def testKerasStyleAddWeight(self):
keras_layer = keras_base_layer.Layer(name="keras_layer")
with backend.name_scope("foo"):
keras_variable = keras_layer.add_weight(
"my_var", [2, 2], initializer=tf.compat.v1.zeros_initializer()
)
self.assertEqual(keras_variable.name, "foo/my_var:0")
with backend.name_scope("baz"):
old_style_layer = base_tf_layers.Layer(name="my_layer")
# Test basic variable creation.
variable = old_style_layer.add_weight(
"my_var", [2, 2], initializer=tf.compat.v1.zeros_initializer()
)
self.assertEqual(variable.name, "my_layer/my_var:0")
with base_tf_layers.keras_style_scope():
layer = base_tf_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_weight(
"my_var", [2, 2], initializer=tf.compat.v1.zeros_initializer()
)
self.assertEqual(variable.name, "bar/my_var:0")
def __init__(self, name=None, enable_histograms=True):
super(CustomModel, self).__init__()
self._my_layers = [
layer_lib.Dense(
4096,
name='dense1',
kernel_initializer=tf.compat.v1.glorot_normal_initializer(seed=0),
use_bias=False),
layer_lib.Dense(
4,
name='dense2',
kernel_initializer=tf.compat.v1.glorot_normal_initializer(seed=0),
use_bias=False),
]
if enable_histograms:
self.histogram_summary_layer = LayerForHistogramSummary()
else:
self.histogram_summary_layer = base_layer.Layer() # no-op pass through
self.scalar_summary_layer = LayerForScalarSummary()
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=tf.compat.v1.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=tf.compat.v1.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=tf.compat.v1.zeros_initializer())
self.assertEqual(variable.name, 'bar/my_var:0')
def test_delete_variable(self):
layer = base_layer.Layer(dtype='mixed_float16')
layer.x = layer.add_weight('x')
self.assertEqual(layer.trainable_weights, [layer.x])
del layer.x
self.assertEqual(layer.trainable_weights, [])