def test_parameter_lazy_init():
# Call init_data() without set default_input.
para = Parameter(initializer('ones', [1, 2, 3], mstype.float32), 'test1')
assert not isinstance(para.default_input, Tensor)
para.init_data()
assert isinstance(para.default_input, Tensor)
assert np.array_equal(para.default_input.asnumpy(), np.ones((1, 2, 3)))
# Call init_data() after default_input is set.
para = Parameter(initializer('ones', [1, 2, 3], mstype.float32), 'test2')
assert not isinstance(para.default_input, Tensor)
para.default_input = Tensor(np.zeros((1, 2, 3)))
assert np.array_equal(para.default_input.asnumpy(), np.zeros((1, 2, 3)))
para.init_data() # expect no effect.
assert np.array_equal(para.default_input.asnumpy(), np.zeros((1, 2, 3)))
def test_parameter_lazy_init():
_set_has_initializer(False)
# support lazy init in SEMI_AUTO_PARALLEL mode
context.reset_auto_parallel_context()
context.set_auto_parallel_context(parallel_mode="semi_auto_parallel",
device_num=8)
# Call init_data() without set default_input.
para = Parameter(initializer('ones', [1, 2, 3], mstype.float32), 'test1')
assert not isinstance(para.default_input, Tensor)
para = para.init_data()
assert isinstance(para.default_input, Tensor)
assert np.array_equal(para.default_input.asnumpy(), np.ones((1, 2, 3)))
# Call init_data() after default_input is set.
para = Parameter(initializer('ones', [1, 2, 3], mstype.float32), 'test2')
assert not isinstance(para.default_input, Tensor)
# expect type error when not init
with pytest.raises(TypeError):
para.default_input = Tensor(np.zeros((1, 2, 3)))
# init then assign
para = para.init_data()
# check the type
with pytest.raises(TypeError):
para.default_input = Tensor(np.zeros((1, 2, 3)))
# check the shape
with pytest.raises(ValueError):
para.default_input = Tensor(np.zeros((1, 2)))
# expect change ok
para.default_input = Tensor(np.zeros((1, 2, 3)).astype(np.float32))
assert np.array_equal(para.default_input.asnumpy(), np.zeros((1, 2, 3)))
para.default_input = initializer('ones', [1, 2, 3], mstype.float32)
assert isinstance(para.default_input, Tensor)
# same object and has inited
assert np.array_equal(para.default_input.asnumpy(), np.ones((1, 2, 3)))
# expect no effect.
para.init_data()
assert np.array_equal(para.default_input.asnumpy(), np.ones((1, 2, 3)))
para.set_parameter_data(Tensor(np.zeros((1, 2)).astype(np.float32)),
slice_shape=True)
assert np.array_equal(para.default_input.asnumpy(), np.zeros((1, 2)))
para.set_parameter_data(initializer('ones', [1, 2], mstype.float32),
slice_shape=True)
assert np.array_equal(para.default_input.asnumpy(), np.ones((1, 2)))
context.reset_auto_parallel_context()
class Net(nn.Cell):
def __init__(self, initial, updated):
super().__init__()
self.initial = initial
self.updated = updated
self.p = Parameter(self.initial, name="weight")
self.new_p = self.p.init_data()
self.new_p.set_data(self.updated)
def construct(self):
return self.new_p
