How to use import_package method in lisa

Best Python code snippet using lisa_python

dl_layers_test.py

Source:dl_layers_test.py

...3import numpy as np4from hyperts.tests import skip_if_not_tf5@skip_if_not_tf6class Test_DL_Layers():7    def import_package(self):8        import tensorflow as tf9        from hyperts.framework.dl import layers10        return tf, layers11    def test_multicolembedding_layers(self):12        tf, layers = self.import_package()13        data = np.random.randint(100, size=(4, 3, 2))14        model = tf.keras.Sequential()15        model.add(layers.MultiColEmbedding(input_dims=[100, 100], output_dims=[4, 4]))16        output = model.predict(data)17        assert output.shape == (4, 3, 8)18    def test_weightedattention_layers(self):19        tf, layers = self.import_package()20        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2421        output = layers.WeightedAttention(timesteps=3)(data)22        assert output.shape == (4, 3, 2)23    def test_feedforwardattention_layers(self):24        tf, layers = self.import_package()25        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2426        output1 = layers.FeedForwardAttention(return_sequences=True)(data)27        output2 = layers.FeedForwardAttention(return_sequences=False)(data)28        assert output1.shape == (4, 3, 2)29        assert output2.shape == (4, 2)30    def test_autoregressive_layers(self):31        tf, layers = self.import_package()32        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2433        output = layers.AutoRegressive(order=1, nb_variables=2)(data)34        assert output.shape == (4, 2)35    def test_highway_layers(self):36        tf, layers = self.import_package()37        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2438        output = layers.Highway(nb_variables=2)(data)39        assert output.shape == (4, 2)40    def test_time2vec_layers(self):41        tf, layers = self.import_package()42        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2443        output = layers.Time2Vec(kernel_size=2)(data)44        assert output.shape == (4, 3, 4)45    def test_revin_layers(self):46        tf, layers = self.import_package()47        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2448        revin = layers.RevInstanceNormalization()49        output1 = revin(data, mode='norm')50        output2 = revin(output1, mode='denorm')51        assert output1.shape == (4, 3, 2)52        assert output2.shape == (4, 3, 2)53    def test_identify_layers(self):54        tf, layers = self.import_package()55        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2456        output = layers.Identity()(data)57        assert output.shape == (4, 3, 2)58    def test_shortcut_layers(self):59        tf, layers = self.import_package()60        data = tf.reshape(tf.range(0, 24), shape=(4, 3, 2)) / 2461        output = layers.Shortcut(filters=8)(data)62        assert output.shape == (4, 3, 8)63    def test_inceptionblock(self):64        tf, layers = self.import_package()65        data = tf.random.normal(shape=(4, 8, 2))66        kernel_size_list = (1, 2, 3, 5, 12)67        kernel_size_list = list(filter(lambda x: x < 8, kernel_size_list))68        output = layers.InceptionBlock(filters=8,69                                       kernel_size_list=kernel_size_list,70                                       bottleneck_size=8)(data)...

conditional_functions.py

Source:conditional_functions.py

1"""Java function implementations for conditional opperations."""2from ..java_function import ExistingJavaFunction3ATOTI_OPERATOR_PACKAGE = "io.atoti.udaf.operators"4EQ_FUNCTION = ExistingJavaFunction(5    "ConditionalOperator.eq",6    import_package=ATOTI_OPERATOR_PACKAGE,7)8NEQ_FUNCTION = ExistingJavaFunction(9    "ConditionalOperator.neq",10    import_package=ATOTI_OPERATOR_PACKAGE,11)12GT_FUNCTION = ExistingJavaFunction(13    "ConditionalOperator.gt",14    import_package=ATOTI_OPERATOR_PACKAGE,15)16GTE_FUNCTION = ExistingJavaFunction(17    "ConditionalOperator.gte",18    import_package=ATOTI_OPERATOR_PACKAGE,19)20LT_FUNCTION = ExistingJavaFunction(21    "ConditionalOperator.lt",22    import_package=ATOTI_OPERATOR_PACKAGE,23)24LTE_FUNCTION = ExistingJavaFunction(25    "ConditionalOperator.lte",26    import_package=ATOTI_OPERATOR_PACKAGE,...

import.py

Source:import.py

1import import_package.bar2import import_package.foo3import import_package.baz as baz_alias4from import_package.qux import Qux5from import_package.quux import Quux as Xuuq6from import_package import sub_package7baz_alias ## type baz8import_package ## type import_package9sub_package ## type sub_package10import_package.foo ## type foo11import_package.bar ## type bar12x1 = baz_alias13x2 = import_package.bar14x1 ## type baz15x2 ## type bar16x = baz_alias.Baz()17x ## type Baz18print x.path()19q = Qux()20q ## type Qux21aq = Xuuq()...

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