[Bugfix] fix dcp_only bug and add e2e accuracy test for dcp only and pcp only (#5565)
### What this PR does / why we need it?
[Bugfix] fix dcp_only bug and add e2e accuracy test for dcp only and pcp
only
this pr fix the bug of accuracy test when decode_parallel_size>1 and
prefill_context_parallel_size=1.
### Does this PR introduce _any_ user-facing change?
NO
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
7157596103
---------
Signed-off-by: zhenwenqi2024 <zhenwenqi_2022@qq.com>
This commit is contained in:
@@ -935,22 +935,21 @@ class NPUModelRunner(GPUModelRunner):
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blk_table_tensor = blk_table.get_device_tensor()
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slot_mapping = blk_table.slot_mapping.gpu[:
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maybe_pcp_full_tokens]
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if self.pcp_size * self.dcp_size == 1:
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if self.pcp_size == 1:
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slot_mapping[
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total_num_scheduled_tokens:num_input_tokens].fill_(-1)
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slot_mapping = blk_table.slot_mapping.gpu
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if self.pcp_size * self.dcp_size > 1:
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self.long_seq_metadata = self.pcp_manager.generate_pcp_metadata(
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total_num_scheduled_tokens, self.query_lens,
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self.attn_mask, self.input_batch)
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blk_table.slot_mapping.gpu[maybe_pcp_full_tokens:].fill_(-1)
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slot_mapping = slot_mapping[:maybe_pcp_full_tokens]
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slot_mapping = self.pcp_manager.get_padded_slot_mapping(
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total_num_scheduled_tokens,
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slot_mapping,
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)
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blk_table.slot_mapping.gpu[:self.pcp_manager.
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num_actual_tokens_pcp_padded] = slot_mapping
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if self.pcp_size > 1:
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slot_mapping = self.pcp_manager.get_padded_slot_mapping(
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total_num_scheduled_tokens,
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slot_mapping,
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)
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blk_table.slot_mapping.gpu[:self.pcp_manager.
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num_actual_tokens_pcp_padded] = slot_mapping
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# NOTE: This is a temporary hack, now in GPUModelRunner, this prepare_inputs
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# has been split to multiple parts, and there are 3 parts that is related to this
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@@ -3034,7 +3033,7 @@ def _torch_cuda_wrapper():
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torch.cuda.synchronize = torch.npu.synchronize
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torch.cuda.mem_get_info = torch.npu.mem_get_info
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yield
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except Exception:
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except Exception as e:
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torch.cuda.Event = _EventPlaceholder
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torch.cuda.Stream = _StreamPlaceholder
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torch.cuda.default_stream = _StreamPlaceholder
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@@ -3042,6 +3041,7 @@ def _torch_cuda_wrapper():
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torch.cuda.stream = _StreamPlaceholder
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torch.cuda.synchronize = _StreamPlaceholder
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torch.cuda.mem_get_info = _StreamPlaceholder
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raise RuntimeError(f"NPUModelRunner init failed, error is {e}")
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finally:
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# if anything goes wrong, just patch it with a placeholder
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torch.cuda.Event = _EventPlaceholder
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@@ -13,6 +13,8 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from vllm.v1.worker.workspace import init_workspace_manager
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from vllm_ascend.worker.worker import NPUWorker
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from vllm_ascend.xlite.xlite_model_runner import XliteModelRunner
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@@ -23,4 +25,6 @@ class XliteWorker(NPUWorker):
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def init_device(self):
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"""Override init_device to init xlite model runner"""
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self.device = self._init_device()
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num_ubatches = 1
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init_workspace_manager(self.device, num_ubatches)
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self.model_runner = XliteModelRunner(self.vllm_config, self.device)
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