Disable TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS

CMakeLists.txt

@@ -48,8 +48,14 @@ option(TORCH_MLIR_OUT_OF_TREE_BUILD "Specifies an out of tree build" OFF)
 
 # PyTorch native extension gate. If OFF, then no features which depend on
 # native extensions will be built.
+# TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS will be disabled by default shortly,
+# once some reorganizations of the testing codebase makes that possible.
 option(TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS "Enables PyTorch native extension features" ON)
-cmake_dependent_option(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER "Enables JIT IR Importer" ON TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS OFF)
+# NOTE: The JIT_IR_IMPORTER paths have become unsupportable due to age and lack of maintainers.
+# Turning this off disables the old TorchScript path, leaving FX based import as the current supported option.
+# The option will be retained for a time, and if a maintainer is interested in setting up testing for it,
+# please reach out on the list and speak up for it.
+cmake_dependent_option(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER "Enables JIT IR Importer" OFF TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS OFF)
 cmake_dependent_option(TORCH_MLIR_ENABLE_LTC "Enables LTC backend" OFF TORCH_MLIR_ENABLE_PYTORCH_EXTENSIONS OFF)
 
 option(TORCH_MLIR_ENABLE_ONNX_C_IMPORTER "Enables the ONNX C importer" OFF)

build_tools/ci/test_posix.sh

@@ -8,22 +8,6 @@ torch_version="${1:-unknown}"
 
 export PYTHONPATH="$repo_root/build/tools/torch-mlir/python_packages/torch_mlir:$repo_root/projects/pt1"
 
-echo "::group::Run Linalg e2e integration tests"
-python -m e2e_testing.main --config=linalg -v
-echo "::endgroup::"
-
-echo "::group::Run make_fx + TOSA e2e integration tests"
-python -m e2e_testing.main --config=make_fx_tosa -v
-echo "::endgroup::"
-
-echo "::group::Run TOSA e2e integration tests"
-python -m e2e_testing.main --config=tosa -v
-echo "::endgroup::"
-
-echo "::group::Run Stablehlo e2e integration tests"
-python -m e2e_testing.main --config=stablehlo -v
-echo "::endgroup::"
-
 echo "::group::Run ONNX e2e integration tests"
 python -m e2e_testing.main --config=onnx -v
 echo "::endgroup::"

projects/pt1/e2e_testing/main.py

@@ -19,13 +19,9 @@
 # Available test configs.
 from torch_mlir_e2e_test.configs import (
     LazyTensorCoreTestConfig,
-    LinalgOnTensorsBackendTestConfig,
-    StablehloBackendTestConfig,
     NativeTorchTestConfig,
     OnnxBackendTestConfig,
     TorchScriptTestConfig,
-    TosaBackendTestConfig,
-    TorchDynamoTestConfig,
     FxImporterTestConfig,
 )
 
@@ -74,12 +70,7 @@ def _get_argparse():
     config_choices = [
         "native_torch",
         "torchscript",
-        "linalg",
-        "stablehlo",
-        "make_fx_tosa",
-        "tosa",
         "lazy_tensor_core",
-        "torchdynamo",
         "onnx",
         "onnx_tosa",
         "fx_importer",
@@ -91,16 +82,16 @@ def _get_argparse():
         "-c",
         "--config",
         choices=config_choices,
-        default="linalg",
+        default="fx_importer",
         help=f"""
 Meaning of options:
-"linalg": run through torch-mlir"s default Linalg-on-Tensors backend.
-"tosa": run through torch-mlir"s default TOSA backend.
-"stablehlo": run through torch-mlir"s default Stablehlo backend.
+# "linalg": run through torch-mlir"s default Linalg-on-Tensors backend.
+# "tosa": run through torch-mlir"s default TOSA backend.
+# "stablehlo": run through torch-mlir"s default Stablehlo backend.
 "native_torch": run the torch.nn.Module as-is without compiling (useful for verifying model is deterministic; ALL tests should pass in this configuration).
 "torchscript": compile the model to a torch.jit.ScriptModule, and then run that as-is (useful for verifying TorchScript is modeling the program correctly).
 "lazy_tensor_core": run the model through the Lazy Tensor Core frontend and execute the traced graph.
-"torchdynamo": run the model through the TorchDynamo frontend and execute the graph using Linalg-on-Tensors.
+# "torchdynamo": run the model through the TorchDynamo frontend and execute the graph using Linalg-on-Tensors.
 "onnx": export to the model via onnx and reimport using the torch-onnx-to-torch path.
 "fx_importer": run the model through the fx importer frontend and execute the graph using Linalg-on-Tensors.
 "fx_importer_stablehlo": run the model through the fx importer frontend and execute the graph using Stablehlo backend.
@@ -154,23 +145,23 @@ def main():
     all_test_unique_names = set(test.unique_name for test in GLOBAL_TEST_REGISTRY)
 
     # Find the selected config.
-    if args.config == "linalg":
-        config = LinalgOnTensorsBackendTestConfig(RefBackendLinalgOnTensorsBackend())
-        xfail_set = LINALG_XFAIL_SET
-        crashing_set = LINALG_CRASHING_SET
-    elif args.config == "stablehlo":
-        config = StablehloBackendTestConfig(LinalgOnTensorsStablehloBackend())
-        xfail_set = all_test_unique_names - STABLEHLO_PASS_SET
-        crashing_set = STABLEHLO_CRASHING_SET
-    elif args.config == "tosa":
-        config = TosaBackendTestConfig(LinalgOnTensorsTosaBackend())
-        xfail_set = all_test_unique_names - TOSA_PASS_SET
-        crashing_set = TOSA_CRASHING_SET
-    elif args.config == "make_fx_tosa":
-        config = TosaBackendTestConfig(LinalgOnTensorsTosaBackend(), use_make_fx=True)
-        xfail_set = all_test_unique_names - MAKE_FX_TOSA_PASS_SET
-        crashing_set = MAKE_FX_TOSA_CRASHING_SET
-    elif args.config == "native_torch":
+    # if args.config == "linalg":
+    #     config = LinalgOnTensorsBackendTestConfig(RefBackendLinalgOnTensorsBackend())
+    #     xfail_set = LINALG_XFAIL_SET
+    #     crashing_set = LINALG_CRASHING_SET
+    # elif args.config == "stablehlo":
+    #     config = StablehloBackendTestConfig(LinalgOnTensorsStablehloBackend())
+    #     xfail_set = all_test_unique_names - STABLEHLO_PASS_SET
+    #     crashing_set = STABLEHLO_CRASHING_SET
+    # elif args.config == "tosa":
+    #     config = TosaBackendTestConfig(LinalgOnTensorsTosaBackend())
+    #     xfail_set = all_test_unique_names - TOSA_PASS_SET
+    #     crashing_set = TOSA_CRASHING_SET
+    # elif args.config == "make_fx_tosa":
+    #     config = TosaBackendTestConfig(LinalgOnTensorsTosaBackend(), use_make_fx=True)
+    #     xfail_set = all_test_unique_names - MAKE_FX_TOSA_PASS_SET
+    #     crashing_set = MAKE_FX_TOSA_CRASHING_SET
+    if args.config == "native_torch":
         config = NativeTorchTestConfig()
         xfail_set = set()
         crashing_set = set()
@@ -194,13 +185,13 @@ def main():
         config = FxImporterTestConfig(LinalgOnTensorsTosaBackend(), "tosa")
         xfail_set = FX_IMPORTER_TOSA_XFAIL_SET
         crashing_set = FX_IMPORTER_TOSA_CRASHING_SET
-    elif args.config == "torchdynamo":
-        # TODO: Enanble runtime verification and extend crashing set.
-        config = TorchDynamoTestConfig(
-            RefBackendLinalgOnTensorsBackend(generate_runtime_verification=False)
-        )
-        xfail_set = TORCHDYNAMO_XFAIL_SET
-        crashing_set = TORCHDYNAMO_CRASHING_SET
+    # elif args.config == "torchdynamo":
+    #     # TODO: Enanble runtime verification and extend crashing set.
+    #     config = TorchDynamoTestConfig(
+    #         RefBackendLinalgOnTensorsBackend(generate_runtime_verification=False)
+    #     )
+    #     xfail_set = TORCHDYNAMO_XFAIL_SET
+    #     crashing_set = TORCHDYNAMO_CRASHING_SET
     elif args.config == "onnx":
         config = OnnxBackendTestConfig(RefBackendLinalgOnTensorsBackend())
         xfail_set = ONNX_XFAIL_SET

projects/pt1/python/CMakeLists.txt

@@ -41,9 +41,11 @@ endif()
 if(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER)
   add_subdirectory(torch_mlir/jit_ir_importer)
   add_subdirectory(torch_mlir/csrc/jit_ir_importer)
+else()
   add_subdirectory(torch_mlir_e2e_test)
 endif()
 
+
 ################################################################################
 # Custom op example
 # Required for running the update_torch_ods.sh and update_abstract_interp_lib.sh
@@ -61,6 +63,10 @@ if(TORCH_MLIR_ENABLE_JIT_IR_IMPORTER)
     TorchMLIRJITIRImporterPybind
     TorchMLIRE2ETestPythonModules
   )
+else()
+  add_dependencies(TorchMLIRPythonTorchExtensionsSources
+    TorchMLIRE2ETestPythonModules
+  )
 endif()
 
 if(TORCH_MLIR_ENABLE_LTC)