def test_scalar_parameter_update():
# float
fp = Parameter(0.5, 'fp')
fp.default_input = 0.8
assert np.array_equal(fp.default_input.asnumpy(),
np.array(0.8, np.float32))
fp.default_input = 1
assert np.array_equal(fp.default_input.asnumpy(),
np.array(1.0, np.float32))
int_ = Parameter(1, 'fp')
int_.default_input = 2
assert np.array_equal(int_.default_input.asnumpy(), np.array(2, np.int32))
with pytest.raises(TypeError):
int_.default_input = 1.2
# Tensor
fp32 = Tensor(0.5, mstype.float32)
int32 = Tensor(2, mstype.int32)
fp16 = Tensor(0.6, mstype.float16)
int16 = Tensor(3, mstype.int16)
bool_ = Tensor(np.array(True, dtype=np.bool_))
# updata_by_tensor
fp32_p = Parameter(fp32, 'fp32')
fp32_p.default_input = 0.8
fp32_p.default_input = 1
fp32_p.default_input = int32
fp32_p.default_input = fp32
fp32_p.default_input = int16
fp32_p.default_input = fp16
fp32_p.default_input = bool_
# updata_by_tensor
fp16_p = Parameter(fp16, 'fp16')
with pytest.raises(TypeError):
fp16_p.default_input = fp32
def test_scalar_parameter_update():
fp = Parameter(0.5, 'fp')
fp.default_input = 0.8
assert np.array_equal(fp.default_input.asnumpy(),
np.array(0.8, np.float32))
fp.default_input = 1
assert np.array_equal(fp.default_input.asnumpy(),
np.array(1.0, np.float32))
int_ = Parameter(1, 'fp')
int_.default_input = 2
assert np.array_equal(int_.default_input.asnumpy(), np.array(2, np.int32))
with pytest.raises(TypeError):
int_.default_input = 1.2
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()
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)))
