test_diag_v2.py 9.7 KB
Newer Older
L
LutaoChu 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
#   Copyright (c) 2019 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.

from __future__ import print_function

import unittest
import numpy as np
from op_test import OpTest
import paddle
import paddle.fluid as fluid
from paddle.fluid import core
from paddle.fluid import Program, program_guard
24
from paddle.fluid.framework import _test_eager_guard
L
LutaoChu 已提交
25 26 27 28 29


class TestDiagV2Op(OpTest):
    def setUp(self):
        self.op_type = "diag_v2"
H
hong 已提交
30
        self.python_api = paddle.diag
L
LutaoChu 已提交
31 32 33 34 35 36 37 38 39 40 41 42 43 44 45
        self.x = np.random.rand(10, 10)
        self.offset = 0
        self.padding_value = 0.0
        self.out = np.diag(self.x, self.offset)

        self.init_config()
        self.inputs = {'X': self.x}
        self.attrs = {
            'offset': self.offset,
            'padding_value': self.padding_value
        }
        self.outputs = {'Out': self.out}

    def test_check_output(self):
        paddle.enable_static()
46
        self.check_output(check_eager=False)
L
LutaoChu 已提交
47

48 49
    def test_check_grad(self):
        paddle.enable_static()
50
        self.check_grad(['X'], 'Out', check_eager=False)
51

L
LutaoChu 已提交
52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69
    def init_config(self):
        pass


class TestDiagV2OpCase1(TestDiagV2Op):
    def init_config(self):
        self.offset = 1
        self.out = np.diag(self.x, self.offset)


class TestDiagV2OpCase2(TestDiagV2Op):
    def init_config(self):
        self.offset = -1
        self.out = np.diag(self.x, self.offset)


class TestDiagV2OpCase3(TestDiagV2Op):
    def init_config(self):
70
        self.x = np.random.randint(-10, 10, size=(10, 10)).astype("float64")
L
LutaoChu 已提交
71 72 73 74 75 76
        self.out = np.diag(self.x, self.offset)


class TestDiagV2OpCase4(TestDiagV2Op):
    def init_config(self):
        self.x = np.random.rand(100)
77
        self.padding_value = 2
L
LutaoChu 已提交
78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247
        n = self.x.size
        self.out = self.padding_value * np.ones((n, n)) + np.diag(
            self.x, self.offset) - np.diag(self.padding_value * np.ones(n))


class TestDiagV2Error(unittest.TestCase):
    def test_errors(self):
        paddle.enable_static()
        with program_guard(Program(), Program()):

            def test_diag_v2_type():
                x = [1, 2, 3]
                output = paddle.diag(x)

            self.assertRaises(TypeError, test_diag_v2_type)

            x = paddle.static.data('data', [3, 3])
            self.assertRaises(TypeError, paddle.diag, x, offset=2.5)

            self.assertRaises(TypeError, paddle.diag, x, padding_value=[9])

            x = paddle.static.data('data2', [3, 3, 3])
            self.assertRaises(ValueError, paddle.diag, x)


class TestDiagV2API(unittest.TestCase):
    def setUp(self):
        self.input_np = np.random.random(size=(10, 10)).astype(np.float32)
        self.expected0 = np.diag(self.input_np)
        self.expected1 = np.diag(self.input_np, k=1)
        self.expected2 = np.diag(self.input_np, k=-1)

        self.input_np2 = np.random.rand(100)
        self.offset = 0
        self.padding_value = 8
        n = self.input_np2.size
        self.expected3 = self.padding_value * np.ones(
            (n, n)) + np.diag(self.input_np2, self.offset) - np.diag(
                self.padding_value * np.ones(n))

        self.input_np3 = np.random.randint(-10, 10, size=(100)).astype(np.int64)
        self.padding_value = 8.0
        n = self.input_np3.size
        self.expected4 = self.padding_value * np.ones(
            (n, n)) + np.diag(self.input_np3, self.offset) - np.diag(
                self.padding_value * np.ones(n))

        self.padding_value = -8
        self.expected5 = self.padding_value * np.ones(
            (n, n)) + np.diag(self.input_np3, self.offset) - np.diag(
                self.padding_value * np.ones(n))

        self.input_np4 = np.random.random(size=(2000, 2000)).astype(np.float32)
        self.expected6 = np.diag(self.input_np4)
        self.expected7 = np.diag(self.input_np4, k=1)
        self.expected8 = np.diag(self.input_np4, k=-1)

        self.input_np5 = np.random.random(size=(2000)).astype(np.float32)
        self.expected9 = np.diag(self.input_np5)
        self.expected10 = np.diag(self.input_np5, k=1)
        self.expected11 = np.diag(self.input_np5, k=-1)

        self.input_np6 = np.random.random(size=(2000, 1500)).astype(np.float32)
        self.expected12 = np.diag(self.input_np6, k=-1)

    def run_imperative(self):
        x = paddle.to_tensor(self.input_np)
        y = paddle.diag(x)
        self.assertTrue(np.allclose(y.numpy(), self.expected0))

        y = paddle.diag(x, offset=1)
        self.assertTrue(np.allclose(y.numpy(), self.expected1))

        y = paddle.diag(x, offset=-1)
        self.assertTrue(np.allclose(y.numpy(), self.expected2))

        x = paddle.to_tensor(self.input_np2)
        y = paddle.diag(x, padding_value=8)
        self.assertTrue(np.allclose(y.numpy(), self.expected3))

        x = paddle.to_tensor(self.input_np3)
        y = paddle.diag(x, padding_value=8.0)
        self.assertTrue(np.allclose(y.numpy(), self.expected4))

        y = paddle.diag(x, padding_value=-8)
        self.assertTrue(np.allclose(y.numpy(), self.expected5))

        x = paddle.to_tensor(self.input_np4)
        y = paddle.diag(x)
        self.assertTrue(np.allclose(y.numpy(), self.expected6))

        y = paddle.diag(x, offset=1)
        self.assertTrue(np.allclose(y.numpy(), self.expected7))

        y = paddle.diag(x, offset=-1)
        self.assertTrue(np.allclose(y.numpy(), self.expected8))

        x = paddle.to_tensor(self.input_np5)
        y = paddle.diag(x)
        self.assertTrue(np.allclose(y.numpy(), self.expected9))

        y = paddle.diag(x, offset=1)
        self.assertTrue(np.allclose(y.numpy(), self.expected10))

        y = paddle.diag(x, offset=-1)
        self.assertTrue(np.allclose(y.numpy(), self.expected11))

        x = paddle.to_tensor(self.input_np6)
        y = paddle.diag(x, offset=-1)
        self.assertTrue(np.allclose(y.numpy(), self.expected12))

    def run_static(self, use_gpu=False):
        x = paddle.static.data(name='input', shape=[10, 10], dtype='float32')
        x2 = paddle.static.data(name='input2', shape=[100], dtype='float64')
        x3 = paddle.static.data(name='input3', shape=[100], dtype='int64')
        x4 = paddle.static.data(
            name='input4', shape=[2000, 2000], dtype='float32')
        x5 = paddle.static.data(name='input5', shape=[2000], dtype='float32')
        x6 = paddle.static.data(
            name='input6', shape=[2000, 1500], dtype='float32')
        result0 = paddle.diag(x)
        result1 = paddle.diag(x, offset=1)
        result2 = paddle.diag(x, offset=-1)
        result3 = paddle.diag(x, name='aaa')
        result4 = paddle.diag(x2, padding_value=8)
        result5 = paddle.diag(x3, padding_value=8.0)
        result6 = paddle.diag(x3, padding_value=-8)
        result7 = paddle.diag(x4)
        result8 = paddle.diag(x4, offset=1)
        result9 = paddle.diag(x4, offset=-1)
        result10 = paddle.diag(x5)
        result11 = paddle.diag(x5, offset=1)
        result12 = paddle.diag(x5, offset=-1)
        result13 = paddle.diag(x6, offset=-1)

        place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()
        exe = fluid.Executor(place)
        exe.run(fluid.default_startup_program())
        res0, res1, res2, res4, res5, res6, res7, res8, res9, res10, res11, res12, res13 = exe.run(
            feed={
                "input": self.input_np,
                "input2": self.input_np2,
                'input3': self.input_np3,
                'input4': self.input_np4,
                'input5': self.input_np5,
                'input6': self.input_np6
            },
            fetch_list=[
                result0, result1, result2, result4, result5, result6, result7,
                result8, result9, result10, result11, result12, result13
            ])

        self.assertTrue(np.allclose(res0, self.expected0))
        self.assertTrue(np.allclose(res1, self.expected1))
        self.assertTrue(np.allclose(res2, self.expected2))
        self.assertTrue('aaa' in result3.name)
        self.assertTrue(np.allclose(res4, self.expected3))
        self.assertTrue(np.allclose(res5, self.expected4))
        self.assertTrue(np.allclose(res6, self.expected5))
        self.assertTrue(np.allclose(res7, self.expected6))
        self.assertTrue(np.allclose(res8, self.expected7))
        self.assertTrue(np.allclose(res9, self.expected8))
        self.assertTrue(np.allclose(res10, self.expected9))
        self.assertTrue(np.allclose(res11, self.expected10))
        self.assertTrue(np.allclose(res12, self.expected11))
        self.assertTrue(np.allclose(res13, self.expected12))

    def test_cpu(self):
        paddle.disable_static(place=paddle.fluid.CPUPlace())
        self.run_imperative()
248 249 250
        with _test_eager_guard():
            self.run_imperative()

L
LutaoChu 已提交
251 252 253 254 255 256 257 258 259 260 261
        paddle.enable_static()

        with fluid.program_guard(fluid.Program()):
            self.run_static()

    def test_gpu(self):
        if not fluid.core.is_compiled_with_cuda():
            return

        paddle.disable_static(place=paddle.fluid.CUDAPlace(0))
        self.run_imperative()
262 263
        with _test_eager_guard():
            self.run_imperative()
L
LutaoChu 已提交
264 265 266 267 268 269 270
        paddle.enable_static()

        with fluid.program_guard(fluid.Program()):
            self.run_static(use_gpu=True)


if __name__ == "__main__":
H
hong 已提交
271
    paddle.enable_static()
L
LutaoChu 已提交
272
    unittest.main()