paddlepaddle--paddle/test/xpu/test_diagonal_op_xpu.py

# Copyright (c) 2022 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.


import unittest

import numpy as np
from get_test_cover_info import (
    XPUOpTestWrapper,
    create_test_class,
    get_xpu_op_support_types,
)
from op_test import skip_check_grad_ci
from op_test_xpu import XPUOpTest

import paddle

paddle.enable_static()


class XPUTestDiagonalOp(XPUOpTestWrapper):
    def __init__(self):
        self.op_name = 'diagonal'
        self.use_dynamic_create_class = False

    @skip_check_grad_ci(
        reason="xpu fill_diagonal_tensor is not implemented yet"
    )
    class TestDiagonalOp(XPUOpTest):
        def setUp(self):
            self.op_type = "diagonal"
            self.python_api = paddle.diagonal
            self.dtype = self.in_type
            self.init_config()
            self.outputs = {'Out': self.target}

        def test_check_output(self):
            self.check_output_with_place(paddle.XPUPlace(0))

        def init_config(self):
            self.case = np.random.randn(10, 5, 2).astype(self.dtype)
            self.inputs = {'Input': self.case}
            self.attrs = {'offset': 0, 'axis1': 0, 'axis2': 1}
            self.target = np.diagonal(
                self.inputs['Input'],
                offset=self.attrs['offset'],
                axis1=self.attrs['axis1'],
                axis2=self.attrs['axis2'],
            )

    class TestDiagonalOpCase1(TestDiagonalOp):
        def init_config(self):
            self.case = np.random.randn(4, 2, 4, 4).astype(self.dtype)
            self.inputs = {'Input': self.case}
            self.attrs = {'offset': -2, 'axis1': 3, 'axis2': 0}
            self.target = np.diagonal(
                self.inputs['Input'],
                offset=self.attrs['offset'],
                axis1=self.attrs['axis1'],
                axis2=self.attrs['axis2'],
            )

    class TestDiagonalOpCase2(TestDiagonalOp):
        def init_config(self):
            self.case = np.random.randn(100, 100).astype(self.dtype)
            self.inputs = {'Input': self.case}
            self.attrs = {'offset': 0, 'axis1': 0, 'axis2': 1}
            self.target = np.diagonal(
                self.inputs['Input'],
                offset=self.attrs['offset'],
                axis1=self.attrs['axis1'],
                axis2=self.attrs['axis2'],
            )

    class TestDiagonalOpCase3(TestDiagonalOp):
        def init_config(self):
            self.case = np.random.randint(0, 2, (4, 2, 4, 4)).astype('bool')
            self.inputs = {'Input': self.case}
            self.attrs = {'offset': -2, 'axis1': 3, 'axis2': 0}
            self.target = np.diagonal(
                self.inputs['Input'],
                offset=self.attrs['offset'],
                axis1=self.attrs['axis1'],
                axis2=self.attrs['axis2'],
            )

        def test_check_grad(self):
            pass

    class TestDiagonalOpCase4(TestDiagonalOp):
        def init_config(self):
            self.case = np.random.randn(100, 100).astype(self.dtype)
            self.inputs = {'Input': self.case}
            self.attrs = {'offset': 1, 'axis1': 1, 'axis2': 0}
            self.target = np.diagonal(
                self.inputs['Input'],
                offset=self.attrs['offset'],
                axis1=self.attrs['axis1'],
                axis2=self.attrs['axis2'],
            )

        def test_check_grad(self):
            pass

    class TestDiagonalOpCase5(TestDiagonalOp):
        def init_config(self):
            self.case = np.random.randn(4, 2, 4, 4).astype(self.dtype)
            self.inputs = {'Input': self.case}
            self.attrs = {'offset': -2, 'axis1': 0, 'axis2': 3}
            self.target = np.diagonal(
                self.inputs['Input'],
                offset=self.attrs['offset'],
                axis1=self.attrs['axis1'],
                axis2=self.attrs['axis2'],
            )


class TestDiagonalAPI(unittest.TestCase):
    def setUp(self):
        self.shape = [10, 3, 4]
        self.x = np.random.random((10, 3, 4)).astype(np.float32)
        self.place = paddle.XPUPlace(0)

    def test_api_static(self):
        paddle.enable_static()
        with paddle.static.program_guard(paddle.static.Program()):
            x = paddle.static.data('X', self.shape)
            out = paddle.diagonal(x)
            exe = paddle.static.Executor(self.place)
            res = exe.run(feed={'X': self.x}, fetch_list=[out])
        out_ref = np.diagonal(self.x)
        for out in res:
            np.testing.assert_allclose(out, out_ref, rtol=1e-08)

    def test_api_dygraph(self):
        paddle.disable_static(self.place)
        x_tensor = paddle.to_tensor(self.x)
        out = paddle.diagonal(x_tensor)
        out_ref = np.diagonal(self.x)
        np.testing.assert_allclose(out.numpy(), out_ref, rtol=1e-08)
        paddle.enable_static()

    def test_api_eager(self):
        paddle.disable_static(self.place)
        x_tensor = paddle.to_tensor(self.x)
        out = paddle.diagonal(x_tensor)
        out2 = paddle.diagonal(x_tensor, offset=0, axis1=2, axis2=1)
        out3 = paddle.diagonal(x_tensor, offset=1, axis1=0, axis2=1)
        out4 = paddle.diagonal(x_tensor, offset=0, axis1=1, axis2=2)
        out_ref = np.diagonal(self.x)
        np.testing.assert_allclose(out.numpy(), out_ref, rtol=1e-08)
        out2_ref = np.diagonal(self.x, offset=0, axis1=2, axis2=1)
        np.testing.assert_allclose(out2.numpy(), out2_ref, rtol=1e-08)
        out3_ref = np.diagonal(self.x, offset=1, axis1=0, axis2=1)
        np.testing.assert_allclose(out3.numpy(), out3_ref, rtol=1e-08)
        out4_ref = np.diagonal(self.x, offset=0, axis1=1, axis2=2)
        np.testing.assert_allclose(out4.numpy(), out4_ref, rtol=1e-08)

        paddle.enable_static()


support_types = get_xpu_op_support_types('diagonal')
for stype in support_types:
    create_test_class(globals(), XPUTestDiagonalOp, stype)

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