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)
