disable lightgbm tvm backend tests

tests/test_lightgbm_converter.py

@@ -1,14 +1,15 @@
 """
 Tests LightGBM converters.
 """
+import sys
 import unittest
 import warnings
 
 import numpy as np
 
 import hummingbird.ml
 from hummingbird.ml import constants
-from hummingbird.ml._utils import lightgbm_installed, onnx_runtime_installed, tvm_installed
+from hummingbird.ml._utils import lightgbm_installed, onnx_runtime_installed, tvm_installed, is_on_github_actions
 from tree_utils import gbdt_implementation_map
 
 if lightgbm_installed():
@@ -400,6 +401,10 @@ def test_lightgbm_onnx(self):
 
     # TVM backend tests.
     @unittest.skipIf(not (tvm_installed()), reason="TVM tests require TVM")
+    @unittest.skipIf(
+        ((sys.platform == "linux") and is_on_github_actions()),
+        reason="This test is flaky on Ubuntu on GitHub Actions. See https://github.com/microsoft/hummingbird/pull/709 for more info.",
+    )
     def test_lightgbm_tvm_regressor(self):
         warnings.filterwarnings("ignore")
 
@@ -417,6 +422,10 @@ def test_lightgbm_tvm_regressor(self):
             np.testing.assert_allclose(tvm_model.predict(X), model.predict(X))
 
     @unittest.skipIf(not (tvm_installed()), reason="TVM tests require TVM installed")
+    @unittest.skipIf(
+        ((sys.platform == "linux") and is_on_github_actions()),
+        reason="This test is flaky on Ubuntu on GitHub Actions. See https://github.com/microsoft/hummingbird/pull/709 for more info.",
+    )
     def test_lightgbm_tvm_classifier(self):
         warnings.filterwarnings("ignore")
 
@@ -436,6 +445,10 @@ def test_lightgbm_tvm_classifier(self):
 
     # Test TVM with large input datasets.
     @unittest.skipIf(not (tvm_installed()), reason="TVM tests require TVM installed")
+    @unittest.skipIf(
+        ((sys.platform == "linux") and is_on_github_actions()),
+        reason="This test is flaky on Ubuntu on GitHub Actions. See https://github.com/microsoft/hummingbird/pull/709 for more info.",
+    )
     def test_lightgbm_tvm_classifier_large_dataset(self):
         warnings.filterwarnings("ignore")