`has_type` is not necessary to match the final expression. It can also be used
like the following to check the type of an op:
```python
in1 = wildcard()
in2 = wildcard()
pat = is_op('add')(in1, in2).has_type(relay.TensorType((10, 10), 'float32'))
x = relay.var('x', shape=(10, 10), dtype='float32')
pat.match(relay.add(x, x))
```
This can be extended to a more complex pattern like
```python
in1 = wildcard()
in2 = wildcard()
add = is_op('add')(in1, in2).has_type(relay.TensorType((10, 10), 'float32'))
mul = is_op('multiply')(add, add)
```
In this case, you only match the the type of `add` but do not care `mul`,
although in this case `mul` must be `float32`, too.
---
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