[AutoParallel] Fix the case in 'get_local_slices' func and add deepseek v3 to ci

ci/auto_parallel/ci_auto_parallel.sh

@@ -77,6 +77,7 @@ get_diff_TO_case(){
     case_list[${#case_list[*]}]=llama_auto
     case_list[${#case_list[*]}]=gpt-3_auto
     case_list[${#case_list[*]}]=gpt-3_dygraph
+    case_list[${#case_list[*]}]=deepseek_auto
 }
 
 print_info(){
@@ -258,6 +259,14 @@ if [[ ${#case_list[*]} -ne 0 ]];then
             execute_func_list $cmd gpt-3_dygraph
             let case_num++
             clean_file ${work_dir}/../PaddleNLP/llm
+        elif [[ ${case} == "deepseek_auto" ]];then
+            cmd=${work_dir}/../PaddleNLP/scripts/distribute/ci_case_auto.sh
+            timeout 5m bash $cmd prepare_case deepseek_case_list_auto $FLAGS_install_deps $FLAGS_download_data
+            execute_func_list $cmd deepseek_auto
+            export FLAGS_install_deps=1
+            export FLAGS_download_data="deepseek ""$FLAGS_download_data"
+            let case_num++
+            clean_file ${work_dir}/../PaddleNLP/llm/auto_parallel/deepseek-v3
         else
             echo -e "\033[31m ---- no ${case} \033"
             let case_num++

python/paddle/distributed/auto_parallel/moe_utils.py

@@ -393,10 +393,13 @@ def get_rank2tensor_indices(sub_mesh_indices_info, sub_mesh_partial_info):
 
 
 def get_local_slices(tensor, mesh, placements):
-    if len(mesh.shape) != len(placements):
+    if len(mesh.shape) < len(placements):
         raise ValueError(
-            f"placements nums ({len(placements)}) must equal mesh_shape({len(mesh.shape)})"
+            f"placements length ({len(placements)}) must be smaller or equal to mesh_shape({len(mesh.shape)})"
         )
+    if len(placements) < len(mesh.shape):
+        for _ in range(len(mesh.shape) - len(placements)):
+            placements.append(dist.Replicate())
 
     sub_mesh_indices_info = {mesh: [(0, s) for s in tensor.shape]}
     sub_mesh_partial_info = {}

test/auto_parallel/semi_auto_parallel_moe_utils.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import os
+import unittest
 
 import numpy as np
 
@@ -26,7 +27,7 @@
 )
 
 
-class TestMoEUtils:
+class TestMoEUtils(unittest.TestCase):
     def __init__(self):
         self._dtype = os.getenv("dtype")
         self._seeds = eval(os.getenv("seeds"))
@@ -160,6 +161,25 @@ def test_get_local_slices(self):
             dist_x.placements[1].reduce_type(),
         )
 
+        y = paddle.arange(0, h * w).reshape(src_shape)
+        y_placements = [dist.Shard(0)]
+        dist_y = dist.shard_tensor(y, self._mesh0, y_placements)
+        dist_y_local_slices = get_local_slices(
+            dist_y, self._mesh0, y_placements
+        )
+        np.testing.assert_equal(
+            dist_y_local_slices[0]['slice'], [(0, 2), (0, 4)]
+        )
+        np.testing.assert_equal(
+            dist_y_local_slices[1]['slice'], [(2, 4), (0, 4)]
+        )
+
+        with self.assertRaises(ValueError):
+            tmp_placements = [dist.Shard(0), dist.Shard(1), dist.Replicate()]
+            dist_y_local_slices = get_local_slices(
+                dist_y, self._mesh0, tmp_placements
+            )
+
     # python -m paddle.distributed.launch --devices=0,1 semi_auto_parallel_moe_utils.py
     def test_reshard_general_case(self):
         """Test reshard when _only_reshard_mesh_shape returns False."""

test/auto_parallel/test_moe_utils.py

@@ -23,14 +23,14 @@ def setUp(self):
             num_of_devices=2,
             timeout=30,
         )
-        self._default_envs = {"dtype": "float32", "seed": "2024"}
+        self._default_envs = {"dtype": "float32", "seeds": "2024"}
         self._changeable_envs = {"backend": ["gpu"]}
 
     def test_moe_utils(self):
         envs_list = test_base.gen_product_envs_list(
             {
                 "dtype": "float32",
-                "seed": "2024",
+                "seeds": "2024",
                 "FLAGS_enable_moe_utils": "true",
             },
             {"backend": ["gpu"]},