def test_ndarray(): nat = DatasetAnalyzer.analyze(np.array([1, 2, 3])) assert issubclass(nat, NumpyNdarrayDatasetType) payload = dumps(nat) nat2 = loads(payload, DatasetType) assert nat == nat2
def test_ndarray(nat): assert issubclass(nat, NumpyNdarrayDatasetType) assert nat.requirements.modules == ['numpy'] payload = dumps(nat) nat2 = loads(payload, DatasetType) assert nat == nat2
def test_number(): ndt = DatasetAnalyzer.analyze(np.float32(.5)) assert issubclass(ndt, NumpyNumberDatasetType) assert ndt.requirements.modules == ['numpy'] payload = dumps(ndt) ndt2 = loads(payload, DatasetType) assert ndt == ndt2
def test_feed_dict_type__serialization(tensor): obj = {tensor: np.array([[1]])} fdt = DatasetAnalyzer.analyze(obj) payload = dumps(obj, fdt) obj2 = loads(payload, fdt) assert obj[tensor] == obj2[tensor.name]
def test_feed_dict_type__self_serialization(fdt, tensor): from ebonite.ext.tensorflow import FeedDictDatasetType assert issubclass(fdt, FeedDictDatasetType) assert set(fdt.requirements.modules) == {'tensorflow', 'numpy'} payload = dumps(fdt) fdt2 = loads(payload, DatasetType) assert fdt == fdt2
def test_feed_dict_type__self_serialization(tftt): from ebonite.ext.tensorflow_v2 import TFTensorDatasetType assert issubclass(tftt, TFTensorDatasetType) assert tftt.requirements.modules == ['tensorflow'] payload = dumps(tftt) tftt2 = loads(payload, DatasetType) assert tftt == tftt2
def test_feed_dict_type__serialization(): tensor = tf.placeholder('float', (1, 1), name="weight") obj = {tensor: np.array([[1]])} fdt = DatasetAnalyzer.analyze(obj) payload = dumps(obj, fdt) obj2 = loads(payload, fdt) assert obj[tensor] == obj2[tensor.name]
def test_feed_dict_type__self_serialization(): tensor = tf.placeholder('float', (1, 1), name="weight") fdt = DatasetAnalyzer.analyze({ tensor: np.array([[1]]), 'a': np.array([[1]]) }) assert issubclass(fdt, FeedDictDatasetType) payload = dumps(fdt) fdt2 = loads(payload, DatasetType) assert fdt == fdt2
def test_number(): ndt = DatasetAnalyzer.analyze(np.float32(.5)) assert issubclass(ndt, NumpyNumberDatasetType) payload = dumps(ndt) ndt2 = loads(payload, DatasetType) assert ndt == ndt2
def safe_loads(payload, as_class): return loads(payload, Optional[as_class])
def test_feed_dict_type__serialization(tftt, tensor_data): payload = dumps(tensor_data, tftt) tensor_data2 = loads(payload, tftt) tf.assert_equal(tensor_data, tensor_data2)