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, {})