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How to use set_complete method in autotest

Best Python code snippet using autotest_python

test_stake_part.py

Source:test_stake_part.py

...77        key = StakePart.make_key(create_address(1))78        self.assertEqual(ICON_CONTRACT_ADDRESS_BYTES_SIZE + len(StakePart.PREFIX), len(key))79    def test_stake_part_stake(self):80        part = StakePart()81        part.set_complete(True)82        self.assertEqual(0, part.stake)83    def test_stake_part_stake_overflow(self):84        part = StakePart()85        with self.assertRaises(Exception) as e:86            self.assertEqual(0, part.stake)87        self.assertEqual(AssertionError, type(e.exception))88    def test_stake_part_voting_weight(self):89        stake = 1090        part = StakePart(stake=stake)91        part.set_complete(True)92        self.assertEqual(stake, part.voting_weight)93    def test_stake_part_voting_weight_overflow(self):94        part = StakePart()95        with self.assertRaises(Exception) as e:96            self.assertEqual(0, part.voting_weight)97        self.assertEqual(AssertionError, type(e.exception))98    def test_stake_part_unstake(self):99        unstake = 10100        part = StakePart(unstake=unstake)101        part.set_complete(True)102        self.assertEqual(unstake, part.unstake)103    def test_stake_part_unstake_overflow(self):104        part = StakePart()105        with self.assertRaises(Exception) as e:106            self.assertEqual(0, part.unstake)107        self.assertEqual(AssertionError, type(e.exception))108    def test_stake_part_unstake_block_height(self):109        unstake_block_height = 10110        part = StakePart(unstake_block_height=unstake_block_height)111        part.set_complete(True)112        self.assertEqual(unstake_block_height, part.unstake_block_height)113    def test_stake_part_unstake_block_height_overflow(self):114        part = StakePart()115        with self.assertRaises(Exception) as e:116            self.assertEqual(0, part.unstake_block_height)117        self.assertEqual(AssertionError, type(e.exception))118    def test_stake_part_total_stake(self):119        stake = 10120        unstake = 20121        part = StakePart(stake=stake, unstake=unstake)122        part.set_complete(True)123        self.assertEqual(stake+unstake, part.total_stake)124    def test_stake_part_total_stake_overflow(self):125        part = StakePart()126        with self.assertRaises(Exception) as e:127            self.assertEqual(0, part.total_stake)128        self.assertEqual(AssertionError, type(e.exception))129    def test_stake_part_add_stake(self):130        part = StakePart()131        part.set_complete(True)132        stake = 100133        part.add_stake(100)134        self.assertEqual(stake, part.stake)135        self.assertTrue(part.is_set(BasePartState.DIRTY | BasePartState.COMPLETE))136    def test_stake_part_set_unstake_update(self):137        part = StakePart()138        part.set_complete(True)139        stake = 100140        block_height = 10141        part.add_stake(100)142        unstake = stake143        part.set_unstake(block_height, unstake)144        self.assertEqual(0, part.stake)145        self.assertEqual(stake, part.unstake)146        self.assertEqual(block_height, part.unstake_block_height)147        self.assertTrue(part.is_set(BasePartState.DIRTY | BasePartState.COMPLETE))148        block_height += block_height149        unstake = 10150        part.set_unstake(block_height, unstake)151        self.assertEqual(stake - unstake, part.stake)152        self.assertEqual(unstake, part.unstake)...

defs.py

Source:defs.py

1import glob2import numpy as np3import tensorflow as tf4import keras5from numpy.random import default_rng6from keras import backend as K7def get_data(train_path, test_path, train_mean, test_mean):8    beginning = 19    actionTrainFolder = sorted(glob.glob(train_path + "train/*/"))10    for ins_e, ins in enumerate(actionTrainFolder):11        instanceFolder = sorted(glob.glob(ins + "*/"))12        for cla_e, cla in enumerate(instanceFolder):13            classFolder = sorted(glob.glob(cla + "/*.png"))14            for img_e, img in enumerate(classFolder):15                tensor = tf.io.read_file(img)16                print(img)17                tensor = tf.io.decode_image(tensor, dtype=tf.dtypes.uint8)18                tensor = tf.image.convert_image_dtype(tensor, tf.float32)19                if beginning == 1:20                    img_w,img_h,img_d = tensor.shape21                    train_cla_n = len(instanceFolder)22                    train_img_n = len(classFolder)23                    train_set = np.zeros((len(actionTrainFolder) ,len(instanceFolder) ,len(classFolder), img_w, img_h, 1), dtype = 'float32')               24                    beginning = 025                train_set[ins_e,cla_e,img_e,:,:,:] = tensor26    beginning = 127    actionTestFolder = sorted(glob.glob(test_path + "test/*/"))28    for ins_e, ins in enumerate(actionTestFolder):29        instanceFolder = sorted(glob.glob(ins + "*/"))30        for cla_e, cla in enumerate(instanceFolder):31            classFolder = sorted(glob.glob(cla + "/*.png"))32            for img_e, img in enumerate(classFolder):33                tensor = tf.io.read_file(img)34                print(img)35                tensor = tf.io.decode_image(tensor, dtype=tf.dtypes.uint8)36                tensor = tf.image.convert_image_dtype(tensor, tf.float32)37                if beginning == 1:38                    test_cla_n = len(instanceFolder)39                    test_set = np.zeros((len(actionTestFolder) ,len(instanceFolder) ,len(classFolder), img_w, img_h, 1), dtype = 'float32')               40                    beginning = 041                test_set[ins_e,cla_e,img_e,:,:,:] = tensor42    if train_mean == True:43        train_set = np.mean(train_set, axis=(2), keepdims=True)44    if test_mean == True:45        test_set = np.mean(test_set, axis=(2), keepdims=True)46    return img_w, img_h, train_cla_n, test_cla_n, train_img_n, train_set, test_set47def get_r_val(train_path, test_path, train_cla_n, test_cla_n):48    r_train = np.array([])49    r_test = np.array([])50    51    beginning = 152    actionFolder = sorted(glob.glob(train_path + "train/*/"))53    54    for ins_e, ins in enumerate(actionFolder):55        print(ins)56        instanceFolder = sorted(glob.glob(ins + "*.npy"))57        for r_e, r in enumerate(instanceFolder):58            print(r)59            r_act = np.load(r)60            if beginning == 1:61                r_shape = r_act.shape62                r_train = np.zeros((train_cla_n, r_shape[0], r_shape[1], 1))63                r_train[r_e,:,:,:] = r_act64                beginning = 065            else :66                r_train[r_e,:,:,:] = r_act67    68    beginning = 169    actionFolder = sorted(glob.glob(test_path + "test/*/"))70    71    for ins_e, ins in enumerate(actionFolder):72        print(ins)73        instanceFolder = sorted(glob.glob(ins + "*.npy"))74        for r_e, r in enumerate(instanceFolder):75            print(r)76            r_act = np.load(r)77            if beginning == 1:78                r_shape = r_act.shape79                r_test = np.zeros((test_cla_n, r_shape[0], r_shape[1], 1))80                r_test[r_e,:,:,:] = r_act81                beginning = 082            else :83                r_test[r_e,:,:,:] = r_act84    return r_train, r_test85def make_epoch(set_complete):86    ins_e,cla_e,img_e,img_h,img_w,img_d=set_complete.shape87    cla_rand = np.zeros(cla_e)88    img_rand = np.zeros(img_e)89    rng = default_rng()90    91    cla_rand[:] = rng.choice(cla_e, size=cla_e, replace=False)92    img_rand[:] = rng.choice(img_e, size=img_e, replace=False)93    cla_rang = np.tile(cla_rand,img_e)94    img_rang = np.repeat(img_rand, cla_e)95    cla_iter = iter(cla_rang)96    img_iter = iter(img_rang)97    return cla_iter, img_iter , cla_rang, img_rang98def make_batch(set_complete, cla_iter, img_iter, batch_size, r_train, r_max):99    ins_e,cla_e,img_e,img_h,img_w,img_d=set_complete.shape100    r_batch = np.zeros((batch_size,img_h,img_w,img_d),dtype='float32')101    input_batch = np.zeros((batch_size,img_h,img_w,img_d),dtype='float32')102    ground_batch = np.zeros((batch_size,img_h,img_w,img_d),dtype='float32')103    for i in range(batch_size):104        cla_pick = next(cla_iter, None)105        img_pick = next(img_iter, None)106        if cla_pick == None or img_pick == None:107            break108        r_batch[i,:,:,:] = r_train[int(cla_pick), :,:,:]109        input_batch[i,:,:,:] = set_complete[0,int(cla_pick),int(img_pick),:,:,:]        110        ground_batch[i,:,:,:] = set_complete[1,int(cla_pick),int(img_pick),:,:,:]111    input_batch = input_batch * r_batch/r_max112    ground_batch = ground_batch * r_batch/r_max113    return input_batch, ground_batch, r_batch114def custom_loss(r, img_w, img_h, r_max):115    img_w = K.constant(img_w)116    img_h = K.constant(img_h)117    r_max = K.constant(r_max)118    def loss(y_true, y_pred):119        loss_value = K.sum((K.abs(y_pred - y_true)))/(img_w * img_h)120        return loss_value121    return loss122def dist(a, b, IM_SIZE, r_max):123    z_diff = 50 #mm...

admin.py

Source:admin.py

...80        'set_shipped',81        'set_delivered',82    )83    def set_complete_delivered(self, request, queryset):84        self.set_complete(request, queryset)85        self.set_delivered(request, queryset)86    set_complete_delivered.short_description = 'Mark selected orders as complete and delivered today'87    def set_complete(self, request, queryset):88        queryset.update(complete=True)89        self.set_delivered(request, queryset)90    set_complete.short_description = 'Mark selected orders as complete'91    def set_incomplete(self, request, queryset):92        queryset.update(complete=False)93    set_incomplete.short_description = 'Mark selected orders as incomplete'94    def set_shipped(self, request, queryset):95        queryset.filter(shipping_date=None).update(shipping_date=date.today())96    set_shipped.short_description = 'Mark selected orders as shipped today'97    def set_delivered(self, request, queryset):98        queryset.filter(delivery_date=None).update(delivery_date=date.today())99    set_delivered.short_description = 'Mark selected orders as delivered today'100    def make_state_action(self, state):101        name   = 'set_state_{0}'.format(state.state)...

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