code stringlengths 3 6.57k |
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dataReaders.append(InventoryReader(privateDatabaseAccessConfiguration) |
print("The GLAMOS database is available. Glacier objects are read from the database.") |
glacierReader.getGlacierBySgi(focusGlacier) |
glaciers.values() |
dataReader.getData(glacier) |
printLatestOutline(glaciers) |
print("Database not available! Application will terminate.") |
sys.exit(2) |
print(e.message) |
print("Sample script aborted!") |
create_model(self, kernel_regularizer=None, activity_regularizer=None) |
keras.models.Sequential() |
get_data(self) |
np_utils.to_categorical(y_train, NUM_CLASSES) |
np_utils.to_categorical(y_test, NUM_CLASSES) |
return (x_train, y_train) |
create_multi_input_model_from(self, layer1, layer2) |
keras.layers.Input(shape=(DATA_DIM,) |
keras.layers.Input(shape=(DATA_DIM,) |
layer1(input_1) |
layer2(input_2) |
keras.layers.Average() |
keras.models.Model([input_1, input_2], out) |
model.add_loss(keras.backend.mean(out2) |
model.add_loss(math_ops.reduce_sum(input_1) |
regularizers.l1() |
regularizers.l2() |
regularizers.l1_l2() |
test_kernel_regularization(self, regularizer) |
self.get_data() |
self.create_model(kernel_regularizer=regularizer) |
testing_utils.should_run_eagerly() |
testing_utils.should_run_tf_function() |
self.assertEqual(len(model.losses) |
model.fit(x_train, y_train, batch_size=10, epochs=1, verbose=0) |
regularizers.l1() |
regularizers.l2() |
regularizers.l1_l2() |
keras.regularizers.l2(0.) |
test_activity_regularization(self, regularizer) |
self.get_data() |
self.create_model(activity_regularizer=regularizer) |
testing_utils.should_run_eagerly() |
testing_utils.should_run_tf_function() |
self.assertEqual(len(model.losses) |
context.executing_eagerly() |
model.fit(x_train, y_train, batch_size=10, epochs=1, verbose=0) |
test_zero_regularization(self) |
np.ones((10, 10) |
np.ones((10, 3) |
keras.layers.Dense(3, kernel_regularizer=keras.regularizers.l2(0) |
testing_utils.should_run_eagerly() |
testing_utils.should_run_tf_function() |
model.fit(x, y, batch_size=5, epochs=1) |
test_custom_regularizer_saving(self) |
my_regularizer(weights) |
math_ops.reduce_sum(math_ops.abs(weights) |
keras.Input((10,) |
keras.layers.Dense(1, kernel_regularizer=my_regularizer) |
keras.Model(inputs, outputs) |
model.get_config() |
self.assertEqual(model2.layers[1].kernel_regularizer, my_regularizer) |
regularizers.l1() |
regularizers.l2() |
regularizers.l1_l2() |
test_regularization_shared_layer(self, regularizer) |
self.create_multi_input_model_from(dense_layer, dense_layer) |
testing_utils.should_run_eagerly() |
testing_utils.should_run_tf_function() |
self.assertLen(model.losses, 5) |
regularizers.l1() |
regularizers.l2() |
regularizers.l1_l2() |
test_regularization_shared_model(self, regularizer) |
keras.layers.Input(shape=(DATA_DIM,) |
keras.models.Model(input_tensor, dense_layer(input_tensor) |
self.create_multi_input_model_from(dummy_model, dummy_model) |
testing_utils.should_run_eagerly() |
testing_utils.should_run_tf_function() |
self.assertLen(model.losses, 6) |
regularizers.l1() |
regularizers.l2() |
regularizers.l1_l2() |
test_regularization_shared_layer_in_different_models(self, regularizer) |
range(2) |
keras.layers.Input(shape=(DATA_DIM,) |
unshared_dense(shared_dense(input_tensor) |
models.append(keras.models.Model(input_tensor, out) |
testing_utils.should_run_eagerly() |
testing_utils.should_run_tf_function() |
self.assertLen(model.losses, 9) |
test.main() |
sys.path.insert(0, os.path.abspath(os.path.join(os.path.abspath(os.pardir) |
sys.path.insert(0, os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(__file__) |
os.environ.setdefault("DJANGO_SETTINGS_MODULE", 'termsandconditions_demo.settings') |
get_wsgi_application() |
Greeter(helloworld_pb2_grpc.GreeterServicer) |
Greet(self, request, context) |
print('Saying `hello` to %s' % request.name) |
helloworld_pb2.GreetResponse(message='Hello, {}!'.format(request.name) |
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