[WebNN EP] Support MultiHeadAttention(MHA)

[peishenyan]

Description

Adds support for MultiHeadAttention via WebNN matmul, transpose, reshape, and other operations that follow the logic in the MHA subgraph below

 Abbreviatios: B is batch_size, S is sequence_length, W is hidden_size, P is past_sequence_length
               N is number of attention heads, H is head size, and W=N*H, h=Sqrt(H)
    Notes: If the datatype of the inputs (qkv and past kv) is float16, we cast them to float32 to ensure data precision.

                 query     key     value
                   |        |        |
           q_Reshape   k_Reshape   v_Reshape  (shape=B,S,H,N)
                   |        |        |
          q_Transpose  k_Transpose v_Transpose (perm=0,2,1,3)
             \           /           |
              \         /            |
present_key<---\----Concat <---------|----past_key
               |      |              |
               |  opt_k_transpose    |
               \  (0,1,3,2)          |
                \    /               |  past_value
                qk_MatMul            |     /
                     |  scale        |    /
                     |   /           |   /
                  qk_Div           Concat------> present_value
                      |              |
                      |              /
                     Add <----------/---------------attention_bias
                      |            /
                    Softmax       /
                       \         /
                        \       /
                      qkv_MatMul
                             |
                          Transpose (perm=0,2,1,3)
                             |
                          Reshape---(shape=B,P,W)
                             |
                           output

Motivation and Context