[UnitTests][Contrib] Enable contrib tensorrt/coreml unit tests

python/tvm/testing/__init__.py

@@ -24,6 +24,7 @@
 from .utils import known_failing_targets, requires_cuda, requires_cudagraph
 from .utils import requires_gpu, requires_llvm, requires_rocm, requires_rpc
 from .utils import requires_tensorcore, requires_metal, requires_micro, requires_opencl
+from .utils import requires_package
 from .utils import identity_after, terminate_self
 
 from ._ffi_api import nop, echo, device_test, run_check_signal, object_use_count

python/tvm/testing/utils.py

@@ -774,7 +774,51 @@ def requires_rpc(*args):
     return _compose(args, _requires_rpc)
 
 
+def requires_package(*packages):
+    """Mark a test as requiring python packages to run.
+
+    If the packages listed are not available, tests marked with
+    `requires_package` will appear in the pytest results as being skipped.
+    This is equivalent to using ``foo = pytest.importorskip('foo')`` inside
+    the test body.
+
+    Parameters
+    ----------
+    packages : List[str]
+
+        The python packages that should be available for the test to
+        run.
+
+    Returns
+    -------
+    mark: pytest mark
+
+        The pytest mark to be applied to unit tests that require this
+
+    """
+
+    def has_package(package):
+        try:
+            __import__(package)
+            return True
+        except ImportError:
+            return False
+
+    marks = [
+        pytest.mark.skipif(not has_package(package), reason=f"Cannot import '{package}'")
+        for package in packages
+    ]
+
+    def wrapper(func):
+        for mark in marks:
+            func = mark(func)
+        return func
+
+    return wrapper
+
+
 def parametrize_targets(*args):
+
     """Parametrize a test over a specific set of targets.
 
     Use this decorator when you want your test to be run over a

tests/python/contrib/test_coreml_codegen.py

@@ -19,11 +19,12 @@
 from unittest import mock
 
 import tvm
+import tvm.testing
 from tvm import relay
 from tvm.relay import transform
 from tvm.contrib.target import coreml as _coreml
 
-pytest.importorskip("coremltools")
+requires_coremltools = tvm.testing.requires_package("coremltools")
 
 
 def _has_xcode():
@@ -88,6 +89,11 @@ def _create_graph_annotated():
     return mod
 
 
+@pytest.mark.xfail(
+    reason="Currently failing test.  See tracking issue https://github.com/apache/tvm/issues/8901"
+)
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_annotate():
     mod = _create_graph()
     mod = transform.AnnotateTarget("coremlcompiler")(mod)
@@ -98,6 +104,8 @@ def test_annotate():
 
 
 @pytest.mark.skipif(not _has_xcode(), reason="Xcode is not available")
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_compile_and_run():
     dev = tvm.cpu()
     target = "llvm"
@@ -136,6 +144,8 @@ def _construct_model(func, m1, m2):
             fcompile(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_add():
     shape = (10, 10)
     x = relay.var("x", shape=shape)
@@ -144,6 +154,8 @@ def test_add():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_multiply():
     shape = (10, 10)
     x = relay.var("x", shape=shape)
@@ -152,6 +164,8 @@ def test_multiply():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_clip():
     shape = (10, 10)
     x = relay.var("x", shape=shape)
@@ -160,6 +174,8 @@ def test_clip():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_batch_flatten():
     shape = (10, 10, 10)
     x = relay.var("x", shape=shape)
@@ -168,6 +184,8 @@ def test_batch_flatten():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_expand_dims():
     shape = (10, 10)
     x = relay.var("x", shape=shape)
@@ -180,6 +198,8 @@ def test_expand_dims():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_relu():
     shape = (10, 10)
     x = relay.var("x", shape=shape)
@@ -188,6 +208,8 @@ def test_relu():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_softmax():
     shape = (10, 10)
     x = relay.var("x", shape=shape)
@@ -196,6 +218,8 @@ def test_softmax():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_conv2d():
     x = relay.var("x", shape=(1, 3, 224, 224))
     w = relay.const(np.zeros((16, 3, 3, 3), dtype="float32"))
@@ -204,6 +228,8 @@ def test_conv2d():
     _construct_model(func)
 
 
+@tvm.testing.uses_gpu
+@requires_coremltools
 def test_global_avg_pool2d():
     shape = (10, 10, 10, 10)
     x = relay.var("x", shape=shape)