onnxruntime

support broadcast shape for elementwise node in padding elimination (#16710)

With PaddingElimination optimizer, input1 of element-wise op may be
flattened like:

```
  input1 (shape:[batch_size, seq_len, ...])        input1 (shape:[valid_tokens, ...])
        \                                               \
         \               input2                          \               input2
          \                /              ----->          \               /
           \              /                                \             /
	    Element-wise Op                                Element-wise Op
```
So, the shape of input2 should be processed accordingly:
1. If input2.shape.dim_size <= input1.shape.dim_size-2, i.e. input2 has
no [batch_size, seq_len] at begining,
we needn't to process the shape of input2 because it's compatible with
the flattened shape of input1 (shape:[valid_tokens, ...]).
   
2. If the shape of input2 has the same dim_size with shape of input1 and
has [batch_size, seqlen] at begening,
to be compatible with flattened shape of input1, we need to insert
flatten pattern for input2 also,
which flatten the shape of input2 from [batch_size, seq_len, ...] to
[valida_tokens, ...].
   
  
3. (which done in this pr) In other case for shape of input2, like [1,
seq_len, ...] or [batch_size, 1, ...], we firstly need to expand it
to [batch_size, seq_len, ...] which is convenient to flatten. And then
insert flatten pattern.