYMM tensor with Random values.
- *
- * Validate the given tensor against the reference result.
- *
- * @param[out] tensor The tensor we want to file
- * @param[in] seed seed for the randomization function
- * @param[in] low lower bound for random values
- * @param[in] high upper bound for random values
- *
- * @return None.
- */
- void fill_tensor(arm_compute::test::SimpleTensor<uint8_t> &tensor, std::random_device::result_type seed, uint8_t low, uint8_t high)
- {
- ARM_COMPUTE_ERROR_ON(tensor.data_type() != arm_compute::DataType::QASYMM8);
-
- const UniformQuantizationInfo qinfo = tensor.quantization_info().uniform();
-
- uint8_t qasymm8_low = quantize_qasymm8(low, qinfo);
- uint8_t qasymm8_high = quantize_qasymm8(high, qinfo);
-
- std::mt19937 gen(seed);
- std::uniform_int_distribution<uint8_t> distribution(qasymm8_low, qasymm8_high);
-
- for(int i = 0; i < tensor.num_elements(); ++i)
- {
- tensor[i] = quantize_qasymm8(distribution(gen), qinfo);
- }
- }
- /** Fill S32 tensor with Random values.
- *
- * Validate the given tensor against the reference result.
- *
- * @param[out] tensor The tensor we want to file
- * @param[in] seed seed for the randomization function
- * @param[in] low lower bound for random values
- * @param[in] high upper bound for random values
- *
- * @return None.
- */
- void fill_tensor(arm_compute::test::SimpleTensor<int32_t> &tensor, std::random_device::result_type seed, int32_t low, int32_t high)
- {
- std::mt19937 gen(seed);
- std::uniform_int_distribution<int32_t> distribution(static_cast<int32_t>(low), static_cast<uint32_t>(high));
-
- for(int i = 0; i < tensor.num_elements(); ++i)
- {
- tensor[i] = distribution(gen);
- }
- }
- /** Fill F32 tensor with Random values.
- *
- * Validate the given tensor against the reference result.
- *
- * @param[out] tensor The tensor we want to file
- * @param[in] seed seed for the randomization function
- * @param[in] low lower bound for random values
- * @param[in] high upper bound for random values
- *
- * @return None.
- */
- void fill_tensor(arm_compute::test::SimpleTensor<float> &tensor, std::random_device::result_type seed, float low, float high)
- {
- ARM_COMPUTE_ERROR_ON(tensor.data_type() != arm_compute::DataType::F32);
- std::mt19937 gen(seed);
- std::uniform_real_distribution<float> distribution(low, high);
-
- for(int i = 0; i < tensor.num_elements(); ++i)
- {
- tensor[i] = distribution(gen);
- }
- }
- /** Fill F16 tensor with Random values.
- *
- * Validate the given tensor against the reference result.
- *
- * @param[out] tensor The tensor we want to file
- * @param[in] seed seed for the randomization function
- * @param[in] low lower bound for random values
- * @param[in] high upper bound for random values
- *
- * @return None.
- */
- void fill_tensor(arm_compute::test::SimpleTensor<half> &tensor, std::random_device::result_type seed, half low, half high)
- {
- ARM_COMPUTE_ERROR_ON(tensor.data_type() != arm_compute::DataType::F16);
- std::mt19937 gen(seed);
- std::uniform_real_distribution<float> distribution(static_cast<half>(low), static_cast<half>(high));
-
- for(int i = 0; i < tensor.num_elements(); ++i)
- {
- tensor[i] = static_cast<half>(distribution(gen));
- }
- }
-
- /** Select relative tolerance.
- *
- * Select relative tolerance if not supplied by user.
- *
- * @return Appropriate relative tolerance.
- */
- virtual float relative_tolerance() = 0;
-
- /** Select absolute tolerance.
- *
- * Select absolute tolerance if not supplied by user.
- *
- * @return Appropriate absolute tolerance.
- */
- virtual float absolute_tolerance() = 0;
-
- /** Select tolerance number.
- *
- * Select tolerance number if not supplied by user.
- *
- * @return Appropriate tolerance number.
- */
- virtual float tolerance_number() = 0;
-
- /** Validate the output versus the reference.
- *
- * @param[in] tensor Tensor result of the actual operation passed into the Accessor.
- * @param[in] output Tensor result of the reference implementation.
- *
- * @return None.
- */
- void validate(ITensor &tensor, arm_compute::test::SimpleTensor<D> output)
- {
- float user_relative_tolerance = _params.verification.relative_tolerance;
- float user_absolute_tolerance = _params.verification.absolute_tolerance;
- float user_tolerance_num = _params.verification.tolerance_number;
- /* If no user input was provided override with defaults. */
- if(user_relative_tolerance == -1)
- {
- user_relative_tolerance = relative_tolerance();
- }
-
- if(user_absolute_tolerance == -1)
- {
- user_absolute_tolerance = absolute_tolerance();
- }
-
- if(user_tolerance_num == -1)
- {
- user_tolerance_num = tolerance_number();
- }
-
- const arm_compute::test::validation::RelativeTolerance<float> rel_tolerance(user_relative_tolerance); /**< Relative tolerance */
- const arm_compute::test::validation::AbsoluteTolerance<float> abs_tolerance(user_absolute_tolerance); /**< Absolute tolerance */
- const float tolerance_num(user_tolerance_num); /**< Tolerance number */
-
- arm_compute::test::validation::validate(arm_compute::test::Accessor(tensor), output, rel_tolerance, tolerance_num, abs_tolerance);
- }
-
- ExampleParams _params;
-};
-
-/** Generates appropriate convolution verify accessor
- *
- * @param[in] params User supplied parameters for convolution.
- *
- * @return A convolution verify accessor for the requested datatype.
- */
-template <template <typename D> class VerifyAccessorT>
-inline std::unique_ptr<graph::ITensorAccessor> get_verify_accessor(ExampleParams params)
-{
- switch(params.data_type)
- {
- case DataType::QASYMM8:
- {
- return arm_compute::support::cpp14::make_unique<VerifyAccessorT<uint8_t>>(
- params);
- }
- case DataType::F16:
- {
- return arm_compute::support::cpp14::make_unique<VerifyAccessorT<half>>(
- params);
- }
- case DataType::F32:
- {
- return arm_compute::support::cpp14::make_unique<VerifyAccessorT<float>>(
- params);
- }
- default:
- ARM_COMPUTE_ERROR("NOT SUPPORTED!");
- }
-}
-
-template <typename LayerT, typename OptionsT, template <typename D> class VerifyAccessorT>
-class GraphValidateExample : public ValidateExample
-{
-public:
- GraphValidateExample(std::string name)
- : graph(0, name)
- {
- }
-
- virtual LayerT GraphFunctionLayer(ExampleParams ¶ms) = 0;
-
- bool do_setup(int argc, char **argv) override
- {
- CommandLineParser parser;
-
- OptionsT Options(parser);
-
- parser.parse(argc, argv);
-
- ExampleParams params;
-
- Options.consume_common_parameters(params);
- Options.consume_parameters(params);
-
- if(params.common_params.help)
- {
- parser.print_help(argv[0]);
- return false;
- }
-
- Options.print_parameters(std::cout, params);
- // Create input descriptor
- const TensorShape input_shape = arm_compute::graph_utils::permute_shape(TensorShape(params.input.width, params.input.height, params.input.fm, params.input.batch),
- DataLayout::NCHW, params.data_layout);
- arm_compute::graph::TensorDescriptor input_descriptor = arm_compute::graph::TensorDescriptor(input_shape, params.data_type, params.input.quant_info, params.data_layout);
-
- const PixelValue lower = PixelValue(params.input.range_low, params.data_type, params.input.quant_info);
- const PixelValue upper = PixelValue(params.input.range_high, params.data_type, params.input.quant_info);
-
- graph << params.common_params.target
- << params.convolution_method
- << params.depth_convolution_method
- << arm_compute::graph::frontend::InputLayer(input_descriptor, get_accessor(params.input, lower, upper, 0))
- << GraphFunctionLayer(params)
- << arm_compute::graph::frontend::OutputLayer(get_verify_accessor<VerifyAccessorT>(params));
-
- arm_compute::graph::GraphConfig config;
- config.num_threads = params.common_params.threads;
-
- graph.finalize(params.common_params.target, config);
-
- return true;
- }
-
- void do_run() override
- {
- graph.run();
- }
-
- void do_teardown() override
- {
- }
-
- arm_compute::graph::frontend::Stream graph;
-};
-
-} // graph_validate_utils
-} // arm_compute
-#endif //__GRAPH_VALIDATE_UTILS_H__