wehub-resource-sync
123 lines
3.1 KiB
Python
123 lines
3.1 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from dygraph_to_static_utils import (
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Dy2StTestBase,
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)
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import paddle
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import paddle.nn.functional as F
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def call_lambda_as_func(x):
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x = paddle.to_tensor(x)
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add_func = lambda x, y: x + y
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mean_func = lambda x: paddle.mean(x)
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y = add_func(x, 1)
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y = add_func(y, add_func(y, -1))
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out = mean_func(y)
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return out
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def call_lambda_directly(x):
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x = paddle.to_tensor(x)
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y = (lambda x, y: x + y)(x, x)
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out = (lambda x: paddle.mean(x))(y)
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return out
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def call_lambda_in_func(x):
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x = paddle.to_tensor(x)
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add_func = lambda x: x + 1
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y = paddle.mean((lambda x: F.relu(x))(x))
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out = add_func(y) if y > 1 and y < 2 else (lambda x: x**2)(y)
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return out
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def call_lambda_with_if_expr(x):
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x = paddle.to_tensor(x)
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add_func = lambda x: x + 1
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y = paddle.mean(x)
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out = add_func(y) if y or y < 2 else (lambda x: x**2)(y)
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return out
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def call_lambda_with_if_expr2(x):
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x = paddle.to_tensor(x)
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add_func = lambda x: x + 1
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y = paddle.mean(x)
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# NOTE: y is Variable, but z<2 is python bool value
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z = 0
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out = add_func(y) if y or z < 2 else (lambda x: x**2)(y)
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return out
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class TestLambda(Dy2StTestBase):
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def setUp(self):
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self.x = np.random.random([10, 16]).astype('float32')
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self.x = np.array([1, 3]).astype('float32')
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def run_static(self, func):
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return self.run_dygraph(func, to_static=True)
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def run_dygraph(self, func, to_static=False):
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x_v = paddle.to_tensor(self.x)
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if to_static:
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ret = paddle.jit.to_static(func)(x_v)
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else:
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ret = func(x_v)
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return ret.numpy()
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def test_call_lambda_as_func(self):
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fn = call_lambda_as_func
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np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
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def test_call_lambda_directly(self):
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fn = call_lambda_directly
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np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
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def test_call_lambda_in_func(self):
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fn = call_lambda_in_func
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np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
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def test_call_lambda_with_if_expr(self):
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fn = call_lambda_with_if_expr
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np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
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def test_call_lambda_with_if_expr2(self):
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fn = call_lambda_with_if_expr2
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np.testing.assert_allclose(self.run_dygraph(fn), self.run_static(fn))
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if __name__ == '__main__':
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unittest.main()
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