def testAddFinalTrainingOpsQuantized(self, flags_mock):
with tf.Graph().as_default():
with tf.Session() as sess:
bottleneck = tf.placeholder(tf.float32, [1, 1024], name='bottleneck')
# Test creating final training op with quantization
retrain.add_final_training_ops(5, 'final', bottleneck, 1024, True)
self.assertIsNotNone(sess.graph.get_tensor_by_name('final:0'))
def testAddFinalTrainingOps(self):
with tf.Graph().as_default():
with tf.Session() as sess:
tf.placeholder(tf.float32, [1, retrain.BOTTLENECK_TENSOR_SIZE], name=retrain.BOTTLENECK_TENSOR_NAME)
retrain.add_final_training_ops(sess.graph, 5, "final", "gt")
self.assertIsNotNone(sess.graph.get_tensor_by_name("final:0"))
self.assertIsNotNone(sess.graph.get_tensor_by_name("gt:0"))
def testAddFinalTrainingOps(self, flags_mock):
with tf.Graph().as_default():
with tf.Session() as sess:
bottleneck = tf.placeholder(
tf.float32, [1, retrain.BOTTLENECK_TENSOR_SIZE],
name=retrain.BOTTLENECK_TENSOR_NAME.split(':')[0])
retrain.add_final_training_ops(5, 'final', bottleneck)
self.assertIsNotNone(sess.graph.get_tensor_by_name('final:0'))
def testAddFinalTrainingOps(self):
with tf.Graph().as_default():
with tf.Session() as sess:
tf.placeholder(tf.float32, [1, retrain.BOTTLENECK_TENSOR_SIZE],
name=retrain.BOTTLENECK_TENSOR_NAME)
retrain.add_final_training_ops(sess.graph, 5, 'final', 'gt')
self.assertIsNotNone(sess.graph.get_tensor_by_name('final:0'))
self.assertIsNotNone(sess.graph.get_tensor_by_name('gt:0'))
def testAddFinalTrainingOps(self):
with tf.Graph().as_default():
with tf.Session() as sess:
bottleneck = tf.placeholder(
tf.float32, [1, retrain.BOTTLENECK_TENSOR_SIZE],
name=retrain.BOTTLENECK_TENSOR_NAME.split(':')[0])
retrain.add_final_training_ops(5, 'final', bottleneck)
self.assertIsNotNone(sess.graph.get_tensor_by_name('final:0'))
def testAddFinalTrainingOps(self, flags_mock):
with tf.Graph().as_default():
with tf.Session() as sess:
bottleneck = tf.placeholder(
tf.float32, [1, 1024],
name='bottleneck')
retrain.add_final_training_ops(5, 'final', bottleneck, 1024)
self.assertIsNotNone(sess.graph.get_tensor_by_name('final:0'))
