Initial import
This commit is contained in:
commit
56a50eead3
820 changed files with 192077 additions and 0 deletions
113
extra/hades/scripts/generate_benchmark_tests.py
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113
extra/hades/scripts/generate_benchmark_tests.py
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#+
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# ARES/HADES/BORG Package -- ./extra/hades/scripts/generate_benchmark_tests.py
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# Copyright (C) 2019 Guilhem Lavaux <guilhem.lavaux@iap.fr>
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#
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# Additional contributions from:
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# Guilhem Lavaux <guilhem.lavaux@iap.fr> (2023)
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#
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#+
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import os
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import sys
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output_cmake_file = sys.argv[1]
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input_config = sys.argv[2]
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base_dir = sys.argv[3]
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input_config_path = os.path.dirname(os.path.abspath(input_config))
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with open(input_config, mode="r") as f:
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config = {}
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exec(f.read(), {}, config)
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config = config['tests']
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tests = config['tests']
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with open(output_cmake_file, "wt") as f:
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for test_name in tests:
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test = tests[test_name]
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includes = test['includes']
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likelihood = test['likelihood']
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info_code = test.get('info_code', '')
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downgrade = test.get('downgrade', 1)
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model_code=""
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f.write("""
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add_executable(benchmark_gradient_%(test_name)s %(base_dir)s/%(test_source)s)
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target_link_libraries(benchmark_gradient_%(test_name)s test_library_LSS LSS ${LIBS})
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ares_add_test_targets(benchmark_gradient_%(test_name)s)
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target_include_directories(benchmark_gradient_%(test_name)s PRIVATE %(input_config_path)s)
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"""
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% dict(test_name=test_name, base_dir=base_dir, input_config_path=input_config_path, test_source="benchmark_%s.cpp" % (test_name,)
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))
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includes_str = \
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"\n".join(
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map(lambda x: "#include \"%s\"" % (x,), includes)
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)
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if 'model' in test:
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if type(test['model']) is list:
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model_string = ""
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args = test.get(
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'model_args', ['comm, box,box, 0.001'] + ['comm, box, box, 1']*(len(test['model'])-1))
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extra_code = test.get(
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'model_extra', [""]*len(test['model'])
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)
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extra_code_prev = test.get(
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'model_extra_prev', [""]*len(test['model'])
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)
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for m, a, e, eprev in zip(test['model'], args, extra_code, extra_code_prev):
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model_string += f"""
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{{
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{eprev}
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auto m = std::make_shared<{m}>({a});
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{e}
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chain->addModel(m);
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}}"""
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model_code = f"""
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auto buildModel(LibLSS::MPI_Communication * comm, LibLSS::MarkovState& state, LibLSS::BoxModel box, LibLSS::BoxModel box2) {{
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using namespace LibLSS;
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auto chain = std::make_shared<ChainForwardModel>(comm, box);
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{model_string}
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return chain;
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}}
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"""
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else:
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args = test.get('model_args', 'comm, box, box, 0.001')
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model_code="auto buildModel(LibLSS::MPI_Communication *comm, LibLSS::MarkovState& state, LibLSS::BoxModel const& box, LibLSS::BoxModel box2) { return std::make_shared<%(model)s>(%(model_args)s); }" % dict(model=test['model'],model_args=args )
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if 'data_setup' in test:
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data_setup='#include "%s"\n#define DATA_SETUP %s\n'%(test['data_setup'])
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else:
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data_setup=''
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with open(os.path.join(base_dir,"benchmark_%s.cpp" % (test_name,)), mode="wt") as f2:
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f2.write("""%(includes)s
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#include "libLSS/physics/likelihoods/base.hpp"
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%(data_setup_header)s
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static const int DOWNGRADE_DATA = %(downgrade)d;
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namespace L = LibLSS::Likelihood;
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using LibLSS::LikelihoodInfo;
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auto makeLikelihood(LikelihoodInfo& info) {
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%(additional_info_code)s
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return std::make_shared<%(likelihood)s>(info);
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}
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%(model_code)s
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static constexpr bool RUN_RSD_TEST = false;
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static std::string testName = "%(test_name)s";
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#include "generic_gradient_benchmark.cpp"
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""" % dict(includes=includes_str,data_setup_header=data_setup, additional_info_code=info_code,likelihood=likelihood,model_code=model_code,test_name=test_name,downgrade=downgrade))
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# ARES TAG: authors_num = 1
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# ARES TAG: name(0) = Guilhem Lavaux
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# ARES TAG: email(0) = guilhem.lavaux@iap.fr
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# ARES TAG: year(0) = 2019
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152
extra/hades/scripts/generate_tests_cmake.py
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152
extra/hades/scripts/generate_tests_cmake.py
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# +
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# ARES/HADES/BORG Package -- -- ./scripts/generate_tests_cmake.py
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# Copyright (C) 2019 Guilhem Lavaux <guilhem.lavaux@iap.fr>
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#
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# Additional contributions from:
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# Guilhem Lavaux <guilhem.lavaux@iap.fr> (2019)
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#
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of either the CeCILL license or the GNU General Public
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# license, as included with the software package.
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#
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# The text of the license is located in Licence_CeCILL_V2.1-en.txt
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# and GPL.txt in the root directory of the source package.
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# +
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import os
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import sys
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import filecmp
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output_cmake_file = sys.argv[1]
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input_config = sys.argv[2]
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base_dir = sys.argv[3]
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input_config_path = os.path.dirname(os.path.abspath(input_config))
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with open(input_config, mode="r") as f:
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config = {}
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exec(f.read(), {}, config)
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config = config['tests']
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tests = config['tests']
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with open(output_cmake_file, "wt") as f:
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for test_name in tests:
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test = tests[test_name]
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base_code = test.get("base_code", "generic_gradient_test.cpp")
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includes = test['includes']
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likelihood = test['likelihood']
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info_code = test.get('info_code', '')
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model_code = ""
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f.write("""
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add_executable(test_gradient_%(test_name)s %(base_dir)s/%(test_source)s)
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target_link_libraries(test_gradient_%(test_name)s test_library_LSS LSS ${LIBS})
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ares_add_test_targets(test_gradient_%(test_name)s)
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target_include_directories(test_gradient_%(test_name)s PRIVATE %(input_config_path)s)
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""" % dict(test_name=test_name,
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base_dir=base_dir,
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input_config_path=input_config_path,
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test_source="test_%s_gradient.cpp" % (test_name, )))
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includes_str = \
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"\n".join(
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map(lambda x: "#include \"%s\"" % (x,), includes)
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)
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downgrade = test.get('downgrade', 1)
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if 'model' in test:
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if isinstance(test['model'], list):
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model_string = ""
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args = test.get('model_args', ['comm, box,box, 0.001'] +
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['comm, box, box, 1'] *
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(len(test['model']) - 1))
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extra_code = test.get('model_extra', [""] * len(test['model']))
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extra_code_prev = test.get('model_extra_prev', [""] * len(test['model']))
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for m, a, e, eprev in zip(test['model'], args, extra_code, extra_code_prev):
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model_string += f"""
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{{
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{eprev}
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auto m = std::make_shared<{m}>({a});
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{e}
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chain->addModel(m);
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}}"""
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model_code = f"""
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auto makeModel(LibLSS::MPI_Communication * comm, LibLSS::MarkovState& state, LibLSS::BoxModel box, LibLSS::BoxModel box2) {{
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using namespace LibLSS;
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auto chain = std::make_shared<ChainForwardModel>(comm, box);
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{model_string}
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return chain;
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}}
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"""
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else:
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args = test.get('model_args', 'comm, box, box, 0.001')
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extra_prev = test.get('model_extra_prev', "")
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extra = test.get('model_extra', "")
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model_code = f"""
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auto makeModel(LibLSS::MPI_Communication * comm, LibLSS::MarkovState& state, LibLSS::BoxModel box, LibLSS::BoxModel box2) {{
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using namespace LibLSS;
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{extra_prev}
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auto m = std::make_shared<{test['model']}>({args});
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{extra}
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return m;
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}}
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"""
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else:
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assert 'model_code' in test
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model_code = test['model_code']
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if 'data_setup' in test:
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data_setup = '#include "%s"\n#define DATA_SETUP %s\n' % (
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test['data_setup'])
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else:
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data_setup = ''
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newfile = os.path.join(base_dir,
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"test_%s_gradient.cpp_tmp" % (test_name, ))
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finalfile = os.path.join(base_dir,
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"test_%s_gradient.cpp" % (test_name, ))
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with open(newfile, mode="wt") as f2:
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f2.write("""%(includes)s
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#include "libLSS/samplers/rgen/hmc/hmc_density_sampler.hpp"
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#include "libLSS/physics/likelihoods/base.hpp"
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%(data_setup_header)s
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namespace L = LibLSS::Likelihood;
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using LibLSS::LikelihoodInfo;
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using LibLSS::HMCDensitySampler;
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static const int DOWNGRADE_DATA = %(downgrade)d;
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HMCDensitySampler::Likelihood_t makeLikelihood(LikelihoodInfo& info) {
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%(additional_info_code)s
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return std::make_shared<%(likelihood)s>(info);
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}
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%(model_code)s
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#include "%(base_code)s"
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""" % dict(includes=includes_str,
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data_setup_header=data_setup,
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additional_info_code=info_code,
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likelihood=likelihood,
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model_code=model_code,
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downgrade=downgrade,
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base_code=base_code))
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try:
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os.stat(finalfile)
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if not filecmp.cmp(finalfile, newfile):
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os.rename(newfile, finalfile)
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else:
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os.unlink(newfile)
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except FileNotFoundError:
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os.rename(newfile, finalfile)
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# ARES TAG: authors_num = 1
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# ARES TAG: name(0) = Guilhem Lavaux
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# ARES TAG: email(0) = guilhem.lavaux@iap.fr
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# ARES TAG: year(0) = 2019
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76
extra/hades/scripts/generate_tests_forward_models_cmake.py
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76
extra/hades/scripts/generate_tests_forward_models_cmake.py
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@ -0,0 +1,76 @@
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#+
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# ARES/HADES/BORG Package -- ./extra/hades/scripts/generate_tests_forward_models_cmake.py
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# Copyright (C) 2019 Guilhem Lavaux <guilhem.lavaux@iap.fr>
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# Copyright (C) 2009-2020 Jens Jasche <jens.jasche@fysik.su.se>
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#
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# Additional contributions from:
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# Guilhem Lavaux <guilhem.lavaux@iap.fr> (2023)
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#
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#+
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import os
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import sys
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output_cmake_file = sys.argv[1]
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input_config = sys.argv[2]
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base_dir = sys.argv[3]
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with open(input_config, mode="r") as f:
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config = {}
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exec(f.read(), {}, config)
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config = config['tests']
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if not 'forward_tests' in config:
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sys.exit(1)
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tests = config['forward_tests']
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with open(output_cmake_file, "wt") as f:
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for test_name in tests:
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test = tests[test_name]
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includes = test['includes']
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model = test['model']
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model_args = test.get('model_args', 'comm, box, 0.001');
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model_code=""
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f.write("""
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add_executable(test_forward_%(test_name)s %(base_dir)s/%(test_source)s)
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target_link_libraries(test_forward_%(test_name)s test_library_LSS LSS ${LIBS})
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ares_add_test_targets(test_forward_%(test_name)s)
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"""
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% dict(test_name=test_name, base_dir=base_dir, test_source="test_forward_%s.cpp" % (test_name,)
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))
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includes_str = \
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"\n".join(
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map(lambda x: "#include \"%s\"" % (x,), includes)
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)
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extra_code_prev = test.get('model_extra_prev', "")
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with open(os.path.join(base_dir,"test_forward_%s.cpp" % (test_name,)), mode="wt") as f2:
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f2.write("""%(includes)s
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#include "libLSS/samplers/rgen/hmc/hmc_density_sampler.hpp"
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#include "libLSS/physics/likelihoods/base.hpp"
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#include "libLSS/physics/forward_model.hpp"
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namespace L = LibLSS::Likelihood;
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using LibLSS::LikelihoodInfo;
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using LibLSS::HMCDensitySampler;
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using LibLSS::MarkovState;
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using LibLSS::BoxModel;
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auto makeModel(MarkovState& state, BoxModel const& box, LikelihoodInfo& info) {
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auto comm = L::getMPI(info);
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%(extra_prev)s
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return std::make_shared<%(model)s>(%(model_args)s);
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}
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#include "libLSS/tests/generic_borg_fwd_test.cpp"
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""" % dict(includes=includes_str,model_args=model_args,model=model,extra_prev=extra_code_prev))
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# ARES TAG: num_authors = 1
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# ARES TAG: name(0) = Guilhem Lavaux
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# ARES TAG: email(0) = guilhem.lavaux@iap.fr
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# ARES TAG: year(0) = 2019
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45
extra/hades/scripts/gradient_tests.cmake
Normal file
45
extra/hades/scripts/gradient_tests.cmake
Normal file
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@ -0,0 +1,45 @@
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function(hades_add_forward_test testnames testbase)
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set(_forward_test_cmake ${CMAKE_BINARY_DIR}/CMakeFiles/hades_forward-test_${testnames}.cmake)
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set(_base_tmp_forward_files ${CMAKE_BINARY_DIR}/CMakeFiles/forward_tests)
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if (NOT EXISTS ${_base_tmp_forward_files})
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FILE(MAKE_DIRECTORY ${_base_tmp_forward_files})
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endif()
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execute_process(
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COMMAND ${PYTHON_EXECUTABLE} ${CMAKE_SOURCE_DIR}/extra/hades/scripts/generate_tests_forward_models_cmake.py
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${_forward_test_cmake} ${testbase} ${_base_tmp_forward_files}
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RESULT_VARIABLE _generate_result)
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if (NOT _generate_result EQUAL 0)
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cmessage(FATAL_ERROR "Could not automatically generate gradient tests.")
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endif()
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include(${_forward_test_cmake})
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endfunction()
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function(hades_add_gradient_test testnames testbase)
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set(_gradient_test_cmake ${CMAKE_BINARY_DIR}/CMakeFiles/hades_gradient_test_${testnames}.cmake)
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set(_benchmark_gradient_test_cmake ${CMAKE_BINARY_DIR}/CMakeFiles/hades_gradient_benchmark_test_${testnames}.cmake)
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set(_base_tmp_gradient_files ${CMAKE_BINARY_DIR}/CMakeFiles/gradient_tests)
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if (NOT EXISTS ${_base_tmp_gradient_files})
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FILE(MAKE_DIRECTORY ${_base_tmp_gradient_files})
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endif()
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execute_process(COMMAND ${PYTHON_EXECUTABLE} ${CMAKE_SOURCE_DIR}/extra/hades/scripts/generate_tests_cmake.py
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${_gradient_test_cmake} ${testbase} ${_base_tmp_gradient_files} RESULT_VARIABLE _generate_result)
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if (NOT _generate_result EQUAL 0)
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cmessage(FATAL_ERROR "Could not automatically generate gradient tests.")
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endif()
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execute_process(COMMAND ${PYTHON_EXECUTABLE} ${CMAKE_SOURCE_DIR}/extra/hades/scripts/generate_benchmark_tests.py
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${_benchmark_gradient_test_cmake} ${testbase} ${_base_tmp_gradient_files} RESULT_VARIABLE _generate_result)
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if (NOT _generate_result EQUAL 0)
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cmessage(FATAL_ERROR "Could not automatically generate gradient tests.")
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endif()
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include(${_gradient_test_cmake})
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include(${_benchmark_gradient_test_cmake})
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endfunction()
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14
extra/hades/scripts/models.cmake
Normal file
14
extra/hades/scripts/models.cmake
Normal file
|
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@ -0,0 +1,14 @@
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macro(hades_register_forward_models)
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SET(_ALL_MODELS ${CMAKE_BINARY_DIR}/libLSS/physics/forwards/all_models.hpp)
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get_property(_init GLOBAL PROPERTY HADES_FORWARD_MODEL_INIT)
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if (NOT _init)
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file(WRITE ${_ALL_MODELS} "#pragma once\n")
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set_property(GLOBAL PROPERTY HADES_FORWARD_MODEL_INIT 1)
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endif()
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foreach(model_header ${ARGN})
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cmessage(STATUS "Registering forward model ${model_header}")
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file(APPEND ${_ALL_MODELS} "#include \"${model_header}\"\n")
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endforeach()
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|
||||
endmacro()
|
||||
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