[Feature] Support for cross-attention and whisper model (#5592)

### What this PR does / why we need it?
To solve the problem of the
issue：https://github.com/vllm-project/vllm-ascend/issues/2262

- support for cross-attention when the model is encoder-decoder
- support for whisper model

- vLLM version: v0.13.0
- vLLM main:
7157596103

Signed-off-by: gh924 <guihao2@huawei.com>
Co-authored-by: Aoxuan Chen <43376869+chenaoxuan@users.noreply.github.com>

tests/ut/attention/test_attention_v1.py

@@ -320,26 +320,3 @@ class TestAscendAttentionBackendImpl(TestBase):
         mock_fused_infer_attention_score.assert_called_once()
 
         assert output.shape == (10, 8, 64)
-
-    @patch('torch_npu._npu_reshape_and_cache')
-    def test_forward_raise_error(self, mock_paged_attention):
-        query = torch.randn(10, 8 * 64)
-        key = torch.randn(10, 8 * 64)
-        value = torch.randn(10, 8 * 64)
-        kv_cache = torch.empty(2, 5, 128, 8, 64)
-        output = torch.empty_like(query)
-
-        metadata = self.attn_metadata
-        metadata.attn_mask = torch.randn(1, 1, 10, 10)
-        metadata.query_lens = torch.tensor([10])
-        metadata.seq_lens = torch.tensor([10])
-        metadata.block_tables = torch.zeros(1, 5, dtype=torch.long)
-        metadata.num_actual_tokens = 10
-        metadata.slot_mapping = torch.zeros(10, dtype=torch.long)
-        metadata.num_decodes = 0
-        metadata.num_prefills = 10
-        layer = self.layer_no_quant
-
-        with self.assertRaises(NotImplementedError):
-            self.impl_error.forward(layer, query, key, value, kv_cache,
-                                    metadata, output)