How to use _load_data method in lisa

Best Python code snippet using lisa_python

tradefed_test_unittest.py

Source:tradefed_test_unittest.py

...4import common5import os6import unittest7import tradefed_test8def _load_data(filename):9    """Loads the test data of the given file name."""10    with open(os.path.join(os.path.dirname(os.path.realpath(__file__)),11                           'tradefed_test_unittest_data', filename), 'r') as f:12        return f.read()13class TradefedTestTest(unittest.TestCase):14    """Unittest for tradefed_test."""15    def test_parse_tradefed_result(self):16        """Test for parse_tradefed_result."""17        waivers = set([18            'android.app.cts.SystemFeaturesTest#testUsbAccessory',19            'android.widget.cts.GridViewTest#testSetNumColumns',20        ])21        # b/35605415 and b/3652062322        # http://pantheon/storage/browser/chromeos-autotest-results/108103986-chromeos-test/23        # CTS: Tradefed may split a module to multiple chunks.24        # Besides, the module name may not end with "TestCases".25        waived, _ = tradefed_test.parse_tradefed_result(26            _load_data('CtsHostsideNetworkTests.txt'),27            waivers=waivers)28        self.assertEquals(0, len(waived))29        # b/3553039430        # http://pantheon/storage/browser/chromeos-autotest-results/108291418-chromeos-test/31        # Crashed, but the automatic retry by tradefed executed the rest.32        waived, _ = tradefed_test.parse_tradefed_result(33            _load_data('CtsMediaTestCases.txt'),34            waivers=waivers)35        self.assertEquals(0, len(waived))36        # b/3553039437        # http://pantheon/storage/browser/chromeos-autotest-results/106540705-chromeos-test/38        # Crashed in the middle, and the device didn't came back.39        waived, _ = tradefed_test.parse_tradefed_result(40            _load_data('CtsSecurityTestCases.txt'),41            waivers=waivers)42        self.assertEquals(0, len(waived))43        # b/3662918744        # http://pantheon/storage/browser/chromeos-autotest-results/108855595-chromeos-test/45        # Crashed in the middle. Tradefed decided not to continue.46        waived, _ = tradefed_test.parse_tradefed_result(47            _load_data('CtsViewTestCases.txt'),48            waivers=waivers)49        self.assertEquals(0, len(waived))50        # b/3637569051        # http://pantheon/storage/browser/chromeos-autotest-results/109040174-chromeos-test/52        # Mixture of real failures and waivers.53        waived, _ = tradefed_test.parse_tradefed_result(54            _load_data('CtsAppTestCases.txt'),55            waivers=waivers)56        self.assertEquals(1, len(waived))57        # ... and the retry of the above failing iteration.58        waived, _ = tradefed_test.parse_tradefed_result(59            _load_data('CtsAppTestCases-retry.txt'),60            waivers=waivers)61        self.assertEquals(1, len(waived))62        # http://pantheon/storage/browser/chromeos-autotest-results/116875512-chromeos-test/63        # When a test case crashed during teardown, tradefed prints the "fail"64        # message twice. Tolerate it and still return an (inconsistent) count.65        waived, _ = tradefed_test.parse_tradefed_result(66            _load_data('CtsWidgetTestCases.txt'),67            waivers=waivers)68        self.assertEquals(1, len(waived))69        # http://pantheon/storage/browser/chromeos-autotest-results/117914707-chromeos-test/70        # When a test case unrecoverably crashed during teardown, tradefed71        # prints the "fail" and failure summary message twice. Tolerate it.72        waived, _ = tradefed_test.parse_tradefed_result(73            _load_data('CtsPrintTestCases.txt'),74            waivers=waivers)75        self.assertEquals(0, len(waived))76        gts_waivers = set([77            ('com.google.android.placement.gts.CoreGmsAppsTest#' +78                'testCoreGmsAppsPreloaded'),79            ('com.google.android.placement.gts.CoreGmsAppsTest#' +80                'testGoogleDuoPreloaded'),81            'com.google.android.placement.gts.UiPlacementTest#testPlayStore'82        ])83        # crbug.com/74811684        # http://pantheon/storage/browser/chromeos-autotest-results/130080763-chromeos-test/85        # 3 ABIS: x86, x86_64, and armeabi-v7a86        waived, _ = tradefed_test.parse_tradefed_result(87            _load_data('GtsPlacementTestCases.txt'),88            waivers=gts_waivers)89        self.assertEquals(9, len(waived))90        # b/6409570291        # http://pantheon/storage/browser/chromeos-autotest-results/130211812-chromeos-test/92        # The result of the last chunk not reported by tradefed.93        # The actual dEQP log is too big, hence the test data here is trimmed.94        waived, _ = tradefed_test.parse_tradefed_result(95            _load_data('CtsDeqpTestCases-trimmed.txt'),96            waivers=waivers)97        self.assertEquals(0, len(waived))98        # b/8016077299        # http://pantheon/storage/browser/chromeos-autotest-results/201962931-kkanchi/100        # The newer tradefed requires different parsing to count waivers.101        waived, _ = tradefed_test.parse_tradefed_result(102            _load_data('CtsAppTestCases_P_simplified.txt'),103            waivers=waivers)104        self.assertEquals(1, len(waived))105        # b/66899135, tradefed may reported inaccuratly with `list results`.106        # Check if summary section shows that the result is inacurrate.107        _, accurate = tradefed_test.parse_tradefed_result(108            _load_data('CtsAppTestCases_P_simplified.txt'),109            waivers=waivers)110        self.assertTrue(accurate)111        _, accurate = tradefed_test.parse_tradefed_result(112            _load_data('CtsDeqpTestCases-trimmed-inaccurate.txt'),113            waivers=waivers)114        self.assertFalse(accurate)115if __name__ == '__main__':...

Preprocessing.py

Source:Preprocessing.py

...9        self.fd = {"train":TRAINFOLD, "test":TESTFOLD}10        self.fl = {"train":TRAINLIST, "test":TESTLIST}11        self.ft = {"train":TRAINFEATURE, "test":TESTFEATURE}12    13    def _load_data(self, file_path, data_type='original'):14        if data_type == 'original':15            data = pd.read_csv(file_path, sep="\s+").iloc[:,0:WINDOW_WIDTH]16        elif data_type == 'features':17            data = pd.read_csv(file_path, sep="\s+")18        return data19    def _choose_status(self, status="train"):20        if status == "train":21            return self.fd["train"], self.fl["train"], self.ft["train"]22        else:23            return self.fd["test"], self.fl["test"], self.ft["test"]24    25    def _get_one_hot(self, label, N):26        size = list(label.size())27        label = label.view(-1) - 128        ones = torch.sparse.torch.eye(N)29        ones = ones.index_select(0, label)   30        size.append(N) 31        return ones.view(*size)32    33    def _concatenate(self, pair, dataX, dataY, amount, random=True):34        actionA = dataX[np.argwhere(dataY==pair[0])[:,0]]35        actionB = dataX[np.argwhere(dataY==pair[1])[:,0]]36        for n in range(amount):37            temp = actionA38            for i in range(len(actionA)):39                if random:40                    cut = np.random.randint(0, 128)41                else:42                    cut = 6443                selection = np.random.randint(0,len(actionB))44                temp[i,:,cut:]= actionB[selection,:,cut:]45            if n == 0:46                output = temp47            else:48                output = np.concatenate((output,temp), axis=0)49        return len(output), output50    51    def _stack(self, dataX, fl, fd):52        for i in range(1, len(fl)):53            fp = fd + fl[i]54            new = self._load_data(fp)55            if i == 1:56                dataX = np.stack([dataX,new],axis=len(dataX.shape))57            else:58                dataX = np.dstack([dataX,new])59        dataX = np.swapaxes(dataX,1,2)60        return dataX61    62    def original(self, status):63        fd, fl, ft = self._choose_status(status)64        dataX = self._load_data(fd + fl[0])65        dataX = self._stack(dataX, fl, fd)66        dataX = torch.FloatTensor(dataX)67        dataY = torch.LongTensor(np.asarray(self._load_data(ft[1])))68        # dataY = self._get_one_hot(dataY, 6)69        return dataX, dataY70    71    def features(self, status):72        fd, fl, ft = self._choose_status(status)73        dataX = torch.FloatTensor(np.asarray(self._load_data(ft[0], 'features').iloc[:,0:NUM_FEATURES_USED]))74        dataY = torch.LongTensor(np.asarray(self._load_data(ft[1], 'features')))75        return dataX, dataY76    def statistics(self, status):77        fd, fl, ft = self._choose_status(status)78        dataX = np.asarray(self._load_data(ft[0], 'features').iloc[:,0:NUM_FEATURES_USED])79        dataY = np.asarray(self._load_data(ft[1], 'features'))80        return dataX, dataY81    def trans(self, status):82        fd, fl, ft = self._choose_status(status)83        dataX = self._load_data(fd + fl[0])84        dataX = self._stack(dataX, fl, fd)85        dataY = np.asarray(self._load_data(ft[1]).values)86        for i in range(NUM_CLASSES):87            pair = PAIR[i+1]88            num, concatenation = self._concatenate(pair, dataX, dataY, 2, False)89            if i == 0:90                outputX = torch.FloatTensor(concatenation)91                outputY = torch.LongTensor(np.repeat(i+1, num))92            else:93                outputX = torch.cat([outputX, torch.FloatTensor(concatenation)])94                outputY = torch.cat([outputY, torch.LongTensor(np.repeat(i+1, num))])95        return outputX, outputY96if __name__ == "__main__":97    prepare_data = Preprocessing()98    training_data_X, training_data_y = prepare_data.original("train")99    testing_data_X, testing_data_y = prepare_data.original("test")...

data.py

Source:data.py

1import json2import os3def _load_data(filename):4    with open(5        os.path.join(os.path.dirname(__file__), '_data', filename)6    ) as contents:7        if filename.endswith('.json'):8            return json.load(contents)9        return [line.strip() for line in contents.readlines()]10def find_canonical(item, graph, key):11    if item['meta']['canonical']:12        return key, item['names']['en-GB']13    return find_canonical(14        graph[item['edges']['from'][0]],15        graph,16        key,17    )18# Copied from19# https://github.com/alphagov/govuk-country-and-territory-autocomplete20# /blob/b61091a502983fd2a77b3cdb5f94a604412eb09321# /dist/location-autocomplete-graph.json22_graph = _load_data('location-autocomplete-graph.json')23UK = 'United Kingdom'24ENDED_COUNTRIES = _load_data('ended-countries.json')25ADDITIONAL_SYNONYMS = list(_load_data('synonyms.json').items())26WELSH_NAMES = list(_load_data('welsh-names.json').items())27_UK_ISLANDS_LIST = _load_data('uk-islands.txt')28_EUROPEAN_ISLANDS_LIST = _load_data('european-islands.txt')29CURRENT_AND_ENDED_COUNTRIES_AND_TERRITORIES = [30    find_canonical(item, _graph, item['names']['en-GB'])31    for item in _graph.values()32]33COUNTRIES_AND_TERRITORIES = []34for synonym, canonical in CURRENT_AND_ENDED_COUNTRIES_AND_TERRITORIES:35    if canonical in _UK_ISLANDS_LIST:36        COUNTRIES_AND_TERRITORIES.append((synonym, UK))37    elif canonical in ENDED_COUNTRIES:38        succeeding_country = ENDED_COUNTRIES[canonical]39        if succeeding_country:40            COUNTRIES_AND_TERRITORIES.append((synonym, succeeding_country))41            COUNTRIES_AND_TERRITORIES.append((canonical, succeeding_country))42    else:43        COUNTRIES_AND_TERRITORIES.append((synonym, canonical))44UK_ISLANDS = [45    (synonym, UK) for synonym in _UK_ISLANDS_LIST46]47EUROPEAN_ISLANDS = [48    (synonym, synonym) for synonym in _EUROPEAN_ISLANDS_LIST49]50# Copied from https://www.royalmail.com/international-zones#europe51# Modified to use the canonical names for countries where incorrect52ROYAL_MAIL_EUROPEAN = _load_data('europe.txt')53class Postage:54    UK = 'united-kingdom'55    EUROPE = 'europe'...

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