Fix partition bug

mindspore/ccsrc/distributed/cluster/cluster_context.cc

@@ -199,12 +199,6 @@ void ClusterContext::InitNodeRole() {
     MS_LOG(EXCEPTION) << "Role name '" << node_role_ << "' is invalid. " << kDetailedFailureReason;
   }
 
-  // If node role is valid, judge the execution mode.
-  // MindSpore cluster does not support PyNative mode.
-  if (MsContext::GetInstance()->get_param<int>(MS_CTX_EXECUTION_MODE) == kPynativeMode) {
-    MS_LOG(EXCEPTION) << "PyNative mode is not supported in MindSpore cluster.";
-  }
-
   if (common::GetEnv(kEnvWorkerNum).empty()) {
     if (node_role_ == kEnvRoleOfWorker) {
       MS_LOG(EXCEPTION) << "Please set env 'WORKER_NUM' to a number greater than 0.";

mindspore/ccsrc/distributed/cluster/topology/meta_server_node.cc

@@ -154,12 +154,13 @@ MessageBase *const MetaServerNode::HandleMessage(MessageBase *const message) {
       return rpc::NULL_MSG;
     }
     const auto &result = (*message_handlers_[name])(message->Body());
-    delete message;
     if (result.length() > 0) {
       auto rt_msg = CreateMessage(meta_server_addr_.GetUrl(), name, result);
       MS_EXCEPTION_IF_NULL(rt_msg);
+      delete message;
       return rt_msg.release();
     } else {
+      delete message;
       return rpc::NULL_MSG;
     }
   }

mindspore/python/mindspore/ops/primitive.py

@@ -426,6 +426,10 @@ class Primitive(Primitive_):
         Validator.check_non_negative_int(rank_id, "rank_id", "Primitive.place")
         Validator.check_string(role, "MS_WORKER", "role", "Primitive.place")
 
+        if context.get_context("mode") == context.PYNATIVE_MODE:
+            raise RuntimeError("You are calling Primitive.place in pynative mode."
+                               "It's only supported in graph mode. Please switch to graph mode.")
+
         # Get the execution context and check whether calling of this 'place' method is valid.
         # This is because placing operators to arbitrary processes while other distributed training mode
         # is enabled is very unpredictable and may cause fatal error.

mindspore/python/mindspore/parallel/_ps_context.py

@@ -48,6 +48,9 @@ def set_ps_enable(enable):
     """
     Set ps enable flag.
     """
+    if context.get_context("mode") == context.PYNATIVE_MODE:
+        raise RuntimeError("Parameter server is not supported in pynative mode currently.")
+
     ps_context().set_ps_enable(enable)
     # If this is Server or Scheduler and device target is Ascend, reset the target to CPU
     if _need_reset_device_target_for_ps(context.get_context("device_target")):

tests/st/nccl/test_nccl_all.py

@@ -16,7 +16,7 @@ import os
 import pytest
 
 
-@pytest.mark.level2
+@pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_single
 def test_nccl_lenet():

tests/st/ps/full_ps/test_entry_full_ps_lenet.py

@@ -16,7 +16,7 @@ import os
 import pytest
 
 
-@pytest.mark.level1
+@pytest.mark.level0
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_single
@@ -39,7 +39,7 @@ def test_full_ps_lenet_ascend():
     assert return_code == 0
 
 
-@pytest.mark.level1
+@pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_full_ps_lenet_gpu():

tests/st/ps/part_ps/test_entry_ps_embedding_heterogeneous_conv2d_adam.py

@@ -16,7 +16,7 @@ import os
 import pytest
 
 
-@pytest.mark.level0
+@pytest.mark.level1
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.env_single

tests/ut/python/dataset/test_noop_mode.py

@@ -28,6 +28,7 @@ def test_noop_pserver():
     Expectation: Runs successfully
     """
     os.environ['MS_ROLE'] = 'MS_PSERVER'
+    context.set_context(mode=context.GRAPH_MODE)
     context.set_ps_context(enable_ps=True)
     data1 = ds.VOCDataset(DATA_DIR, task="Segmentation", usage="train", shuffle=False, decode=True)
     num = 0
@@ -45,6 +46,7 @@ def test_noop_sched():
     Expectation: Runs successfully
     """
     os.environ['MS_ROLE'] = 'MS_SCHED'
+    context.set_context(mode=context.GRAPH_MODE)
     context.set_ps_context(enable_ps=True)
     data1 = ds.VOCDataset(DATA_DIR, task="Segmentation", usage="train", shuffle=False, decode=True)
     num = 0