chore: import upstream snapshot with attribution

test/legacy_test/test_count_nonzero_api.py

@@ -0,0 +1,84 @@
+#   Copyright (c) 2022 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 unittest
+
+import numpy as np
+from op_test import get_device_place
+
+import paddle
+
+np.random.seed(10)
+
+
+class TestCountNonzeroAPI(unittest.TestCase):
+    # test paddle.tensor.math.count_nonzero
+
+    def setUp(self):
+        self.x_shape = [2, 3, 4, 5]
+        self.x = np.random.uniform(-1, 1, self.x_shape).astype(np.float32)
+        self.place = get_device_place()
+
+    def test_api_static(self):
+        paddle.enable_static()
+        with paddle.static.program_guard(paddle.static.Program()):
+            x = paddle.static.data('X', self.x_shape)
+            out1 = paddle.count_nonzero(x)
+            out2 = paddle.tensor.count_nonzero(x)
+            out3 = paddle.tensor.math.count_nonzero(x)
+            axis = np.arange(len(self.x_shape)).tolist()
+            out4 = paddle.count_nonzero(x, axis)
+            out5 = paddle.count_nonzero(x, tuple(axis))
+            exe = paddle.static.Executor(self.place)
+            res = exe.run(
+                feed={'X': self.x}, fetch_list=[out1, out2, out3, out4, out5]
+            )
+        out_ref = np.count_nonzero(self.x)
+        for out in res:
+            np.testing.assert_allclose(out, out_ref, rtol=1e-05)
+
+    def test_api_dygraph(self):
+        paddle.disable_static(self.place)
+
+        def test_case(x, axis=None, keepdim=False):
+            x_tensor = paddle.to_tensor(x)
+            out = paddle.count_nonzero(x_tensor, axis=axis, keepdim=keepdim)
+            if isinstance(axis, list):
+                axis = tuple(axis)
+                if len(axis) == 0:
+                    axis = None
+
+            out_ref = np.count_nonzero(x, axis, keepdims=keepdim)
+            np.testing.assert_allclose(out.numpy(), out_ref, rtol=1e-05)
+
+        test_case(self.x)
+        test_case(self.x, None)
+        test_case(self.x, -1)
+        test_case(self.x, keepdim=True)
+        test_case(self.x, 2, keepdim=True)
+        test_case(self.x, [0, 2])
+        test_case(self.x, (0, 2))
+        test_case(self.x, (0, 1, 3))
+        test_case(self.x, [0, 1, 2, 3])
+        paddle.enable_static()
+
+    def test_errors(self):
+        paddle.enable_static()
+        with paddle.static.program_guard(paddle.static.Program()):
+            x = paddle.static.data('X', [10, 12], 'int32')
+            self.assertRaises(ValueError, paddle.count_nonzero, x, axis=10)
+
+
+if __name__ == "__main__":
+    unittest.main()