[CI] change to new ds model (#1513)

Previous, the DeepSeek V3 Pruning weight is not correct, the moe layer
is not tested. We update a new Pruning model to enable moe layer
compute.

This PR fix the CI to address the new weight.

---------

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

tests/e2e/multicard/test_fused_moe_allgather_ep.py

@@ -0,0 +1,82 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+"""
+Execute the inference of fused_moe_allgather_ep and fused_moe_alltoall_ep.
+
+Run 'pytest tests/multicard/test_fused_moe_allgather_ep.py'.
+"""
+
+import os
+from unittest.mock import patch
+
+from modelscope import snapshot_download  # type: ignore
+from vllm import SamplingParams
+
+from tests.conftest import VllmRunner
+
+
+@patch.dict(
+    os.environ, {
+        "VLLM_USE_V1": "1",
+        "VLLM_WORKER_MULTIPROC_METHOD": "spawn",
+        "TASK_QUEUE_ENABLE": "1",
+        "VLLM_ENABLE_FUSED_EXPERTS_ALLGATHER_EP": "1"
+    })
+def test_generate_with_allgather():
+    example_prompts = ["Hello, my name is"]
+    sampling_params = SamplingParams(max_tokens=100, temperature=0.0)
+
+    with VllmRunner(snapshot_download("vllm-ascend/DeepSeek-V3-Pruning"),
+                    tensor_parallel_size=4,
+                    enforce_eager=True,
+                    max_model_len=1024,
+                    dtype="auto",
+                    enable_expert_parallel=True,
+                    additional_config={
+                        "ascend_scheduler_config": {
+                            "enabled": True,
+                            "chunked_prefill_enabled": False,
+                        },
+                        "expert_tensor_parallel_size": 1
+                    }) as vllm_model:
+        vllm_model.generate(example_prompts, sampling_params)
+
+
+@patch.dict(
+    os.environ, {
+        "VLLM_USE_V1": "1",
+        "VLLM_WORKER_MULTIPROC_METHOD": "spawn",
+        "TASK_QUEUE_ENABLE": "1"
+    })
+def test_generate_with_alltoall():
+    example_prompts = ["Hello, my name is"]
+    sampling_params = SamplingParams(max_tokens=100, temperature=0.0)
+
+    with VllmRunner(snapshot_download("vllm-ascend/DeepSeek-V3-Pruning"),
+                    tensor_parallel_size=4,
+                    enforce_eager=True,
+                    max_model_len=1024,
+                    dtype="auto",
+                    enable_expert_parallel=True,
+                    additional_config={
+                        "ascend_scheduler_config": {
+                            "enabled": True,
+                            "chunked_prefill_enabled": False,
+                        },
+                        "expert_tensor_parallel_size": 1
+                    }) as vllm_model:
+        vllm_model.generate(example_prompts, sampling_params)

tests/e2e/multicard/test_offline_inference_distributed.py

@@ -56,7 +56,7 @@ def test_models_distributed_DeepSeek_multistream_moe():
     with VllmRunner(
             "vllm-ascend/DeepSeek-V3-Pruning",
             dtype=dtype,
-            tensor_parallel_size=2,
+            tensor_parallel_size=4,
             distributed_executor_backend="mp",
             additional_config={
                 "torchair_graph_config": {

tests/e2e/multicard/test_torchair_graph_mode.py

@@ -66,10 +66,10 @@ def _deepseek_torchair_test_fixture(
     # inaccurate. This will only change if accuracy improves with the
     # official weights of DeepSeek-V3.
     golden_results = [
-        'Hello, my name is feasibility伸 spazio debtor添',
-        'The president of the United States is begg"""\n杭州风和 bestimm',
-        'The capital of France is frequentlyশามalinkAllowed',
-        'The future of AI is deleting俯احت怎么样了حراف',
+        'Hello, my name is下载早点向前很有่อง',
+        'The president of the United States isSender)## physiological Albany',
+        'The capital of France is Rocky转角 hospitalizedinterval sparked',
+        'The future of AI is её asegο BIOS一扫',
     ]
 
     assert len(golden_results) == len(vllm_output)