[CI] Port ut test_decomp.py from pytorch

test/xpu/run_test_with_only.py

@@ -42,7 +42,59 @@ def launch_test(test_case, skip_list=None, exe_list=None):
     "test_comprehensive_nn_functional_nll_loss_xpu_float64",
     "bincount",
 )
-res += launch_test("test_decomp_xpu.py", exe_list=execute_list)
+skip_list = (
+    "test_comprehensive_baddbmm_xpu_float64",
+    "test_comprehensive_logspace_tensor_overload_xpu_int16",
+    "test_comprehensive_logspace_tensor_overload_xpu_int32",
+    "test_comprehensive_logspace_tensor_overload_xpu_int64",
+    "test_comprehensive_logspace_xpu_int16",
+    "test_comprehensive_logspace_xpu_int32",
+    "test_comprehensive_logspace_xpu_int64",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_bfloat16",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_complex128",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_complex32",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_complex64",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_float16",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_float32",
+    "test_comprehensive_nn_functional_conv_transpose2d_xpu_float64",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_bfloat16",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_complex128",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_complex32",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_complex64",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_float16",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_float32",
+    "test_comprehensive_nn_functional_conv_transpose3d_xpu_float64",
+    "test_comprehensive_nn_functional_instance_norm_xpu_float64",
+    "test_comprehensive_nn_functional_nll_loss_xpu_float16",
+    "test_comprehensive_nn_functional_pad_reflect_xpu_bfloat16",
+    "test_comprehensive_torch_ops_aten__flash_attention_forward_xpu_float16",
+    "test_comprehensive_vdot_xpu_complex128",
+    "test_comprehensive_vdot_xpu_complex64",
+    "test_quick_addmm_xpu_float64",
+    "test_quick_baddbmm_xpu_float64",
+    "test_quick_core_backward_baddbmm_xpu_float64",
+    "test_quick_core_backward_mv_xpu_float64",
+    "test_quick_logspace_tensor_overload_xpu_int16",
+    "test_quick_logspace_tensor_overload_xpu_int32",
+    "test_quick_logspace_tensor_overload_xpu_int64",
+    "test_quick_logspace_xpu_int16",
+    "test_quick_logspace_xpu_int32",
+    "test_quick_logspace_xpu_int64",
+    "test_quick_vdot_xpu_complex128",
+    "test_quick_vdot_xpu_complex64",
+    "test_exponential_non_inf_xpu",
+    "test_aten_core_operators",
+    "test_has_decomposition",
+    "test_comprehensive_diff_xpu_complex128",
+    "test_comprehensive_ormqr_xpu_complex128",
+    "test_quick_var_mean_xpu_float64",
+    "test_comprehensive_diff_xpu_complex64",
+    "test_comprehensive_ormqr_xpu_complex64",
+    "test_quick_mean_xpu_complex128",
+    "test_comprehensive_grid_sampler_2d_xpu_bfloat16",
+)
+# res += launch_test("test_decomp_xpu.py", exe_list=execute_list)
+res += launch_test("test_decomp.py", skip_list=skip_list)
 
 if os.name == "nt":
     sys.exit(res)

test/xpu/run_test_with_skip.py

@@ -13,29 +13,112 @@
     default="selected",
     help="Test cases scope",
 )
+# Add skip-cases parameter to import window skip dictionary
+parser.add_argument(
+    "--skip-cases",
+    action="store_true",
+    default=False,
+    help="Use window skip dictionary for test cases",
+)
 args = parser.parse_args()
 
 
+def should_skip_entire_file(skip_list):
+    """Check if the skip list contains any entire file skip pattern (*.py::)"""
+    if not skip_list:
+        return False
+    return any(item.endswith(".py::") for item in skip_list)
+
+
+# Import window skip dictionary if skip-cases is True
+if args.skip_cases:
+    try:
+        # Import the window skip dictionary module
+        from window_skip_dict import skip_dict as window_skip_dict
+
+        # Merge the window skip dictionary with the default one using intelligent strategy
+        merged_skip_dict = {}
+
+        # First, copy all keys from default skip_dict
+        for key in skip_dict:
+            merged_skip_dict[key] = skip_dict[key].copy() if skip_dict[key] else []
+
+        # Then merge with window_skip_dict using intelligent strategy
+        for key in window_skip_dict:
+            window_skip_list = window_skip_dict[key]
+
+            if key in merged_skip_dict:
+                default_skip_list = merged_skip_dict[key]
+
+                # Intelligent merge strategy:
+                if should_skip_entire_file(window_skip_list):
+                    # If Windows wants to skip entire file, use ONLY Windows skip list
+                    merged_skip_dict[key] = window_skip_list
+                    print(
+                        f"Windows entire file skip detected for {key}, using: {window_skip_list}"
+                    )
+                else:
+                    # Otherwise, merge both lists and remove duplicates
+                    combined_list = default_skip_list + [
+                        item
+                        for item in window_skip_list
+                        if item not in default_skip_list
+                    ]
+                    merged_skip_dict[key] = combined_list
+                    print(f"Windows merging skip lists for {key}: {combined_list}")
+            else:
+                # Add new key-value pair from window_skip_dict
+                merged_skip_dict[key] = window_skip_list
+                print(f"Windows adding new skip key: {key} with {window_skip_list}")
+
+        print("Using intelligently merged skip dictionary")
+
+    except ImportError:
+        print(
+            "Warning: window_skip_dict module not found, using default skip dictionary"
+        )
+        merged_skip_dict = skip_dict
+    except Exception as e:
+        print(f"Error importing window skip dictionary: {e}")
+        merged_skip_dict = skip_dict
+else:
+    merged_skip_dict = skip_dict
+    print("Using default skip dictionary")
+
 res = 0
 fail_test = []
 
-for key in skip_dict:
-    skip_list = skip_dict[key]
+for key in merged_skip_dict:
+    skip_list = merged_skip_dict[key]
     exe_list = None
+
     if args.test_cases == "skipped":
+        # When running only skipped cases, use skip_list as exe_list
         exe_list = skip_list
         skip_list = None
-        if exe_list is None:
+        if not exe_list:  # Check if exe_list is empty
+            print(f"Skipping {key} as no tests to execute")
             continue
     elif args.test_cases == "all":
+        # When running all cases, don't skip any
         skip_list = None
+    # For "selected" case, use the skip_list as is
+
+    print(f"Running test case: {key}")
+    if skip_list:
+        print(f"Skip list: {skip_list}")
+    if exe_list:
+        print(f"Execute list: {exe_list}")
+
     fail = launch_test(key, skip_list=skip_list, exe_list=exe_list)
     res += fail
     if fail:
         fail_test.append(key)
+
 if fail_test:
     print(",".join(fail_test) + " have failures")
-
+else:
+    print("All tests passed!")
 
 if os.name == "nt":
     sys.exit(res)

test/xpu/skip_list_common.py

@@ -737,6 +737,70 @@
         # CUDA specific case
         "test_cufft_plan_cache_xpu_float64",
     ),
+    "test_decomp.py": (
+        #  AssertionError: Tensor-likes are not close! ; Exception: Tensor-likes are not close!
+        "test_comprehensive_baddbmm_xpu_float64",
+        "test_comprehensive_logspace_tensor_overload_xpu_int16",
+        "test_comprehensive_logspace_tensor_overload_xpu_int32",
+        "test_comprehensive_logspace_tensor_overload_xpu_int64",
+        "test_comprehensive_logspace_xpu_int16",
+        "test_comprehensive_logspace_xpu_int32",
+        "test_comprehensive_logspace_xpu_int64",
+        #  RuntimeError: could not create a primitive descriptor for the deconvolution forward propagation primitive.
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_bfloat16",
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_complex128",
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_complex32",
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_complex64",
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_float16",
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_float32",
+        "test_comprehensive_nn_functional_conv_transpose2d_xpu_float64",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_bfloat16",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_complex128",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_complex32",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_complex64",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_float16",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_float32",
+        "test_comprehensive_nn_functional_conv_transpose3d_xpu_float64",
+        #  AssertionError: Tensor-likes are not close! ; Exception: Tensor-likes are not close!
+        "test_comprehensive_nn_functional_instance_norm_xpu_float64",
+        #  RuntimeError: Difference from float64 is larger with decomposition nll_loss_forward.default than original on output 0.
+        "test_comprehensive_nn_functional_nll_loss_xpu_float16",
+        "test_comprehensive_nn_functional_pad_reflect_xpu_bfloat16",
+        #  NotImplementedError: Could not run 'aten::_flash_attention_forward' with arguments from the 'CPU' backend.
+        "test_comprehensive_torch_ops_aten__flash_attention_forward_xpu_float16",
+        #  AssertionError: Scalars are not close! ; Exception: Scalars are not close!
+        "test_comprehensive_vdot_xpu_complex128",
+        "test_comprehensive_vdot_xpu_complex64",
+        #  AssertionError: Tensor-likes are not close! ; Exception: Tensor-likes are not close!
+        "test_quick_addmm_xpu_float64",
+        "test_quick_baddbmm_xpu_float64",
+        "test_quick_core_backward_baddbmm_xpu_float64",
+        # Exception: Jacobian mismatch for output 0 with respect to input 0
+        "test_quick_core_backward_mv_xpu_float64",
+        #  AssertionError: Tensor-likes are not equal! ; Exception: Tensor-likes are not equal!
+        "test_quick_logspace_tensor_overload_xpu_int16",
+        "test_quick_logspace_tensor_overload_xpu_int32",
+        "test_quick_logspace_tensor_overload_xpu_int64",
+        "test_quick_logspace_xpu_int16",
+        "test_quick_logspace_xpu_int32",
+        "test_quick_logspace_xpu_int64",
+        #  AssertionError: Scalars are not close! ; Exception: Scalars are not close!
+        "test_quick_vdot_xpu_complex128",
+        "test_quick_vdot_xpu_complex64",
+        #  AssertionError: Tensor-likes are not close!
+        "test_exponential_non_inf_xpu",
+        #  RuntimeError: I got this output for HasDecompTest.test_aten_core_operators:
+        "test_aten_core_operators",
+        "test_has_decomposition",
+        #  AssertionError: Tensor-likes are not close!
+        "test_comprehensive_diff_xpu_complex128",
+        "test_comprehensive_ormqr_xpu_complex128",
+        "test_quick_var_mean_xpu_float64",
+        "test_comprehensive_diff_xpu_complex64",
+        "test_comprehensive_ormqr_xpu_complex64",
+        "test_quick_mean_xpu_complex128",
+        "test_comprehensive_grid_sampler_2d_xpu_bfloat16",
+    ),
     "functorch/test_ops_xpu.py": None,
     "test_sparse_xpu.py": None,
     "test_sparse_csr_xpu.py": None,