!22359 add st for pynative synchronize

Merge pull request !22359 from chujinjin/add_st_for_pynative_synchronize

mindspore/context.py

@@ -516,7 +516,7 @@ def _check_target_specific_cfgs(device, arg_key):
                  enable_profiling=bool, profiling_options=str, enable_auto_mixed_precision=bool,
                  enable_graph_kernel=bool, check_bprop=bool, max_device_memory=str, print_file_path=str,
                  enable_sparse=bool, max_call_depth=int, env_config_path=str, graph_kernel_flags=str,
-                 save_compile_cache=bool, load_compile_cache=bool, grad_for_scalar=bool)
+                 save_compile_cache=bool, load_compile_cache=bool, grad_for_scalar=bool, pynative_synchronize=bool)
 def set_context(**kwargs):
     """
     Set context for running environment.
@@ -544,14 +544,14 @@ def set_context(**kwargs):
     check_bprop                  print_file_path              max_device_memory
     device_id                    enable_dump                  enable_graph_kernel
     device_target                save_dump_path               graph_kernel_flags
-    enable_sparse                enable_graph_kernel
+    enable_sparse                enable_graph_kernel          pynative_synchronize
     max_call_depth               enable_reduce_precision
     mode                         enable_profiling
     reserve_class_name_in_scope  profiling_options
     save_graphs                  variable_memory_max_size
     save_graphs_path             auto_tune_mode
     env_config_path              graph_kernel_flags
-    grad_for_scalar
+    grad_for_scalar              pynative_synchronize
     save_compile_cache
     load_compile_cache
     ===========================  ===========================  =================
@@ -663,6 +663,8 @@ def set_context(**kwargs):
             you should make sure the network has not been changed since the last execution. By now, we have
             not support automatically checking the changes yet. Default: False.
             This is an experimental prototype that is subject to change and/or deletion.
+        pynative_synchronize (bool): Whether to enable asynchronous execution of the device in Pynative mode.
+            Default: False.
 
     Raises:
         ValueError: If input key is not an attribute in context.

tests/st/pynative/test_pynative_sync_control.py

@@ -0,0 +1,51 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore.context as context
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore.common import dtype as mstype
+from mindspore.ops import operations as P
+
+context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
+
+class Net(nn.Cell):
+    def __init__(self):
+        super(Net, self).__init__()
+        self.get_next = P.GetNext([mstype.float32], [(1, 1)], 1, "test")
+
+    def construct(self, x1,):
+        x = self.get_next()
+        x = x + x1
+        return x
+
+def test_pynative_synchronize_true():
+    context.set_context(pynative_synchronize=True)
+    with pytest.raises(RuntimeError) as execinfo:
+        x1 = np.random.randn(1, 1).astype(np.float32)
+        net = Net()
+        output = net(Tensor(x1))
+        print(output.asnumpy())
+    assert "GetNext" in str(execinfo.value)
+
+def test_pynative_synchronize_false():
+    context.set_context(pynative_synchronize=False)
+    with pytest.raises(RuntimeError) as execinfo:
+        x1 = np.random.randn(1, 1).astype(np.float32)
+        net = Net()
+        output = net(Tensor(x1))
+        print(output.asnumpy())
+    assert "Sync stream error" in str(execinfo.value)