def test_layer_database_with_dynamic_shape(self):
""" test layer database creation with different input shapes"""
# create tf.compat.v1.Session and initialize the weights and biases with zeros
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth = True
graph = tf.Graph()
with graph.as_default():
# by default, model will be constructed in default graph
input_placeholder = tf.compat.v1.placeholder(tf.float32, [None, None, None, 3], 'input')
x = tf.keras.layers.Conv2D(8, (2, 2), padding='SAME')(input_placeholder)
x = tf.keras.layers.BatchNormalization(momentum=.3, epsilon=.65)(x)
x = tf.keras.layers.Conv2D(8, (1, 1), padding='SAME', activation=tf.nn.tanh)(x)
x = tf.keras.layers.BatchNormalization(momentum=.4, epsilon=.25)(x)
init = tf.compat.v1.global_variables_initializer()
# create session with graph
sess = tf.compat.v1.Session(graph=graph, config=config)
sess.run(init)
layer_db = LayerDatabase(model=sess, input_shape=(1, 224, 224, 3), working_dir=None, starting_ops=['input'],
ending_ops=['batch_normalization_1/cond/Merge'])
conv1_layer = layer_db.find_layer_by_name('conv2d/Conv2D')
conv2_layer = layer_db.find_layer_by_name('conv2d_1/Conv2D')
self.assertEqual(conv1_layer.output_shape, [1, 8, 224, 224])
self.assertEqual(conv2_layer.output_shape, [1, 8, 224, 224])
layer_db.destroy()
# 2) try with different input shape
# create another session with graph
sess = tf.compat.v1.Session(graph=graph, config=config)
sess.run(init)
batch_size = 32
layer_db = LayerDatabase(model=sess, input_shape=(batch_size, 28, 28, 3), working_dir=None,
starting_ops=['input'], ending_ops=['batch_normalization_1/cond/Merge'])
conv1_layer = layer_db.find_layer_by_name('conv2d/Conv2D')
conv2_layer = layer_db.find_layer_by_name('conv2d_1/Conv2D')
self.assertEqual(conv1_layer.output_shape, [32, 8, 28, 28])
self.assertEqual(conv2_layer.output_shape, [32, 8, 28, 28])
layer_db.destroy()
def test_layer_database_destroy(self):
# create tf.compat.v1.Session and initialize the weights and biases with zeros
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth = True
# create session with graph
sess = tf.compat.v1.Session(graph=tf.Graph(), config=config)
with sess.graph.as_default():
# by default, model will be constructed in default graph
_ = mnist_tf_model.create_model(data_format='channels_last')
init = tf.compat.v1.global_variables_initializer()
sess.run(init)
layer_db = LayerDatabase(model=sess, input_shape=(1, 28, 28, 1), working_dir=None)
layer_db.destroy()
self.assertRaises(RuntimeError, lambda: sess.run(init))
# delete temp directory
shutil.rmtree(str('./temp_meta/'))