[Bugfix] Fix the bug in sfa-cp under multi-DP scenarios. (#4850)

### What this PR does / why we need it?
This PR fix the bug in sfa-cp under multi-DP scenarios.

### Does this PR introduce _any_ user-facing change?
None

### How was this patch tested?
None

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: zzhxx <2783294813@qq.com>
Co-authored-by: clrs97 <524936896@qq.com>

vllm_ascend/attention/sfa_v1.py

@@ -66,8 +66,6 @@ class SfaCpContext:
     local_start: int
     local_end: int
     local_end_with_pad: int
-    pad_size: int
-    local_pad_size: int
     slot_mapping_cp: torch.Tensor
     actual_seq_lengths_query: torch.Tensor
     actual_seq_lengths_key: torch.Tensor
@@ -206,23 +204,41 @@ class AscendSFAMetadataBuilder:
         sfa_cp_context = None
         if self.enable_sfa_cp:
             global_tp_size = get_tp_group().world_size
-            num_tokens = num_actual_tokens
+            num_tokens = num_input_tokens
-            num_tokens_pad = _round_up(num_actual_tokens, global_tp_size)
+            num_tokens_pad = _round_up(num_tokens, global_tp_size)
             num_tokens_per_device = num_tokens_pad // global_tp_size
-            pad_size = num_tokens_pad - num_tokens
             local_start = get_tp_group().rank_in_group * num_tokens_per_device
             local_end_with_pad = local_start + num_tokens_per_device
             local_end = min(local_end_with_pad, num_actual_tokens)
-            local_pad_size = local_end_with_pad - local_end
+
+            pad_size = num_tokens_pad - cos.shape[0]
+            assert cos.shape == sin.shape, \
+                f"cos.shape must be equal to sin.shape, got {cos.shape} and {sin.shape}"
 
             if pad_size > 0:
                 cos = nn.functional.pad(cos, (0, 0, 0, 0, 0, 0, 0, pad_size))
                 sin = nn.functional.pad(sin, (0, 0, 0, 0, 0, 0, 0, pad_size))
-                slot_mapping = nn.functional.pad(slot_mapping, (0, pad_size),
+
+            pad_size_slot = num_tokens_pad - slot_mapping.shape[0]
+            if pad_size_slot > 0:
+                slot_mapping = nn.functional.pad(slot_mapping,
+                                                 (0, pad_size_slot),
                                                  value=-1)
+            else:
+                slot_mapping = slot_mapping[:num_tokens_pad]
+
             cos = cos[local_start:local_end_with_pad]
             sin = sin[local_start:local_end_with_pad]
             slot_mapping_cp = slot_mapping[local_start:local_end_with_pad]
+            assert cos.shape[0] == num_tokens_per_device, \
+                f"cos.shape[0] must be equal to num_tokens_per_device, \
+                    got {cos.shape[0]} and {num_tokens_per_device}"
+            assert slot_mapping_cp.shape[0] == num_tokens_per_device, \
+                f"slot_mapping_cp.shape[0] must be equal to num_tokens_per_device, \
+                    got {slot_mapping_cp.shape[0]} and {num_tokens_per_device}"
+            assert slot_mapping.shape[0] == num_tokens_pad, \
+                f"slot_mapping.shape[0] must be equal to num_tokens_pad, \
+                    got {slot_mapping.shape[0]} and {num_tokens_pad}"
 
             actual_seq_lengths_query = torch.empty_like(cum_query_lens)
             actual_seq_lengths_key = torch.empty_like(seq_lens)
@@ -254,8 +270,6 @@ class AscendSFAMetadataBuilder:
                 local_start=local_start,
                 local_end=local_end,
                 local_end_with_pad=local_end_with_pad,
-                pad_size=pad_size,
-                local_pad_size=local_pad_size,
                 slot_mapping_cp=slot_mapping_cp,
                 actual_seq_lengths_query=actual_seq_lengths_query,
                 actual_seq_lengths_key=actual_seq_lengths_key,