[ET-VK][tests][1/N] Report disabled delegate tests as executed

backends/vulkan/test/test_vulkan_delegate.py

@@ -7,6 +7,7 @@
 # pyre-unsafe
 
 import ctypes
+import functools
 import unittest
 from typing import Tuple
 
@@ -42,6 +43,24 @@
     pass
 
 
+def disable_test(reason):
+    """Disable a test while still reporting it as executed.
+
+    Some test runners do not handle skipped results consistently, so this keeps
+    disabled tests visible in logs without using unittest.skip.
+    """
+
+    def decorator(fn):
+        @functools.wraps(fn)
+        def wrapper(*args, **kwargs):
+            print(f"DISABLED_TEST: {fn.__qualname__}: {reason}")
+            return None
+
+        return wrapper
+
+    return decorator
+
+
 def lower_module(
     model: torch.nn.Module, sample_inputs: Tuple[torch.Tensor], dynamic_shapes=None
 ) -> EdgeProgramManager:
@@ -743,7 +762,7 @@ def forward(self, x):
 
         self.lower_module_and_test_output(model, sample_inputs)
 
-    @unittest.skip(
+    @disable_test(
         "Currently this test is failing due to weird partitioning because the eq scalar"
         "operator is not supported yet. Re-enable when the operator is supported."
     )
@@ -810,7 +829,7 @@ def forward(self, x):
 
         self.lower_module_and_test_output(module, sample_inputs)
 
-    @unittest.skip(
+    @disable_test(
         "Reduce shader does not support multiple reduction axes at the moment"
     )
     def test_vulkan_backend_sum_dim_list(self):
@@ -831,7 +850,7 @@ def forward(self, x):
             sample_inputs,
         )
 
-    @unittest.skip(
+    @disable_test(
         "Reduce shader does not support multiple reduction axes at the moment"
     )
     def test_vulkan_backend_sum(self):
@@ -1028,7 +1047,7 @@ def forward(self, x):
             sample_inputs,
         )
 
-    @unittest.skip("layer norm compute shader not working with swiftshader")
+    @disable_test("layer norm compute shader not working with swiftshader")
     def test_vulkan_backend_native_layer_norm(self):
         class NativeLayerNormModule(torch.nn.Module):
             def __init__(self):
@@ -1459,7 +1478,7 @@ def forward(self, x):
             sample_inputs,
         )
 
-    @unittest.skip(
+    @disable_test(
         "Softmax shader with shared memory does not work with swiftshader due to potential swiftshader bug"
     )
     def test_vulkan_backend_softmax(self):
@@ -1480,7 +1499,7 @@ def forward(self, x):
             sample_inputs,
         )
 
-    @unittest.skip(
+    @disable_test(
         "Softmax shader with shared memory does not work with swiftshader due to potential swiftshader bug"
     )
     def test_vulkan_backend_logsoftmax(self):
@@ -1512,7 +1531,7 @@ def forward(self, x):
 
         self.lower_unary_module_and_test_output(GeluModule())
 
-    @unittest.skip(
+    @disable_test(
         "Reduce shader does not support multiple reduction axes at the moment"
     )
     def test_vulkan_backend_mean(self):
@@ -2364,7 +2383,7 @@ def apply_quantization(self):
             quantized_linear_module_gemm, sample_inputs_gemm, atol=1e-2, rtol=1e-2
         )
 
-    @unittest.skip("Cannot run on swiftshader due to no integer dot product support")
+    @disable_test("Cannot run on swiftshader due to no integer dot product support")
     def test_vulkan_backend_xnnpack_pt2e_quantized_linear_sequence(self):
         """
         Test a sequence of linear layers quantized with XNNPACK quantization config.
@@ -2439,7 +2458,7 @@ def forward(self, x):
             rtol=1e-1,
         )
 
-    @unittest.skip("Cannot run on swiftshader due to no integer dot product support")
+    @disable_test("Cannot run on swiftshader due to no integer dot product support")
     def test_vulkan_backend_xnnpack_pt2e_quantized_conv_sequence(self):
         """
         Test a sequence of convolution layers quantized with PT2E quantization.
@@ -2530,7 +2549,7 @@ def forward(self, x):
             rtol=1e-1,
         )
 
-    @unittest.skip("Cannot run on swiftshader due to no integer dot product support")
+    @disable_test("Cannot run on swiftshader due to no integer dot product support")
     def test_vulkan_backend_xnnpack_pt2e_quantized_conv_sequence_all_reduced(self):
         """
         Test a sequence of convolution layers quantized with PT2E quantization.
@@ -2610,7 +2629,7 @@ def forward(self, x):
             rtol=1e-1,
         )
 
-    @unittest.skip("Cannot run on swiftshader due to no 8-bit int support")
+    @disable_test("Cannot run on swiftshader due to no 8-bit int support")
     def test_vulkan_backend_torchao_8da4w_quantized_linear(self):
         """
         Test TorchAO 8da4w quantization (int8 dynamic activation + int4 weight) with Vulkan backend.

devtools/inspector/tests/inspector_test.py

@@ -7,6 +7,7 @@
 # pyre-unsafe
 
 import copy
+import functools
 import os
 import random
 import statistics
@@ -90,6 +91,28 @@ def forward(self, indices: torch.Tensor, values: torch.Tensor) -> torch.Tensor:
 ETRECORD_PATH = "unittest_etrecord_path"
 
 
+def disable_if(condition, reason):
+    """Disable a test when condition is true, still reporting it as executed.
+
+    Conditional analogue of unittest.skipIf that keeps disabled tests visible in
+    logs instead of producing a skipped result, which some test runners handle
+    inconsistently.
+    """
+
+    def decorator(fn):
+        if not condition:
+            return fn
+
+        @functools.wraps(fn)
+        def wrapper(*args, **kwargs):
+            print(f"DISABLED_TEST: {fn.__qualname__}: {reason}")
+            return None
+
+        return wrapper
+
+    return decorator
+
+
 # TODO: write an E2E test: create an inspector instance, mock just the file reads, and then verify the external correctness
 class TestInspector(unittest.TestCase):
     def test_perf_data(self) -> None:
@@ -1504,7 +1527,7 @@ def test_calculate_numeric_gap_with_edge_dialect_exported_program_name(self):
             self.assertIsInstance(df, pd.DataFrame)
             self.assertEqual(len(df), 1)
 
-    @unittest.skipIf(sys.platform.startswith("win"), "Skipping on Windows")
+    @disable_if(sys.platform.startswith("win"), "Skipping on Windows")
     def test_transformer_block_xnnpack_numeric_gap_within_tolerance(self):
         """
         Test that the numeric gap between AOT and runtime intermediate outputs
@@ -1693,7 +1716,7 @@ def forward(
                         f"Stack trace for {op_name} doesn't contain file info",
                     )
 
-    @unittest.skipIf(sys.platform.startswith("win"), "Skipping on Windows")
+    @disable_if(sys.platform.startswith("win"), "Skipping on Windows")
     def test_intermediate_tensor_comparison_with_torch_export(self):
         """Test intermediate tensor comparison using torch.export.export and to_edge_transform_and_lower.
 
@@ -1840,7 +1863,7 @@ def _gen_random_runtime_output(
     ) -> List[Union[None, List[torch.Tensor], bool, float, int, str, torch.Tensor]]:
         return [torch.randn(RAW_DATA_SIZE)]
 
-    @unittest.skipIf(sys.platform.startswith("win"), "Skipping on Windows")
+    @disable_if(sys.platform.startswith("win"), "Skipping on Windows")
     def test_disable_debug_handle_validation_with_symbolic_shapes(self):
         """
         Test that demonstrates the issue with symbolic shape related nodes losing from_node info