Misc fixes for MacOS. (#255)

* Change aligned_alloc -> malloc. It can fail (and does on MacOS) and is a bit over-aggressive optimization for a reference backend.
* Fixed a fragile test that prints -0.0 on MacOS.
* Fail the test (not the framework) on failure to trace (Torch on MacOS is missing features).
* Fix .so -> .dylib for compiler runtime.

frontends/pytorch/python/torch_mlir/torchscript/e2e_test/framework.py

@@ -227,9 +227,9 @@ def run_tests(tests: List[Test], config: TestConfig) -> List[TestResult]:
     """Invoke the given `Test`'s with the provided `TestConfig`."""
     results = []
     for test in tests:
-        golden_trace = _generate_golden_trace(test)
         # TODO: Precompile everything in parallel.
         try:
+            golden_trace = _generate_golden_trace(test)
             compiled = config.compile(test.program_factory())
         except Exception as e:
             results.append(

lib/RefBackend/Runtime/Runtime.cpp

@@ -488,7 +488,8 @@ RtValue refbackrt::createRtValueFromOutputArgInfo(const OutputArgInfo &info) {
     switch (info.elementType) {
     case ElementType::F32: {
       auto byteSize = numel * sizeof(float);
-      data = static_cast<void *>(aligned_alloc(32, byteSize));
+      data = static_cast<void *>(malloc(byteSize));
+      assert(data && "could not allocate tensor");
       memset(data, 0, byteSize);
       return RtValue(Tensor::create(shape, ElementType::F32, data));
       break;

python/npcomp/compiler/generic/backend/refjit.py

@@ -3,6 +3,7 @@
 #  SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 
 import os
+import platform
 
 _refjit = None
 
@@ -40,7 +41,11 @@ def is_enabled() -> bool:
 def get_runtime_libs():
   # The _refjit_resources directory is at the npcomp.compiler level.
   resources_dir = os.path.join(os.path.dirname(__file__))
-  return [os.path.join(resources_dir, "libNPCOMPCompilerRuntimeShlib.so")]
+  suffix = ".so"
+  if platform.system() == "Darwin":
+    suffix = ".dylib"
+  shlib_name = f"libNPCOMPCompilerRuntimeShlib{suffix}"
+  return [os.path.join(resources_dir, shlib_name)]
 
 
 class JitModuleInvoker:

python/npcomp/types.py

@@ -465,7 +465,7 @@ class ArrayParams:
       Traceback (most recent call last):
       ...
       ValueError: ArrayParams(dtype=Unspec) is not concrete
-      >>> ArrayParams(np.float32, (1, 2)).new_ndarray() * 0.0
+      >>> (ArrayParams(np.float32, (1, 2)).new_ndarray() * 0.0 + 1.0) * 0.0
       array([[0., 0.]], dtype=float32)
     """
     if not self.is_concrete: