def __init__(self):
super(NetReduceLogic, self).__init__()
self.axis0 = 0
self.axis1 = -1
self.axis2 = (0, 1, 2)
self.axis3 = ()
self.reduce_all = P.ReduceAll(False)
self.reduce_any = P.ReduceAny(False)
def test_elim_all_shape_one(tag):
""" test_elim_all_shape_one """
fns = FnDict()
all_ = P.ReduceAll()
@fns
def before(x, y):
return all_(x, 0)
@fns
def after(x, y):
return x
return fns[tag]
('Dropout', {
'block': nn.Dropout(0.5),
'desc_inputs': [[64, 12, 128, 128]],
'desc_bprop': [[64, 12, 128, 128]]}),
('ReduceMean0', {
'block': P.ReduceMean(),
'desc_const': [(2,)],
'desc_inputs': [[3, 2, 2]],
'desc_bprop': [[3, 2]]}),
('ReduceMean1', {
'block': P.ReduceMean(),
'desc_const': [2],
'desc_inputs': [[3, 2, 2]],
'desc_bprop': [[3, 2]]}),
('All', {
'block': P.ReduceAll(),
'desc_const': [(1,)],
'desc_inputs': [Tensor(np.ones([3, 2]).astype(np.bool_))],
'desc_bprop': [[3]],
'skip': ['backward']}),
('DescConst', {
'block': Tensor(np.array([2], np.float32)),
'desc_inputs': [],
'desc_bprop': [[1]],
'skip': ['backward'],
'add_fake_input': True}),
('Fill', {
'block': P.Fill(),
'desc_const': [mstype.float32, (2, 3), 1.0],
'desc_inputs': [],
'desc_bprop': [[2, 3]],
def __init__(self):
super(ReduceAllDynamic, self).__init__()
self.reduceall = P.ReduceAll(False)
self.test_dynamic = inner.GpuConvertToDynamicShape()
def construct(self):
return (P.ReduceAll(self.keep_dims0)(self.x0, self.axis0),
P.ReduceAll(self.keep_dims1)(self.x1, self.axis1),
P.ReduceAll(self.keep_dims2)(self.x2, self.axis2),
P.ReduceAll(self.keep_dims3)(self.x3, self.axis3))
