def test_efficientnet_b0_fails_if_both_features_requested(self):
with self.assertRaises(AssertionError):
efficientnet_builder.build_model(None,
model_name='efficientnet-b0',
training=False,
features_only=True,
pooled_features_only=True)
def _test_model_params(self,
model_name,
input_size,
expected_params,
override_params=None,
features_only=False,
pooled_features_only=False):
images = tf.zeros((1, input_size, input_size, 3), dtype=tf.float32)
efficientnet_builder.build_model(
images,
model_name=model_name,
override_params=override_params,
training=True,
features_only=features_only,
pooled_features_only=pooled_features_only)
num_params = np.sum([np.prod(v.shape) for v in tf.trainable_variables()])
self.assertEqual(num_params, expected_params)
