test_complex_view_op.py 4.3 KB
Newer Older
1
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
2
#
3 4 5
# 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
6
#
7
#     http://www.apache.org/licenses/LICENSE-2.0
8
#
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
# 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.

from __future__ import print_function

import unittest
import numpy as np
from op_test import OpTest

import paddle
from paddle.fluid import dygraph
from paddle import static
24
from paddle.fluid.framework import _test_eager_guard
25

26 27 28 29 30 31 32 33 34 35 36 37 38
paddle.enable_static()


def ref_view_as_complex(x):
    real, imag = np.take(x, 0, axis=-1), np.take(x, 1, axis=-1)
    return real + 1j * imag


def ref_view_as_real(x):
    return np.stack([x.real, x.imag], -1)


class TestViewAsComplexOp(OpTest):
39

40 41 42 43 44
    def setUp(self):
        self.op_type = "as_complex"
        x = np.random.randn(10, 10, 2).astype("float64")
        out_ref = ref_view_as_complex(x)
        self.out_grad = np.ones(
45
            [10, 10], dtype="float64") + 1j * np.ones([10, 10], dtype="float64")
46 47 48 49
        self.inputs = {'X': x}
        self.outputs = {'Out': out_ref}

    def test_check_output(self):
50
        self.check_output(check_eager=True)
51 52

    def test_check_grad(self):
53 54 55 56 57
        self.check_grad(['X'],
                        'Out',
                        user_defined_grads=[ref_view_as_real(self.out_grad)],
                        user_defined_grad_outputs=[self.out_grad],
                        check_eager=True)
58 59 60


class TestViewAsRealOp(OpTest):
61

62 63 64 65 66 67 68 69 70 71 72
    def setUp(self):
        self.op_type = "as_real"
        real = np.random.randn(10, 10).astype("float64")
        imag = np.random.randn(10, 10).astype("float64")
        x = real + 1j * imag
        out_ref = ref_view_as_real(x)
        self.inputs = {'X': x}
        self.outputs = {'Out': out_ref}
        self.out_grad = np.ones([10, 10, 2], dtype="float64")

    def test_check_output(self):
73
        self.check_output(check_eager=True)
74 75

    def test_check_grad(self):
76 77 78 79 80
        self.check_grad(['X'],
                        'Out',
                        user_defined_grads=[ref_view_as_complex(self.out_grad)],
                        user_defined_grad_outputs=[self.out_grad],
                        check_eager=True)
81 82 83


class TestViewAsComplexAPI(unittest.TestCase):
84

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105
    def setUp(self):
        self.x = np.random.randn(10, 10, 2)
        self.out = ref_view_as_complex(self.x)

    def test_dygraph(self):
        with dygraph.guard():
            x = paddle.to_tensor(self.x)
            out_np = paddle.as_complex(x).numpy()
        self.assertTrue(np.allclose(self.out, out_np))

    def test_static(self):
        mp, sp = static.Program(), static.Program()
        with static.program_guard(mp, sp):
            x = static.data("x", shape=[10, 10, 2], dtype="float64")
            out = paddle.as_complex(x)

        exe = static.Executor()
        exe.run(sp)
        [out_np] = exe.run(mp, feed={"x": self.x}, fetch_list=[out])
        self.assertTrue(np.allclose(self.out, out_np))

106 107 108 109
    def test_eager(self):
        with _test_eager_guard():
            self.test_dygraph()

110 111

class TestViewAsRealAPI(unittest.TestCase):
112

113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133
    def setUp(self):
        self.x = np.random.randn(10, 10) + 1j * np.random.randn(10, 10)
        self.out = ref_view_as_real(self.x)

    def test_dygraph(self):
        with dygraph.guard():
            x = paddle.to_tensor(self.x)
            out_np = paddle.as_real(x).numpy()
        self.assertTrue(np.allclose(self.out, out_np))

    def test_static(self):
        mp, sp = static.Program(), static.Program()
        with static.program_guard(mp, sp):
            x = static.data("x", shape=[10, 10], dtype="complex128")
            out = paddle.as_real(x)

        exe = static.Executor()
        exe.run(sp)
        [out_np] = exe.run(mp, feed={"x": self.x}, fetch_list=[out])
        self.assertTrue(np.allclose(self.out, out_np))

134 135 136 137
    def test_eager(self):
        with _test_eager_guard():
            self.test_dygraph()

138 139 140

if __name__ == "__main__":
    unittest.main()