wehub-resource-sync
122 lines
3.3 KiB
Python
122 lines
3.3 KiB
Python
# Copyright (c) 2021 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 op_test import OpTest, get_places
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import paddle
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import paddle.base.dygraph as dg
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class TestComplexAbsOp(OpTest):
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def setUp(self):
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paddle.enable_static()
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self.python_api = paddle.abs
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self.op_type = "abs"
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self.dtype = np.float64
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self.shape = (2, 3, 4, 5)
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self.init_input_output()
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self.inputs = {'X': OpTest.np_dtype_to_base_dtype(self.x)}
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self.outputs = {'Out': self.out}
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def init_input_output(self):
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self.x = np.random.random(self.shape).astype(
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self.dtype
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) + 1j * np.random.random(self.shape).astype(self.dtype)
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self.out = np.abs(self.x)
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(
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['X'],
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'Out',
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)
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class TestComplexAbsOpZeroValues(OpTest):
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def setUp(self):
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paddle.enable_static()
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self.op_type = "abs"
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self.python_api = paddle.abs
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self.dtype = np.float64
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self.shape = (2, 3, 4, 5)
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self.init_input_output()
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self.inputs = {'X': OpTest.np_dtype_to_base_dtype(self.x)}
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self.outputs = {'Out': self.out}
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def init_input_output(self):
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self.x = np.zeros(self.shape).astype(self.dtype) + 1j * np.zeros(
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self.shape
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).astype(self.dtype)
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self.out = np.abs(self.x)
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(
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['X'],
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'Out',
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)
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class TestAbs(unittest.TestCase):
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def setUp(self):
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self._dtypes = ["float32", "float64"]
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self._places = get_places()
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def test_all_positive(self):
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for dtype in self._dtypes:
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x = 1 + 10 * np.random.random([13, 3, 3]).astype(dtype)
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for place in self._places:
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with dg.guard(place):
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y = paddle.abs(paddle.to_tensor(x))
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np.testing.assert_allclose(np.abs(x), y.numpy(), rtol=1e-05)
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class TestRealAbsOp(OpTest):
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def setUp(self):
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paddle.enable_static()
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self.python_api = paddle.abs
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self.op_type = "abs"
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self.dtype = np.float64
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self.shape = (2, 3, 4, 5)
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self.init_input_output()
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self.inputs = {'X': OpTest.np_dtype_to_base_dtype(self.x)}
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self.outputs = {'Out': self.out}
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def init_input_output(self):
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self.x = 1 + np.random.random(self.shape).astype(self.dtype)
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self.out = np.abs(self.x)
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(
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['X'],
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'Out',
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)
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if __name__ == '__main__':
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unittest.main()
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