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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