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))