def test_xception_get_config_has_all_attributes():
block = blocks.XceptionBlock()
config = block.get_config()
assert utils.get_func_args(
blocks.XceptionBlock.__init__).issubset(config.keys())
def test_xception_build_return_tensor():
block = blocks.XceptionBlock()
outputs = block.build(kerastuner.HyperParameters(),
tf.keras.Input(shape=(32, 32, 3), dtype=tf.float32))
assert len(nest.flatten(outputs)) == 1
assert isinstance(nest.flatten(outputs)[0], tf.Tensor)
def test_xception_pretrained_error_with_two_channels():
block = blocks.XceptionBlock(pretrained=True)
with pytest.raises(ValueError) as info:
block.build(kerastuner.HyperParameters(),
tf.keras.Input(shape=(224, 224, 2), dtype=tf.float32))
assert 'When pretrained is set to True' in str(info.value)
def test_xception_pretrained_with_one_channel_input():
block = blocks.XceptionBlock(pretrained=True)
outputs = block.build(
keras_tuner.HyperParameters(),
tf.keras.Input(shape=(224, 224, 1), dtype=tf.float32),
)
assert len(nest.flatten(outputs)) == 1
def test_xception_pretrained_build_return_tensor():
block = blocks.XceptionBlock(pretrained=True)
outputs = block.build(
keras_tuner.HyperParameters(),
tf.keras.Input(shape=(32, 32, 3), dtype=tf.float32),
)
assert len(nest.flatten(outputs)) == 1
def test_xception_deserialize_to_xception():
serialized_block = blocks.serialize(blocks.XceptionBlock())
block = blocks.deserialize(serialized_block)
assert isinstance(block, blocks.XceptionBlock)