class MultiheadAttention()

调用方式示例：

from torch_npu.contrib.module import MultiheadAttention
model = MultiheadAttention(embed_dim=1024,num_heads=16,dropout=0.1,kdim=1024,vdim=1024,self_attention=True,encoder_decoder_attention=True)

使用示例：

   >>> model = MultiheadAttention(embed_dim=1024,num_heads=16,dropout=0.1,kdim=1024,vdim=1024,self_attention=True,encoder_decoder_attention=True)
   >>> _, query = create_common_tensor([np.float16, FORMAT_NZ, (1024,1024)], -1, 1)
   >>> _, key = create_common_tensor([np.float16, FORMAT_NZ, (1024, 1024)], -1, 1)
   >>> _, value = create_common_tensor([np.float16, FORMAT_NZ, (1024, 1024)], -1, 1)
   >>> _, key_padding_mask = create_common_tensor([np.float16, FORMAT_NZ, (16,16,64,64)], -65504, 65504)
   >>> bsz = 16
   >>> tgt_len = 64
   >>> s_len=64
   >>> model = model.to("npu")
   >>> output = model(query, key, value, bsz, tgt_len, s_len,   key_padding_mask)