Inconsistency between HybridBlock and Block

[arcadiaphy]

Following #16279, another example of inconsistency between HybridBlock and Block:

import mxnet as mx
from mxnet.gluon import HybridBlock

class Foo(HybridBlock):
    def hybrid_forward(self, F, a, b):
        return a + b


b1 = Foo(prefix='non_hybrid')
b2 = Foo(prefix='hybrid')
b2.hybridize()

print(b1(mx.nd.ones((10,)), mx.nd.ones((1,))))
print(b2(mx.nd.ones((10,)), mx.nd.ones((1,))))

MXNetError is triggered for hybridized case:

MXNetError: MXNetError: Error in operator hybrid_plus0: [14:24:15] src/operator/numpy/linalg/../../tensor/../elemwise_op_common.h:135: Check failed: assign(&dattr, vec.at(i)): Incompatible attr in node hybridized_plus0 at 1-th input: expected [10], got [1]

I think it's because for symbol, elemwise_add is used for __add__, while for ndarray broadcasting is considered in __add__ considering input shape. Can we add broadcasting in symbol too and avoid the need to differentiate between elemwise_add and broadcast_add?

Note that the same problem exists in subtract, multiply and divide operation, too.