def test_display_callback(self):
config = hparams_config.get_detection_config('efficientdet-d0')
config.batch_size = 1
config.num_examples_per_epoch = 1
config.model_dir = tempfile.mkdtemp()
sample_image = tf.ones([416, 416, 3])
display_callback = train_lib.DisplayCallback(sample_image)
model = train_lib.EfficientDetNetTrain(config=config)
model.build((1, 512, 512, 3))
display_callback.set_model(model)
display_callback.on_epoch_end(0, {})
def test_display_callback(self):
config = hparams_config.get_detection_config('efficientdet-d0')
config.batch_size = 1
config.num_examples_per_epoch = 1
config.model_dir = tempfile.mkdtemp()
fake_image = tf.ones([512, 512, 3], dtype=tf.uint8)
fake_jpeg = tf.image.encode_jpeg(fake_image)
sample_image = 'ram://fake_image.jpg'
tf.io.write_file(sample_image, fake_jpeg)
display_callback = train_lib.DisplayCallback(sample_image, config.model_dir)
model = train_lib.EfficientDetNetTrain(config=config)
model.build((1, 512, 512, 3))
display_callback.set_model(model)
display_callback.on_epoch_end(0, {})
