[Metax] update metax CI CMakeLists & scripts

.github/workflows/metax_work.yaml

@@ -51,4 +51,4 @@ jobs:
       - name: run test
         run: |
           cd backends/metax_gpu/tests
-          bash run_test.sh
+          bash run_test.sh -j 16

backends/metax_gpu/tests/CMakeLists.txt

@@ -47,6 +47,8 @@ if(NOT TEST_LIST_FILE)
   list(
     REMOVE_ITEM
     PYTHON_TEST_SCRIPTS
+    # Metax unit test
+    ${METAX_UNIT_TEST_PATH}/test_matmul_op__metax.py
     # 精度问题
     ${PADDLE_LEGACY_TEST_PATH}/test_sum_op.py
     ${PADDLE_LEGACY_TEST_PATH}/test_max_op.py
@@ -101,5 +103,5 @@ foreach(test_script ${PYTHON_TEST_SCRIPTS})
       WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
   endif()
 
-  set_tests_properties("python_${test_name}" PROPERTIES TIMEOUT 360)
+  set_tests_properties("python_${test_name}" PROPERTIES TIMEOUT 600)
 endforeach()

backends/metax_gpu/tests/run_test.sh

@@ -33,7 +33,7 @@ mkdir -p build && cd build
 TEST_LOG_LEVEL=0
 TEST_LIST_FILE=""
 TEST_LOG_OUTPUT_DIR=""
-TEST_PARALLEL_NUM=10
+TEST_PARALLEL_NUM=1
 
 while getopts "i:o:v:j:h" opt; do
   case "$opt" in

backends/metax_gpu/tests/scripts/classify.json

@@ -7,13 +7,38 @@
 
     "FAILED":{
         "precision":{
-            "rule":["Mismatched elements"]
+            "rule":["Mismatched elements",
+            "RuntimeError: Jacobian mismatch for output 0 in y with respect to input 0 in x on Place(metax_gpu:0),",
+            "AssertionError: np.float64("]
         },
         "api":{
-            "rule":["(PermissionDenied) Cannot use CUDAPinnedPlace", "ValueError: The API paddle.device.cuda.get_device_properties", "TypeError: paddle.index_add api"]
+            "rule":["(PermissionDenied) Cannot use CUDAPinnedPlace",
+            "ValueError: The API paddle.device.cuda.get_device_properties",
+            "TypeError: paddle.index_add api",
+            "RuntimeError: (Unavailable) Paddle is not compiled with CUDA.",
+            "ValueError: invalid literal for int() with base",
+            "AttributeError: module 'paddle.base.libpaddle' has no attribute 'cudnn_version'",
+            "RuntimeError: Pinning memory is not supported for Place(metax_gpu:0)",
+            "PreconditionNotMetError: Context place error, excepted GPUPlace, but actually Place(metax_gpu:0).",
+            "AttributeError: module 'paddle.base.libpaddle.eager.ops.legacy' has no attribute 'fused_gemm_epilogue'",
+            "ValueError: The device should not be 'gpu', since PaddlePaddle is not compiled with CUDA"]
         },
         "missing":{
-            "rule":["missing metax_gpu kernel", "UnimplementedError: There are no kernels which are registered"]
+            "rule":["missing metax_gpu kernel",
+            "missing ONEDNN kernel",
+            "UnimplementedError: There are no kernels which are registered",
+            "symbol lookup error:",
+            "RuntimeError: (NotFound) The kernel"]
+        },
+        "core_dumped":{
+            "rule":["Segmentation fault"]
+        },
+        "input_dim":{
+            "rule":["ValueError: (InvalidArgument) The Input(",
+            "Test range of input is out of bound"]
+        },
+        "array_dim":{
+            "rule":["Arrays are not equal"]
         },
         "file_not_found":{
             "rule":["FileNotFoundError:"]

backends/metax_gpu/tests/scripts/log_analysis.py

@@ -153,7 +153,6 @@ def run(self):
 
                 cur_res_type = TestResult.FAILURE
                 cur_sub_type = "other"
-                pre_line = None
                 finish_early = False
 
                 try:
@@ -172,19 +171,19 @@ def run(self):
                                 if finish_early:
                                     break
 
-                            pre_line = line
                             if finish_early:
                                 break
 
-                        if "OK" in pre_line:
-                            cur_res_type = TestResult.OK
-                            cur_sub_type = None
-                            for sub_type, sub_type_params in self.__classify_data[
-                                cur_res_type.value
-                            ].items():
-                                for rule in sub_type_params["rule"]:
-                                    if rule in line:
-                                        cur_sub_type = sub_type
+                            if len(line) >= 2 and line[:2] == "OK":
+                                cur_res_type = TestResult.OK
+                                cur_sub_type = None
+                                for sub_type, sub_type_params in self.__classify_data[
+                                    cur_res_type.value
+                                ].items():
+                                    for rule in sub_type_params["rule"]:
+                                        if rule in line:
+                                            cur_sub_type = sub_type
+                                break
 
                         op_name = filename.split(".")
                         if cur_sub_type is None: