paddlepaddle--paddle/test/legacy_test/test_nextafter_op.py

#   Copyright (c) 2023 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 op_test import OpTest, get_device_place

import paddle


def ref_nextafter(x, y):
    out = np.nextafter(x, y)
    return out


class TestNextafterAPI(unittest.TestCase):
    def setUp(self):
        self.x = np.random.rand(2, 3, 4, 5).astype('float32')
        self.y = np.random.rand(2, 3, 4, 5).astype('float32')
        self.x1 = np.array([0, 0, 10]).astype("float32")
        self.y1 = np.array([np.inf, -np.inf, 10]).astype("float32")
        self.x2 = np.random.rand(100).astype("float32")
        self.y2 = np.random.rand(100).astype("float32")
        self.place = get_device_place()

    def test_static_api(self):
        paddle.enable_static()
        with paddle.static.program_guard(paddle.static.Program()):
            x = paddle.static.data(
                name='x', shape=self.x.shape, dtype='float32'
            )
            y = paddle.static.data(
                name='y', shape=self.y.shape, dtype='float32'
            )
            out = paddle.nextafter(x, y)
            exe = paddle.static.Executor(self.place)
            res = exe.run(feed={'x': self.x, 'y': self.y}, fetch_list=[out])
        out_ref = ref_nextafter(self.x, self.y)
        np.testing.assert_allclose(out_ref, res[0], rtol=1e-05)

        with paddle.static.program_guard(paddle.static.Program()):
            x1 = paddle.static.data(
                name='x', shape=self.x1.shape, dtype='float32'
            )
            y1 = paddle.static.data(
                name='y', shape=self.y1.shape, dtype='float32'
            )
            out = paddle.nextafter(x1, y1)
            exe = paddle.static.Executor(self.place)
            res = exe.run(feed={'x': self.x1, 'y': self.y1}, fetch_list=[out])
        out_ref = ref_nextafter(self.x1, self.y1)
        np.testing.assert_allclose(out_ref, res[0], rtol=1e-05)

        with paddle.static.program_guard(paddle.static.Program()):
            x2 = paddle.static.data(
                name='x', shape=self.x2.shape, dtype='float32'
            )
            y2 = paddle.static.data(
                name='y', shape=self.y2.shape, dtype='float32'
            )
            out = paddle.nextafter(x2, y2)
            exe = paddle.static.Executor(self.place)
            res = exe.run(feed={'x': self.x2, 'y': self.y2}, fetch_list=[out])
        out_ref = ref_nextafter(self.x2, self.y2)
        np.testing.assert_allclose(out_ref, res[0], rtol=1e-05)

    def test_dygraph_api(self):
        paddle.disable_static(self.place)
        x = paddle.to_tensor(self.x)
        y = paddle.to_tensor(self.y)
        out = paddle.nextafter(x, y)
        out_ref = ref_nextafter(self.x, self.y)
        np.testing.assert_allclose(out_ref, out.numpy(), rtol=1e-05)
        paddle.enable_static()


class TestNextafterOP(OpTest):
    def setUp(self):
        self.op_type = "nextafter"
        self.python_api = paddle.nextafter
        self.init_dtype()
        self.init_shape()

        x = np.random.rand(*self.x_shape).astype(self.dtype)
        y = np.random.rand(*self.y_shape).astype(self.dtype)
        out = np.nextafter(x, y)
        self.inputs = {'x': x, 'y': y}
        self.outputs = {'out': out}

    def test_check_output(self):
        self.check_output(check_pir=True, check_symbol_infer=False)

    def init_dtype(self):
        self.dtype = np.float64

    def init_shape(self):
        self.x_shape = (2,)
        self.y_shape = (2,)


class TestNextafterOPFP32(TestNextafterOP):
    def init_dtype(self):
        self.dtype = np.float32


class TestNextafterOPFP32Case1(TestNextafterOP):
    def init_dtype(self):
        self.dtype = np.float32

    def init_shape(self):
        self.x_shape = (5,)
        self.y_shape = (2, 3, 4, 5)


class TestNextafterOPFP32Case2(TestNextafterOP):
    def init_dtype(self):
        self.dtype = np.float32

    def init_shape(self):
        self.x_shape = (2, 3, 4, 5)
        self.y_shape = (1,)


class TestNextafterOPCase1(TestNextafterOP):
    def init_shape(self):
        self.x_shape = (5,)
        self.y_shape = (2, 3, 4, 5)


class TestNextafterOPCase2(TestNextafterOP):
    def init_shape(self):
        self.x_shape = (2, 3, 4, 5)
        self.y_shape = (1,)


class TestNextafterOPZeroDim1(TestNextafterOP):
    def setUp(self):
        self.op_type = "nextafter"
        self.python_api = paddle.nextafter
        self.init_dtype()

        x = np.random.rand(0, 3, 2).astype(self.dtype)
        y = np.random.rand(0, 3, 2).astype(self.dtype)
        out = np.nextafter(x, y)
        self.inputs = {'x': x, 'y': y}
        self.outputs = {'out': out}


class TestNextafterOPZeroDim2(TestNextafterOP):
    def setUp(self):
        self.op_type = "nextafter"
        self.python_api = paddle.nextafter
        self.init_dtype()

        x = np.random.rand(4, 0, 2).astype(self.dtype)
        y = np.random.rand(4, 0, 2).astype(self.dtype)
        out = np.nextafter(x, y)
        self.inputs = {'x': x, 'y': y}
        self.outputs = {'out': out}


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