Add test cases for environment variables.

mindspore/ccsrc/pipeline/jit/ps/static_analysis/order_enforce.cc

@@ -56,6 +56,8 @@ class OrderEnforcer {
     static const bool no_insert_tensormove = common::GetEnv("MS_DEV_SIDE_EFFECT_LOAD_ELIM") == "3";
     // Do not insert TensorMove for all Load nodes
     if (no_insert_tensormove) {
+      MS_LOG(WARNING) << "Do not insert TensorMove for all Load nodes, the memory footprint is minimal, "
+                         "but there may be accuracy issues with the results.";
       return;
     }
     // After ensuring the correct control edge relationship, then insert the TensorMove operator.

tests/st/auto_monad/test_auto_monad_expression.py

@@ -12,6 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
+import os
+import re
+import shutil
 import pytest
 import numpy as np
 from mindspore.nn import Cell
@@ -168,10 +171,31 @@ class BackwardNet(Cell):
         return grads
 
 
-@pytest.mark.level2
+def clean_all_ir_files(folder_path):
+    if os.path.exists(folder_path):
+        for file_name in os.listdir(folder_path):
+            if file_name.endswith('.ir') or file_name.endswith('.dot') or \
+                    file_name.endswith('.dat') or file_name.endswith('.pb'):
+                os.remove(os.path.join(folder_path, file_name))
+
+
+def find_newest_validateir_file(folder_path):
+    ckpt_files = map(lambda f: os.path.join(folder_path, f),
+                     filter(lambda f: re.match(r'\d+_auto_monad_reorder_\d+.ir', f),
+                            os.listdir(folder_path)))
+    return max(ckpt_files, key=os.path.getctime)
+
+
+def read_file(save_path):
+    filename = find_newest_validateir_file(save_path)
+    with open((os.path.join(filename)), 'r') as f:
+        content = f.read()
+    clean_all_ir_files(save_path)
+    return content
+
+
+@pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
 def test_load_convert_tensormove():
     """
@@ -179,12 +203,26 @@ def test_load_convert_tensormove():
     Description: record the value of load.
     Expectation: No exception.
     """
-    x = Tensor(np.array(1), ms.int32)
-    graph_forword_net = ForwardNet()
-    graph_backword_net = BackwardNet(graph_forword_net)
-    graph_mode_grads = graph_backword_net(x)
-    output_except = (Tensor(np.array(3), ms.int32),)
-    assert np.all(graph_mode_grads == output_except)
+
+    if ms.context.get_context('mode') == 0:
+        # set MS_DEV_SIDE_EFFECT_LOAD_ELIM = 0/1/2
+        os.environ['MS_DEV_SIDE_EFFECT_LOAD_ELIM'] = '1'
+        save_path = "./test_load_convert_tensormove"
+        context.set_context(save_graphs=True, save_graphs_path=save_path)
+        x = Tensor(np.array(1), ms.int32)
+        graph_forword_net = ForwardNet()
+        graph_backword_net = BackwardNet(graph_forword_net)
+        output_except = (Tensor(np.array(3), ms.int32),)
+        graph_mode_grads = graph_backword_net(x)
+        content2 = read_file(save_path)
+        tensormove_set = re.findall('= TensorMove', content2)
+        context.set_context(save_graphs=False)
+        try:
+            shutil.rmtree(save_path)
+        except FileNotFoundError:
+            pass
+        assert len(tensormove_set) == 3
+        assert np.all(graph_mode_grads == output_except)
 
 
 class ForwardNet2(Cell):
@@ -204,8 +242,6 @@ class ForwardNet2(Cell):
 
 @pytest.mark.level1
 @pytest.mark.platform_x86_gpu_training
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_onecard
 def test_load_convert_tensormove_2():
     """
@@ -213,9 +249,17 @@ def test_load_convert_tensormove_2():
     Description: record the value of load.
     Expectation: No exception.
     """
-    graph_forword_net = ForwardNet2()
-    forward_res = graph_forword_net()
-    assert forward_res == 3
+    if ms.context.get_context('mode') == 0:
+        os.environ['MS_DEV_SIDE_EFFECT_LOAD_ELIM'] = '1'
+        save_path = "./test_load_convert_tensormove2"
+        context.set_context(save_graphs=True, save_graphs_path=save_path)
+        graph_forword_net = ForwardNet2()
+        forward_res = graph_forword_net()
+        assert forward_res == 3
+        content = read_file(save_path)
+        tensormove_set = re.findall('= TensorMove', content)
+        context.set_context(save_graphs=False)
+        assert len(tensormove_set) == 3
 
 
 @pytest.mark.level1

tests/st/auto_monad/test_auto_moned_not_convert_tensormove.py

@@ -0,0 +1,103 @@
+# Copyright 2024 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 os
+import re
+import shutil
+import pytest
+import numpy as np
+from mindspore.nn import Cell
+from mindspore import context, Tensor, Parameter
+from mindspore.ops import functional as F
+from mindspore.ops import composite as C
+import mindspore as ms
+
+context.set_context(mode=context.GRAPH_MODE)
+
+
+class ForwardNet(Cell):
+    def __init__(self):
+        super(ForwardNet, self).__init__()
+        self.weight = Parameter(Tensor(np.array(0), ms.int32), name="param")
+
+    def construct(self, x):
+        out = 0
+        i = 0
+        while i < 3:
+            F.assign(self.weight, i)
+            out = x * self.weight + out
+            i = i + 1
+        return out
+
+
+class BackwardNet(Cell):
+    def __init__(self, net):
+        super(BackwardNet, self).__init__(auto_prefix=False)
+        self.forward_net = net
+        self.grad = C.GradOperation(get_all=True)
+
+    def construct(self, *inputs):
+        grads = self.grad(self.forward_net)(*inputs)
+        return grads
+
+
+def clean_all_ir_files(folder_path):
+    if os.path.exists(folder_path):
+        for file_name in os.listdir(folder_path):
+            if file_name.endswith('.ir') or file_name.endswith('.dot') or \
+                    file_name.endswith('.dat') or file_name.endswith('.pb'):
+                os.remove(os.path.join(folder_path, file_name))
+
+
+def find_newest_validateir_file(folder_path):
+    ckpt_files = map(lambda f: os.path.join(folder_path, f),
+                     filter(lambda f: re.match(r'\d+_auto_monad_reorder_\d+.ir', f),
+                            os.listdir(folder_path)))
+    return max(ckpt_files, key=os.path.getctime)
+
+
+def read_file(save_path):
+    filename = find_newest_validateir_file(save_path)
+    with open((os.path.join(filename)), 'r') as f:
+        content = f.read()
+    clean_all_ir_files(save_path)
+    return content
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_load_not_convert_tensormove():
+    """
+    Feature: Auto monad feature: record the value of load.
+    Description: record the value of load.
+    Expectation: No exception.
+    """
+
+    if ms.context.get_context('mode') == 0:
+        # Do not covert tensormove, the result may be incorrect.
+        os.environ['MS_DEV_SIDE_EFFECT_LOAD_ELIM'] = '3'
+        save_path = "./test_load_not_convert_tensormove"
+        context.set_context(save_graphs=True, save_graphs_path=save_path)
+        x = Tensor(np.array(1), ms.int32)
+        graph_forword_net = ForwardNet()
+        graph_backword_net = BackwardNet(graph_forword_net)
+        graph_backword_net(x)
+        content = read_file(save_path)
+        tensormove_set = re.findall('= TensorMove', content)
+        try:
+            shutil.rmtree(save_path)
+        except FileNotFoundError:
+            pass
+        assert not tensormove_set