chore: import upstream snapshot with attribution

test/custom_op/test_dispatch_jit.py

@@ -0,0 +1,116 @@
+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import unittest
+
+import numpy as np
+from utils import extra_cc_args, paddle_includes
+
+import paddle
+from paddle.utils.cpp_extension import get_build_directory, load
+from paddle.utils.cpp_extension.extension_utils import run_cmd
+
+# Because Windows don't use docker, the shared lib already exists in the
+# cache dir, it will not be compiled again unless the shared lib is removed.
+file = f'{get_build_directory()}\\dispatch_op\\dispatch_op.pyd'
+if os.name == 'nt' and os.path.isfile(file):
+    cmd = f'del {file}'
+    run_cmd(cmd, True)
+
+dispatch_op = load(
+    name='dispatch_op',
+    sources=['dispatch_test_op.cc'],
+    extra_include_paths=paddle_includes,  # add for Coverage CI
+    extra_cxx_cflags=extra_cc_args,
+    verbose=True,
+)
+
+
+class TestJitDispatch(unittest.TestCase):
+    def setUp(self):
+        paddle.set_device('cpu')
+
+    def run_dispatch_test(self, func, dtype):
+        np_x = np.ones([2, 2]).astype(dtype)
+        x = paddle.to_tensor(np_x)
+        out = func(x)
+        np_x = x.numpy()
+        np_out = out.numpy()
+        self.assertTrue(dtype in str(np_out.dtype))
+        np.testing.assert_array_equal(
+            np_x,
+            np_out,
+            err_msg=f'custom op x: {np_x},\n custom op out: {np_out}',
+        )
+
+    def test_dispatch_integer(self):
+        dtypes = ["int32", "int64", "int8", "uint8", "int16"]
+        for dtype in dtypes:
+            self.run_dispatch_test(dispatch_op.dispatch_test_integer, dtype)
+
+    def test_dispatch_complex(self):
+        dtypes = ["complex64", "complex128"]
+        for dtype in dtypes:
+            self.run_dispatch_test(dispatch_op.dispatch_test_complex, dtype)
+
+    def test_dispatch_float_and_integer(self):
+        dtypes = [
+            "float32",
+            "float64",
+            "int32",
+            "int64",
+            "int8",
+            "uint8",
+            "int16",
+        ]
+        for dtype in dtypes:
+            self.run_dispatch_test(
+                dispatch_op.dispatch_test_float_and_integer, dtype
+            )
+
+    def test_dispatch_float_and_complex(self):
+        dtypes = ["float32", "float64", "complex64", "complex128"]
+        for dtype in dtypes:
+            self.run_dispatch_test(
+                dispatch_op.dispatch_test_float_and_complex, dtype
+            )
+
+    def test_dispatch_float_and_integer_and_complex(self):
+        dtypes = [
+            "float32",
+            "float64",
+            "int32",
+            "int64",
+            "int8",
+            "uint8",
+            "int16",
+            "complex64",
+            "complex128",
+        ]
+        for dtype in dtypes:
+            self.run_dispatch_test(
+                dispatch_op.dispatch_test_float_and_integer_and_complex, dtype
+            )
+
+    def test_dispatch_float_and_half(self):
+        dtypes = ["float32", "float64", "float16"]
+        for dtype in dtypes:
+            self.run_dispatch_test(
+                dispatch_op.dispatch_test_float_and_half, dtype
+            )
+
+
+if __name__ == '__main__':
+    unittest.main()