[OP] Introduces auxiliary attrs into compute

[tqchen]

Previously we allow set a tag field to indicate the type of the compute op. After discussing with various TOPI developers, we find that it is helpful to further embed more meta information, such as padding size of the conv2d, to pass information from compute to schedule function. This PR introduces such change.

Attrs allows storing any Expr indexed by string.

Example

n = 10
m = 100
C = tvm.compute((n, m), 
    lambda i, j: tvm.sum(A[i, k] * B[j, k], axis=k), attrs={"n" : n, "shape":[n, m]})
print(C.op.attrs)
assert C.op.attrs["n"].value == 10
assert C.op.attrs["shape"][1].value == 100

NOTE

This change will break the json storage convention of the current TVM operations.

[tqchen]

@merrymercy @Laurawly @cowanmeg @srkreddy1238 can you review this PR?

[cowanmeg]

Looks good to me. If I'm understanding correctly this is to make it easier to look-up or compute parameters that are shared across compute and schedule? For example, in the rasp conv2d we wouldn't need to infer the stride and padding in the schedules if they were attributes.

[srkreddy1238]

Expr or Array<Expr> ??
In the context of passing a tuple (ex pad) leads to passing 2 or 4 different attributes !

[tqchen]

@srkreddy1238 made a very good point. I have changed the attrs to be Map<std::string, NodeRef>, so we can store any node object as an attribute value. test cases are updated.