feature_extrator_dir = os.path.join(temp_dir,
"mnist_feature_extractor")
full_model_dir = os.path.join(temp_dir, "full_model")
self.assertCommandSucceeded("export_mnist_cnn",
fast_test_mode=fast_test_mode,
export_dir=feature_extrator_dir)
use_kwargs = dict(fast_test_mode=fast_test_mode,
input_saved_model_dir=feature_extrator_dir,
retrain=retrain_flag_value,
use_keras_save_api=use_keras_save_api)
if full_model_dir is not None:
use_kwargs["output_saved_model_dir"] = full_model_dir
if named_strategy:
use_kwargs["strategy"] = str(named_strategy)
if regularization_loss_multiplier is not None:
use_kwargs[
"regularization_loss_multiplier"] = regularization_loss_multiplier
self.assertCommandSucceeded("use_mnist_cnn", **use_kwargs)
if full_model_dir is not None:
self.assertCommandSucceeded("deploy_mnist_cnn",
fast_test_mode=fast_test_mode,
saved_model_dir=full_model_dir)
if __name__ == "__main__":
scripts.MaybeRunScriptInstead()
tf.test.main()
"use_text_embedding_in_dataset", model_dir=export_dir)
def test_mnist_cnn(self):
self.skipIfMissingExtraDeps()
export_dir = self.get_temp_dir()
self.assertCommandSucceeded(
"export_mnist_cnn", export_dir=export_dir, fast_test_mode="true")
self.assertCommandSucceeded(
"use_mnist_cnn", export_dir=export_dir, fast_test_mode="true")
def test_mnist_cnn_with_mirrored_strategy(self):
self.skipIfMissingExtraDeps()
self.skipTest(
"b/129134185 - saved model and distribution strategy integration")
export_dir = self.get_temp_dir()
self.assertCommandSucceeded(
"export_mnist_cnn",
export_dir=export_dir,
fast_test_mode="true")
self.assertCommandSucceeded(
"use_mnist_cnn",
export_dir=export_dir,
fast_test_mode="true",
use_mirrored_strategy=True,
)
if __name__ == "__main__":
integration_scripts.MaybeRunScriptInstead()
tf.test.main()
