def testKerasStyleAddWeight(self):
keras_layer = keras_base_layer.Layer(name='keras_layer')
with ops.name_scope('foo', skip_on_eager=False):
keras_variable = keras_layer.add_variable(
'my_var', [2, 2], initializer=init_ops.zeros_initializer())
self.assertEqual(keras_variable.name, 'foo/my_var:0')
with ops.name_scope('baz', skip_on_eager=False):
old_style_layer = base_layers.Layer(name='my_layer')
# Test basic variable creation.
variable = old_style_layer.add_variable(
'my_var', [2, 2], initializer=init_ops.zeros_initializer())
self.assertEqual(variable.name, 'my_layer/my_var:0')
with base_layers.keras_style_scope():
layer = base_layers.Layer(name='my_layer')
# Test basic variable creation.
with ops.name_scope('bar', skip_on_eager=False):
variable = layer.add_variable(
'my_var', [2, 2], initializer=init_ops.zeros_initializer())
self.assertEqual(variable.name, 'bar/my_var:0')
def testKerasStyleAddWeight(self):
keras_layer = keras_base_layer.Layer(name='keras_layer')
with backend.name_scope('foo'):
keras_variable = keras_layer.add_variable(
'my_var', [2, 2], initializer=init_ops.zeros_initializer())
self.assertEqual(keras_variable.name, 'foo/my_var:0')
with backend.name_scope('baz'):
old_style_layer = base_layers.Layer(name='my_layer')
# Test basic variable creation.
variable = old_style_layer.add_variable(
'my_var', [2, 2], initializer=init_ops.zeros_initializer())
self.assertEqual(variable.name, 'my_layer/my_var:0')
with base_layers.keras_style_scope():
layer = base_layers.Layer(name='my_layer')
# Assert that the layer was not instrumented as a Keras layer
self.assertFalse(layer._instrumented_keras_api)
# Test basic variable creation.
with backend.name_scope('bar'):
variable = layer.add_variable(
'my_var', [2, 2], initializer=init_ops.zeros_initializer())
self.assertEqual(variable.name, 'bar/my_var:0')
def test_delete_variable(self):
layer = base_layer.Layer(dtype=policy.Policy('mixed_float16'))
layer.x = layer.add_weight('x')
self.assertEqual(layer.trainable_weights, [layer.x])
del layer.x
self.assertEqual(layer.trainable_weights, [])
