chore: import upstream snapshot with attribution

test/dygraph_to_static/test_lambda.py

@@ -0,0 +1,122 @@
+#   Copyright (c) 2020 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 dygraph_to_static_utils import (
+    Dy2StTestBase,
+)
+
+import paddle
+import paddle.nn.functional as F
+
+
+def call_lambda_as_func(x):
+    x = paddle.to_tensor(x)
+
+    add_func = lambda x, y: x + y
+    mean_func = lambda x: paddle.mean(x)
+
+    y = add_func(x, 1)
+    y = add_func(y, add_func(y, -1))
+    out = mean_func(y)
+
+    return out
+
+
+def call_lambda_directly(x):
+    x = paddle.to_tensor(x)
+
+    y = (lambda x, y: x + y)(x, x)
+    out = (lambda x: paddle.mean(x))(y)
+
+    return out
+
+
+def call_lambda_in_func(x):
+    x = paddle.to_tensor(x)
+
+    add_func = lambda x: x + 1
+
+    y = paddle.mean((lambda x: F.relu(x))(x))
+    out = add_func(y) if y > 1 and y < 2 else (lambda x: x**2)(y)
+
+    return out
+
+
+def call_lambda_with_if_expr(x):
+    x = paddle.to_tensor(x)
+
+    add_func = lambda x: x + 1
+
+    y = paddle.mean(x)
+    out = add_func(y) if y or y < 2 else (lambda x: x**2)(y)
+
+    return out
+
+
+def call_lambda_with_if_expr2(x):
+    x = paddle.to_tensor(x)
+
+    add_func = lambda x: x + 1
+
+    y = paddle.mean(x)
+
+    # NOTE: y is Variable, but z<2 is python bool value
+    z = 0
+    out = add_func(y) if y or z < 2 else (lambda x: x**2)(y)
+
+    return out
+
+
+class TestLambda(Dy2StTestBase):
+    def setUp(self):
+        self.x = np.random.random([10, 16]).astype('float32')
+        self.x = np.array([1, 3]).astype('float32')
+
+    def run_static(self, func):
+        return self.run_dygraph(func, to_static=True)
+
+    def run_dygraph(self, func, to_static=False):
+        x_v = paddle.to_tensor(self.x)
+        if to_static:
+            ret = paddle.jit.to_static(func)(x_v)
+        else:
+            ret = func(x_v)
+        return ret.numpy()
+
+    def test_call_lambda_as_func(self):
+        fn = call_lambda_as_func
+        np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
+
+    def test_call_lambda_directly(self):
+        fn = call_lambda_directly
+        np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
+
+    def test_call_lambda_in_func(self):
+        fn = call_lambda_in_func
+        np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
+
+    def test_call_lambda_with_if_expr(self):
+        fn = call_lambda_with_if_expr
+        np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
+
+    def test_call_lambda_with_if_expr2(self):
+        fn = call_lambda_with_if_expr2
+        np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
+
+
+if __name__ == '__main__':
+    unittest.main()