fix some build and env issues. (#111)

.github/workflows/scripts/wheelbuilder.sh

@@ -26,7 +26,7 @@ fi
 
 # Build wheels
 if [ "$GITHUB_EVENT_NAME" == "schedule" ]; then
-    python setup.py bdist_wheel --weekly_build || { echo "Building wheels failed."; exit 1; }
+    python setup.py bdist_wheel --nightly_build || { echo "Building wheels failed."; exit 1; }
 else
     python setup.py bdist_wheel || { echo "Building wheels failed."; exit 1; }
 fi

.gitignore

@@ -32,6 +32,7 @@ out/
 *.egg-info/
 .setuptools-cmake-build/
 onnxruntime-*-*-*/
+temp_*.onnx
 
 # Compiled Dynamic libraries
 *.so

setup.py

@@ -20,6 +20,12 @@ import subprocess
 
 
 TOP_DIR = os.path.dirname(__file__)
+PACKAGE_NAME = 'onnxruntime_extensions'
+
+
+if '--nightly_build' in sys.argv:
+    PACKAGE_NAME = 'ortext_nightly'
+    sys.argv.remove('--nightly_build')
 
 
 @contextmanager
@@ -153,7 +159,7 @@ with open(os.path.join(TOP_DIR, "README.md"), 'r') as f:
     long_description = long_description[start_pos:end_pos]
 
 setup(
-    name='onnxruntime_extensions',
+    name=PACKAGE_NAME,
     version=read_version(),
     packages=packages,
     package_dir=package_dir,

test/test_onnxprocess.py

@@ -36,7 +36,7 @@ class TestTorchE2E(unittest.TestCase):
             tc_sess.save_as_onnx(f, rout)
 
         m = onnx.load_model_from_string(f.getvalue())
-        onnx.save_model(m, 'range.onnx')
+        onnx.save_model(m, 'temp_range.onnx')
         fu_m = eager_op.EagerOp.from_model(m)
         result = fu_m(num)
         np.testing.assert_array_equal(result, np.array(range(num)))
@@ -52,14 +52,14 @@ class TestTorchE2E(unittest.TestCase):
             tc_sess.save_as_onnx(f, fuse_output)
 
         m = onnx.load_model_from_string(f.getvalue())
-        onnx.save_model(m, 'test00.onnx')
+        onnx.save_model(m, 'temp_test00.onnx')
         fu_m = eager_op.EagerOp.from_model(m)
         result = fu_m(input_text)
         np.testing.assert_array_equal(result, [2, 2])
 
     def test_imagenet_postprocess(self):
-        mb_core_path = "mobilev2.onnx"
-        mb_full_path = "mobilev2_full.onnx"
+        mb_core_path = 'temp_mobilev2.onnx'
+        mb_full_path = 'temp_mobilev2_full.onnx'
         dummy_input = torch.randn(10, 3, 224, 224)
         np_input = dummy_input.numpy()
         torch.onnx.export(self.mobilenet, dummy_input, mb_core_path, opset_version=11)

test/test_sentencepiece_ops.py

@@ -445,7 +445,7 @@ class TestPythonOpSentencePiece(unittest.TestCase):
             np.array([flags & 1], dtype=np.bool_),
             np.array([flags & 2], dtype=np.bool_),
             np.array([flags & 4], dtype=np.bool_))
-        self.assertEquals(tokens.tolist(), [1095, 4054, 26, 2022, 755, 99935])
+        self.assertEqual(tokens.tolist(), [1095, 4054, 26, 2022, 755, 99935])
 
 
 if __name__ == "__main__":

test/test_torch_ops.py

@@ -68,7 +68,7 @@ class TestPyTorchCustomOp(unittest.TestCase):
         self.assertIn('domain: "ai.onnx.contrib"', str(onnx_model))
 
         model = CustomInverse()
-        onnx.save_model(onnx_model, 'pytorchcustomop.onnx')
+        onnx.save_model(onnx_model, 'temp_pytorchcustomop.onnx')
         pt_outputs = model(x0, x1)
 
         run_ort = EagerOp.from_model(onnx_model)