Ejemplo n.º 1
0
def test_bad_simd_specification_in_codegen():
    with NamedTemporaryFile('w', suffix='.yaml') as file:
        file.write(
            remove_common_indentation("""
        platform:
            name: portable
            lang: opencl
            # deep vectorization
            depth: 4
            is_simd: True
        """))
        file.seek(0)

        with assert_raises(ValidationError):
            build_and_validate('codegen_platform.yaml', file.name)
Ejemplo n.º 2
0
 def setUp(self):
     lp.set_caching_enabled(False)
     if not self.is_setup:
         utils.setup_logging()
         # load equations
         self.dirpath = os.path.dirname(os.path.realpath(__file__))
         gasname = os.path.join(self.dirpath, 'test.cti')
         # first check test config
         gasname = get_mechanism_file()
         # load the gas
         gas = ct.Solution(gasname)
         # the mechanism
         elems, specs, reacs = read_mech_ct(gasname)
         # and finally check for a test platform
         platform = get_platform_file()
         try:
             if platform is None:
                 platform = ''
                 raise OSError
             platform = build_and_validate('test_platform_schema.yaml',
                                           platform)
         except (OSError, IOError):
             logger = logging.getLogger(__name__)
             logger.warn('Test platform file {} was not found, reverting '
                         'to default.'.format(platform))
             platform = None
         self.store = storage(platform, gas, specs, reacs)
         self.is_setup = True
Ejemplo n.º 3
0
def load_memory_limits(input_file, schema='common_schema.yaml'):
    """
    Conviencence method for loading inputs from memory limits file

    Parameters
    ----------
    input_file:
        The input file to load
    """
    def __limitfy(limits):
        # note: this is only safe because we've already validated.
        # hence, NO ERRORS!
        if limits:
            return {
                k: parse_bytestr(object, v) if not k == 'platforms' else v
                for k, v in six.iteritems(limits)
            }

    if input_file:
        try:
            memory_limits = build_and_validate('common_schema.yaml',
                                               input_file,
                                               allow_unknown=True)
            return [__limitfy(memory_limits['memory-limits'])]
        except ValidationError:
            # TODO: fix this -- need a much better way of specifying / passing in
            # limits
            memory_limits = build_and_validate('test_matrix_schema.yaml',
                                               input_file,
                                               allow_unknown=True)
            return [__limitfy(x) for x in memory_limits['memory-limits']]
        except KeyError:
            # no limits
            pass

    return {}
Ejemplo n.º 4
0
    def setUp(self):
        lp.set_caching_enabled(False)
        if not self.is_setup:
            utils.setup_logging()
            # first check test config
            gasname = get_mechanism_file()
            # load the gas
            gas = ct.Solution(gasname)
            # the mechanism
            elems, specs, reacs = read_mech_ct(gasname)
            # get sort type
            sorting = get_rxn_sorting()
            if sorting != reaction_sorting.none:
                # get ordering
                ordering = sort_reactions(reacs, sorting, return_order=True)
                # and apply
                reacs = sort_reactions(reacs, sorting)
                ct_reacs = gas.reactions()
                # and apply to gas
                gas = ct.Solution(thermo='IdealGas',
                                  kinetics='GasKinetics',
                                  species=gas.species(),
                                  reactions=[ct_reacs[i] for i in ordering])

            # and reassign
            utils.reassign_species_lists(reacs, specs)
            # and finally check for a test platform
            platform = get_platform_file()
            try:
                if platform is None:
                    platform = ''
                    raise OSError
                platform = build_and_validate('test_platform_schema.yaml',
                                              platform)
            except (OSError, IOError):
                logger = logging.getLogger(__name__)
                logger.warn('Test platform file {} was not found, reverting '
                            'to default.'.format(platform))
                platform = None
            self.store = storage(platform, gas, specs, reacs)
            self.is_setup = True
Ejemplo n.º 5
0
def load_platform(codegen):
    """
    Loads a code-generation platform from a file, and returns the corresponding
    :class:`loopy_options`

    Parameters
    ----------
    codegen: str
        The user-specified code-generation platform yaml file

    Returns
    -------
    :class:`loopy_options`
        The loaded platform

    Raises
    ------
    :class:`cerberus.ValidationError`: A validation error if the supplied codegen
        platform doesn't comply with the :doc:`../schemas/codegen_platform.yaml`
    """

    platform = build_and_validate('codegen_platform.yaml', codegen)['platform']
    width = platform['vectype'] == 'wide'
    depth = platform['vectype'] == 'deep'
    if width:
        width = platform['vecsize']
    elif depth:
        depth = platform['vecsize']
    # TODO: implement memory limits loading here
    # optional params get passed as kwargs
    kwargs = {}
    if 'order' in platform and platform['order'] is not None:
        kwargs['order'] = platform['order']
    if 'atomics' in platform:
        kwargs['use_atomics'] = platform['atomics']
    return loopy_options(width=width,
                         depth=depth,
                         lang=platform['lang'],
                         platform=platform['name'],
                         **kwargs)
Ejemplo n.º 6
0
 def _internal(source, schema, includes):
     # make schema
     built = build_and_validate(schema, source, includes=includes)
     assert built is not None
     return built
Ejemplo n.º 7
0
def test_override():
    # test the base override schema
    with NamedTemporaryFile(mode='w', suffix='.yaml') as file:
        file.write(
            remove_common_indentation("""
            override:
                num_cores: [1]
                order: ['F']
                gpuorder: ['C']
                conp: ['conp']
                width: [2, 4]
                gpuwidth: [128]
                models: ['C2H4']
            """))
        file.flush()
        file.seek(0)
        data = build_and_validate('common_schema.yaml', file.name)['override']
    assert data['num_cores'] == [1]
    assert data['order'] == ['F']
    assert data['gpuorder'] == ['C']
    assert data['conp'] == ['conp']
    assert data['width'] == [2, 4]
    assert data['gpuwidth'] == [128]
    assert data['models'] == ['C2H4']

    # now test embedded overrides
    with NamedTemporaryFile(mode='w', suffix='.yaml') as file:
        file.write(
            remove_common_indentation("""
            model-list:
              - name: CH4
                mech: gri30.cti
                path:
            platform-list:
              - lang: c
                name: openmp
            test-list:
              - test-type: performance
                # limit to intel
                platforms: [intel]
                eval-type: jacobian
                exact:
                    both:
                        num_cores: [1]
                        order: [F]
                        gpuorder: [C]
                        conp: [conp]
                        depth: [2, 4]
                        gpudepth: [128]
                        models: [C2H4]
            """))
        file.flush()
        file.seek(0)
        data = build_and_validate('test_matrix_schema.yaml',
                                  file.name,
                                  update=True)

    data = data['test-list'][0]['exact']['both']
    assert data['num_cores'] == [1]
    assert data['order'] == ['F']
    assert data['gpuorder'] == ['C']
    assert data['conp'] == ['conp']
    assert data['depth'] == [2, 4]
    assert data['gpudepth'] == [128]
    assert data['models'] == ['C2H4']
Ejemplo n.º 8
0
def test_duplicate_tests_fails():
    with NamedTemporaryFile('w', suffix='.yaml') as file:
        file.write(
            remove_common_indentation("""
        model-list:
          - name: CH4
            path:
            mech: gri30.cti
        platform-list:
          - name: openmp
            lang: c
        test-list:
          - test-type: performance
            eval-type: jacobian
          - test-type: performance
            eval-type: both
        """))
        file.seek(0)

        with assert_raises(DuplicateTestException):
            tests = build_and_validate('test_matrix_schema.yaml', file.name)
            load_tests(tests, file.name)

    with NamedTemporaryFile('w', suffix='.yaml') as file:
        file.write(
            remove_common_indentation("""
        model-list:
          - name: CH4
            path:
            mech: gri30.cti
        platform-list:
          - name: openmp
            lang: c
        test-list:
          - test-type: performance
            eval-type: jacobian
            exact:
                sparse:
                    num_cores: [1]
                full:
                    num_cores: [1]
        """))
        file.seek(0)

        tests = build_and_validate('test_matrix_schema.yaml', file.name)
        load_tests(tests, file.name)

    with NamedTemporaryFile('w', suffix='.yaml') as file:
        file.write(
            remove_common_indentation("""
        model-list:
          - name: CH4
            path:
            mech: gri30.cti
        platform-list:
          - name: openmp
            lang: c
        test-list:
          - test-type: performance
            eval-type: jacobian
            exact:
                both:
                    num_cores: [1]
                full:
                    num_cores: [1]
        """))
        file.seek(0)

        with assert_raises(OverrideCollisionException):
            tests = build_and_validate('test_matrix_schema.yaml', file.name)
            load_tests(tests, file.name)
Ejemplo n.º 9
0
def __get_test_matrix(**kwargs):
    return build_and_validate('test_matrix_schema.yaml',
                              __prefixify('test_matrix.yaml', examples_dir),
                              **kwargs)
Ejemplo n.º 10
0
def get_test_matrix(work_dir,
                    test_type,
                    test_matrix,
                    for_validation,
                    raise_on_missing=True,
                    langs=get_test_langs()):
    """Runs a set of mechanisms and an ordered dictionary for
    performance and functional testing

    Parameters
    ----------
    work_dir : str
        Working directory with mechanisms and for data
    test_type: :class:`build_type.jacobian`
        Controls some testing options (e.g., whether to do a sparse matrix or not)
    test_matrix: str
        The test matrix file to load
    for_validation: bool
        If determines which test type to load from the test matrix,
        validation or performance
    raise_on_missing: bool
        Raise an exception of the specified :param:`test_matrix` file is not found
    langs: list of str
        The allowed languages, modifiable by the :envvar:`TEST_LANGS` or test_langs
        in :file:`test_setup.py`
    Returns
    -------
    mechanisms : dict
        A dictionary indicating which mechanism are available for testing,
        The structure is as follows:
            mech_name : {'mech' : file path to the Cantera mechanism
                         'ns' : number of species in the mechanism
                         'limits' : {'full': XXX, 'sparse': XXX}}: a dictionary of
                            limits on the number of conditions that can be evaluated
                            for this mechanism (full & sparse jacobian respectively)
                            due to memory constraints
    params  : OrderedDict
        The parameters to put in an oploop
    max_vec_width : int
        The maximum vector width to test

    """
    work_dir = abspath(work_dir)

    # validate the test matrix
    matrix_name = test_matrix
    test_matrix = build_and_validate('test_matrix_schema.yaml', test_matrix)

    # check that we have the working directory
    if not exists(work_dir):
        raise Exception('Work directory {} for '.format(work_dir) +
                        'testing not found, exiting...')

    # load the models
    models = load_models(work_dir, test_matrix)
    assert isinstance(test_type, build_type)

    # load tests
    tests = load_tests(test_matrix, matrix_name)
    # filter those that match the test type
    valid_str = 'validation' if for_validation else 'performance'
    tests = [test for test in tests if test['test-type'] == valid_str]
    tests = [
        test for test in tests
        if test['eval-type'] == enum_to_string(test_type)
        or test['eval-type'] == 'both'
    ]
    # and dictify
    tests = [OrderedDict(test) for test in tests]
    if not tests:
        raise Exception('No tests found in matrix {} for {} test of {}, '
                        'exiting...'.format(matrix_name, valid_str,
                                            enum_to_string(test_type)))

    # get defaults we haven't migrated to schema yet
    rate_spec = ['fixed', 'hybrid'] if test_type != build_type.jacobian \
        else ['fixed']
    sparse = ([
        enum_to_string(JacobianFormat.sparse),
        enum_to_string(JacobianFormat.full)
    ] if test_type == build_type.jacobian else
              [enum_to_string(JacobianFormat.full)])
    jac_types = [
        enum_to_string(JacobianType.exact),
        enum_to_string(JacobianType.finite_difference)
    ] if (test_type == build_type.jacobian
          and not for_validation) else [enum_to_string(JacobianType.exact)]
    split_kernels = [False]

    # and default # of cores, this may be overriden
    default_num_cores, can_override_cores = num_cores_default()

    # load platforms
    platforms = load_platforms(test_matrix,
                               langs=langs,
                               raise_on_empty=raise_on_missing)
    platforms = [OrderedDict(platform) for platform in platforms]
    out_params = []
    logger = logging.getLogger(__name__)
    for test in tests:
        # filter platforms
        plats = [p.copy() for p in platforms]
        if 'platforms' in test:
            plats = [
                plat for plat in plats if plat['platform'] in test['platforms']
            ]
            if len(plats) < len(platforms):
                logger.info(
                    'Platforms ({}) filtered out for test type: {}'.format(
                        ', '.join([
                            p['platform'] for p in platforms if p not in plats
                        ]), ' - '.join([test['test-type'],
                                        test['eval-type']])))
        if not len(plats):
            logger.warn('No platforms found for test {}, skipping...'.format(
                ' - '.join([test['test-type'], test['eval-type']])))
            continue

        for plookup in plats:
            clean = plookup.copy()
            # get default number of cores
            cores = default_num_cores[:]
            # get default vector widths
            widths = plookup['width']
            is_wide = widths is not None
            depths = plookup['depth']
            is_deep = depths is not None
            if is_deep and not is_wide:
                widths = depths[:]
            # sanity check
            if is_wide or is_deep:
                assert widths is not None
            # special gpu handling for cores
            is_gpu = False
            # test platform type
            if platform_is_gpu(plookup['platform']):
                # set cores to 1
                is_gpu = True
                cores = [1]

            def apply_vectypes(lookup,
                               widths,
                               is_wide=is_wide,
                               is_deep=is_deep):
                if is_wide or is_deep:
                    # set vec widths
                    use_par = None in widths or (is_wide and is_deep)
                    lookup['vecsize'] = [x for x in widths[:] if x is not None]
                    base = [True] if not use_par else [True, False]
                    if is_wide:
                        lookup['wide'] = base[:]
                        base.pop()
                    if is_deep:
                        lookup['deep'] = base[:]
                else:
                    lookup['vecsize'] = [None]
                    lookup['wide'] = [False]
                    lookup['deep'] = [False]
                del lookup['width']
                del lookup['depth']

            apply_vectypes(plookup, widths)

            # default is both conp / conv
            conp = [True, False]
            order = ['C', 'F']

            # loop over possible overrides
            oploop = OptionLoop(
                OrderedDict([('ttype', [enum_to_string(test_type)]),
                             ('jtype', jac_types), ('stype', sparse)]))
            for i, state in enumerate(oploop):
                ttype = state['ttype']
                jtype = state['jtype']
                stype = state['stype']

                def override_log(key, old, new):
                    logging.info(
                        'Replacing {} for test type: {}. Old value:'
                        ' ({}), New value: ({})'.format(
                            key,
                            stringify_args(
                                [ttype, test['eval-type'], jtype, stype],
                                joiner='.'), stringify_args(listify(old)),
                            stringify_args(listify(new))))

                # copy defaults
                icores = cores[:]
                iorder = order[:]
                iconp = conp[:]
                ivecsizes = widths[:] if widths is not None else [None]
                imodels = tuple(models.keys())
                # load overides
                overrides = get_overrides(test, ttype, jtype, stype)

                # check that we can apply
                if 'num_cores' in overrides and not can_override_cores:
                    raise InvalidTestEnivironmentException(
                        ttype, 'num_cores', matrix_name, 'num_threads')
                elif 'num_cores' in overrides and is_gpu:
                    logger = logging.getLogger(__name__)
                    logger.info(
                        'Discarding unused "num_cores" override for GPU '
                        'platform {}'.format(plookup['platform']))
                    del overrides['num_cores']

                # 'num_cores', 'order', 'conp', 'vecsize', 'vectype'
                # now apply overrides
                outplat = plookup.copy()
                for current in overrides:
                    ivectypes_override = None
                    for override in overrides:
                        if override == 'num_cores':
                            override_log('num_cores', icores,
                                         overrides[override])
                            icores = overrides[override]
                        elif override == 'order' and not is_gpu:
                            override_log('order', iorder, overrides[override])
                            iorder = overrides[override]
                        elif override == 'gpuorder' and is_gpu:
                            override_log('order', iorder, overrides[override])
                            iorder = overrides[override]
                        elif override == 'conp':
                            iconp_save = iconp[:]
                            iconp = []
                            if 'conp' in overrides[override]:
                                iconp.append(True)
                            if 'conv' in overrides[override]:
                                iconp.append(False)
                            override_log('conp', iconp_save, iconp)
                        elif override == 'vecsize' and not is_gpu:
                            override_log('vecsize', ivecsizes,
                                         overrides[override])
                            outplat['vecsize'] = listify(overrides[override])
                        elif override == 'gpuvecsize' and is_gpu:
                            override_log('gpuvecsize', ivecsizes,
                                         overrides[override])
                            outplat['vecsize'] = listify(overrides[override])
                        elif override == 'vectype' and not is_gpu:
                            # we have to do this at the end
                            ivectypes_override = overrides[override]
                        elif override == 'gpuvectype' and is_gpu:
                            ivectypes_override = overrides[override]
                        elif override == 'models':
                            # check that all models are valid
                            for model in overrides[override]:
                                if model not in imodels:
                                    raise InvalidOverrideException(
                                        override, model, imodels)
                            # and replace
                            override_log('models', stringify_args(imodels),
                                         stringify_args(overrides[override]))
                            imodels = tuple(overrides[override])

                    if ivectypes_override is not None:
                        c = clean.copy()
                        apply_vectypes(c,
                                       outplat['vecsize'],
                                       is_wide='wide' in ivectypes_override,
                                       is_deep='deep' in ivectypes_override)
                        # and copy into working
                        outplat['wide'] = c['wide'] if 'wide' in c else [False]
                        outplat['deep'] = c['deep'] if 'deep' in c else [False]
                        outplat['vecsize'] = c['vecsize']
                        old = ['']
                        if is_wide:
                            old += ['wide']
                        if is_deep:
                            old += ['deep']
                        elif not is_wide:
                            old += ['par']
                        override_log('vecsize', old, ivectypes_override)

                # and finally, convert back to an option loop format
                out_params.append(
                    [('num_cores', icores), ('order',
                                             iorder), ('rate_spec', rate_spec),
                     ('split_kernels', split_kernels), ('conp', iconp),
                     ('sparse', [stype]), ('jac_type',
                                           [jtype]), ('models', [imodels])] +
                    [(key, value) for key, value in six.iteritems(outplat)])

    max_vec_width = 1
    vector_params = [
        dict(p)['vecsize'] for p in out_params
        if 'vecsize' in dict(p) and dict(p)['vecsize'] != [None]
    ]
    if vector_params:
        max_vec_width = max(max_vec_width,
                            max([max(x) for x in vector_params]))
    from . import reduce_oploop
    loop = reduce_oploop(out_params)
    return models, loop, max_vec_width