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81 lines
2.9 KiB
81 lines
2.9 KiB
# 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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import paddle
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import paddle.fluid as fluid
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class TestVarianceLayer(unittest.TestCase):
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def setUp(self):
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self._dtype = "float64"
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self._input = np.random.random([2, 3, 4, 5]).astype(self._dtype)
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def static(self, axis=None, keepdim=False, unbiased=True):
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prog = fluid.Program()
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with fluid.program_guard(prog):
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data = fluid.data(
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name="data", dtype=self._dtype, shape=[None, 3, 4, 5])
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out = prog.current_block().create_var(
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dtype=self._dtype, shape=[2, 3, 4, 5])
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paddle.var(input=data,
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axis=axis,
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keepdim=keepdim,
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unbiased=unbiased,
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out=out)
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exe = fluid.Executor(self._place)
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return exe.run(feed={"data": self._input},
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program=prog,
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fetch_list=[out])[0]
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def dynamic(self, axis=None, keepdim=False, unbiased=True):
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with fluid.dygraph.guard(self._place):
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data = fluid.dygraph.to_variable(self._input)
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out = paddle.var(input=data,
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axis=axis,
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keepdim=keepdim,
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unbiased=unbiased)
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return out.numpy()
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def numpy(self, axis=None, keepdim=False, unbiased=True):
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ddof = 1 if unbiased else 0
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axis = tuple(axis) if isinstance(axis, list) else axis
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return np.var(self._input, axis=axis, keepdims=keepdim, ddof=ddof)
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def test_equal(self):
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places = [fluid.CPUPlace()]
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if fluid.core.is_compiled_with_cuda():
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places.append(fluid.CUDAPlace(0))
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for place in places:
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self._place = place
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self.assertTrue(np.allclose(self.numpy(), self.static()))
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self.assertTrue(
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np.allclose(
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self.numpy(axis=[0, 2]), self.dynamic(axis=[0, 2])))
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self.assertTrue(
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np.allclose(
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self.numpy(
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axis=[1, 3], keepdim=True),
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self.dynamic(
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axis=[1, 3], keepdim=True)))
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self.assertTrue(
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np.allclose(
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self.numpy(unbiased=False), self.dynamic(unbiased=False)))
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if __name__ == '__main__':
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unittest.main()
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