def test_saving_int8_ndarray(tmpdir):
protobuf_file = str(tmpdir/'dictionary_val.bin')
delete_if_file_exists(protobuf_file)
data = np.arange(0,64, dtype=np.int8).reshape(16,4)
dict_val = C._to_cntk_dict_value(data)
dict_val.save(protobuf_file)
assert(os.path.getsize(protobuf_file) == 82)
a = dict_val.load(protobuf_file)
assert(a==dict_val)
def test_saving_int16_ndarray(tmpdir):
protobuf_file = str(tmpdir/'dictionary_val_int16.bin')
delete_if_file_exists(protobuf_file)
data = np.arange(0,64, dtype=np.int16).reshape(16,4)
dict_val = C._to_cntk_dict_value(data)
dict_val.save(protobuf_file)
assert(os.path.getsize(protobuf_file) == 82)
a = dict_val.load(protobuf_file)
assert(a==dict_val)
def test_saving_and_loading_int8_ndarray_as_attribute(tmpdir):
model_file = str(tmpdir/'test_model.bin')
delete_if_file_exists(model_file)
data = np.arange(0,64, dtype=np.int8).reshape(16,4)
dict_val = C._to_cntk_dict_value(data)
W = C.Parameter((C.InferredDimension, 42), init=C.glorot_uniform(), dtype=np.float)
x = C.input_variable(12, dtype=np.float)
y = C.times(x, W)
y.custom_attributes = {'int8_nd':dict_val}
y.save(model_file)
assert(os.path.isfile(model_file))
z = C.load_model(model_file)
int8_data = z.custom_attributes['int8_nd']
assert(int8_data.shape == (16,4))
assert (np.array_equal(int8_data, data))
def test_saving_and_loading_int16_ndarray_as_attribute(tmpdir):
model_file = str(tmpdir/'test_model_int16.bin')
delete_if_file_exists(model_file)
data = np.arange(0,64, dtype=np.int16).reshape(16,4)
dict_val = C._to_cntk_dict_value(data)
W = C.Parameter((C.InferredDimension, 42), init=C.glorot_uniform(), dtype=np.float)
x = C.input_variable(12, dtype=np.float)
y = C.times(x, W)
y.custom_attributes = {'int16_nd':dict_val}
y.save(model_file)
assert(os.path.isfile(model_file))
z = C.load_model(model_file)
int16_data = z.custom_attributes['int16_nd']
assert(int16_data.shape == (16,4))
assert (np.array_equal(int16_data, data))