未验证 提交 2aa738c1 编写于 作者: Z Zhang Zheng 提交者: GitHub

Fix CI error of resnet test with prim/cinn/prim+cinn in CUDA11.8 (#56105)

* Fix CI error of resnet test with prim/cinn/prim+cinn

* fix

* fix ref_result
上级 496422e9
......@@ -8,19 +8,19 @@ foreach(TEST_OP ${TEST_OPS})
py_test_modules(${TEST_OP} MODULES ${TEST_OP} ENVS ${GC_ENVS})
endforeach()
#set_tests_properties(test_resnet_prim PROPERTIES TIMEOUT 850)
set_tests_properties(test_resnet_prim PROPERTIES TIMEOUT 850)
set_tests_properties(test_bert_prim PROPERTIES TIMEOUT 500)
set_tests_properties(test_prim_simplenet_cinn PROPERTIES TIMEOUT 120)
if(WITH_CINN)
#set_tests_properties(test_resnet_cinn PROPERTIES TIMEOUT 850)
#set_tests_properties(test_resnet_prim_cinn PROPERTIES TIMEOUT 850)
set_tests_properties(test_resnet_cinn PROPERTIES TIMEOUT 850)
set_tests_properties(test_resnet_prim_cinn PROPERTIES TIMEOUT 850)
set_tests_properties(test_bert_cinn PROPERTIES TIMEOUT 500)
set_tests_properties(test_bert_prim_cinn PROPERTIES TIMEOUT 500)
#set_tests_properties(test_resnet_prim PROPERTIES LABELS "RUN_TYPE=CINN")
#set_tests_properties(test_resnet_cinn PROPERTIES LABELS "RUN_TYPE=CINN")
#set_tests_properties(test_resnet_prim_cinn PROPERTIES LABELS "RUN_TYPE=CINN")
set_tests_properties(test_resnet_prim PROPERTIES LABELS "RUN_TYPE=CINN")
set_tests_properties(test_resnet_cinn PROPERTIES LABELS "RUN_TYPE=CINN")
set_tests_properties(test_resnet_prim_cinn PROPERTIES LABELS "RUN_TYPE=CINN")
set_tests_properties(test_bert_prim PROPERTIES LABELS "RUN_TYPE=CINN")
set_tests_properties(test_bert_cinn PROPERTIES LABELS "RUN_TYPE=CINN")
set_tests_properties(test_bert_prim_cinn PROPERTIES LABELS "RUN_TYPE=CINN")
......
......@@ -45,16 +45,16 @@ epoch_num = 1
# note: Version 2.0 momentum is fused to OP when L2Decay is available, and the results are different from the fluid version.
# The results in ci as as follows:
DY2ST_CINN_GT = [
5.828789710998535,
8.340764999389648,
4.998946666717529,
8.4613676071167,
8.033733367919922,
7.352842807769775,
9.8336181640625,
8.22379207611084,
8.195695877075195,
10.508796691894531,
5.847333908081055,
8.347576141357422,
5.1415300369262695,
8.373777389526367,
8.05331802368164,
7.437496185302734,
9.630914688110352,
8.547889709472656,
8.343082427978516,
10.203847885131836,
]
if core.is_compiled_with_cuda():
......
......@@ -46,16 +46,16 @@ epoch_num = 1
# note: Version 2.0 momentum is fused to OP when L2Decay is available, and the results are different from the fluid version.
# The results in ci as as follows:
DY2ST_PRIM_GT = [
5.82879114151001,
8.33370590209961,
5.104889392852783,
8.546337127685547,
8.263965606689453,
7.413934230804443,
9.569124221801758,
8.251557350158691,
8.513609886169434,
10.603094100952148,
5.847333908081055,
8.368712425231934,
4.989010334014893,
8.523179054260254,
7.997398376464844,
7.601831436157227,
9.777579307556152,
8.428393363952637,
8.581992149353027,
10.313587188720703,
]
if core.is_compiled_with_cuda():
......
......@@ -46,17 +46,18 @@ epoch_num = 1
# note: Version 2.0 momentum is fused to OP when L2Decay is available, and the results are different from the fluid version.
# The results in ci as as follows:
DY2ST_PRIM_CINN_GT = [
5.828786849975586,
8.332863807678223,
5.041562080383301,
8.514982223510742,
7.9860992431640625,
7.491837501525879,
9.559739112854004,
8.430597305297852,
8.109201431274414,
10.224763870239258,
5.847333908081055,
8.342670440673828,
5.130363941192627,
8.511886596679688,
8.13458251953125,
7.35969352722168,
9.874241828918457,
8.126291275024414,
8.637175559997559,
10.385666847229004,
]
if core.is_compiled_with_cuda():
paddle.set_flags({'FLAGS_cudnn_deterministic': True})
......
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