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'))