test_trunc_op.py

#   Copyright (c) 2021 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.core as core
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
from paddle.fluid.framework import _test_eager_guard

paddle.enable_static()


class TestTruncOp(OpTest):
    def setUp(self):
        self.op_type = "trunc"
        self.python_api = paddle.trunc
        self.dtype = np.float64
        np.random.seed(2021)
        self.inputs = {'X': np.random.random((20, 20)).astype(self.dtype)}
        self.outputs = {'Out': (np.trunc(self.inputs['X']))}

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

    def test_check_output(self):
        self.check_output(check_eager=True)

    def test_check_grad(self):
        self.check_grad(['X'], 'Out', numeric_grad_delta=1e-5, check_eager=True)


class TestFloatTruncOp(TestTruncOp):
    def init_dtype_type(self):
        self.dtype = np.float32


class TestIntTruncOp(TestTruncOp):
    def init_dtype_type(self):
        self.dtype = np.int32


class TestTruncAPI(unittest.TestCase):
    def setUp(self):
        self.shape = [20, 20]
        self.x = np.random.random((20, 20)).astype(np.float32)
        self.place = paddle.CPUPlace()

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

    def test_api_dygraph(self):
        paddle.disable_static(self.place)
        x_tensor = paddle.to_tensor(self.x)
        out = paddle.trunc(x_tensor)
        out_ref = np.trunc(self.x)
        self.assertEqual(np.allclose(out.numpy(), out_ref, rtol=1e-08), True)
        paddle.enable_static()

    def test_api_eager(self):
        paddle.disable_static(self.place)

        with _test_eager_guard():
            x_tensor = paddle.to_tensor(self.x)
            out = paddle.trunc(x_tensor)
        out_ref = np.trunc(self.x)
        self.assertEqual(np.allclose(out.numpy(), out_ref, rtol=1e-08), True)
        paddle.enable_static()

    def test_api_eager_dygraph(self):
        with _test_eager_guard():
            self.test_api_dygraph()

    def test_errors(self):
        with paddle.static.program_guard(paddle.static.Program()):
            x = paddle.fluid.data('X', [20, 20], 'bool')
            self.assertRaises(TypeError, paddle.trunc, x)


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