Fix high memory usage in autotest (#7988)

* Fix high memory usage in autotest

* restore conv3d test

Signed-off-by: daquexian <daquexian566@gmail.com>

Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>

python/oneflow/test/modules/test_conv3d.py

@@ -22,14 +22,13 @@
 
 @flow.unittest.skip_unless_1n1d()
 class TestConv3DModule(flow.unittest.TestCase):
-    # Disable this test for unknown error
-    # @autotest(n=3)
-    # def test_nn_functional_conv3d(test_case):
-    #     device = random_device()
-    #     img = torch.ones((1, 3, 224, 224, 224), requires_grad=True).to(device)
-    #     kernel = torch.ones((6, 3, 3, 3, 3), requires_grad=True).to(device)
-    #     y = torch.nn.functional.conv3d(img, kernel)
-    #     return y
+    @autotest(n=3)
+    def test_nn_functional_conv3d(test_case):
+        device = random_device()
+        img = torch.ones((1, 3, 16, 16, 16), requires_grad=True).to(device)
+        kernel = torch.ones((6, 3, 3, 3, 3), requires_grad=True).to(device)
+        y = torch.nn.functional.conv3d(img, kernel)
+        return y
 
     @autotest(n=10)
     def test_conv3d_with_random_data(test_case):

python/oneflow/test_utils/automated_test_util/torch_flow_dual_object.py

@@ -19,6 +19,7 @@
 import copy
 import os
 import warnings
+import gc
 
 import numpy as np
 import oneflow as flow
@@ -843,6 +844,10 @@ def __eq__(self, other):
         else:
             return self.pytorch == other
 
+    def __del__(self):
+        # force running gc to avoid the periodic gc related to metaclass
+        gc.collect()
+
 
 dual_modules_to_test = []
 dual_objects_to_test = []
@@ -983,6 +988,8 @@ def new_f(test_case, *args, **kwargs):
             loop_limit = successful_runs_needed * 20
             current_run = 0
             while successful_runs_needed > 0:
+                # force running gc to avoid the periodic gc related to metaclass
+                gc.collect()
                 clear_note_fake_program()
                 if current_run > loop_limit:
                     raise ValueError(