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Paddle/python/paddle/fluid/tests/unittests/test_erf_op.py

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# Copyright (c) 2018 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 scipy.special import erf
from op_test import OpTest
import paddle
import paddle.fluid as fluid
import paddle.fluid.dygraph as dg
class TestErfOp(OpTest):
def setUp(self):
self.op_type = "erf"
self.dtype = self._init_dtype()
self.x_shape = [11, 17]
x = np.random.uniform(-1, 1, size=self.x_shape).astype(self.dtype)
y_ref = erf(x).astype(self.dtype)
self.inputs = {'X': x}
self.outputs = {'Out': y_ref}
def _init_dtype(self):
return "float64"
def test_check_output(self):
self.check_output()
def test_check_grad(self):
self.check_grad(['X'], 'Out')
class TestErfLayer(unittest.TestCase):
def _test_case(self, place):
x = np.random.uniform(-1, 1, size=(11, 17)).astype(np.float64)
y_ref = erf(x)
with dg.guard(place) as g:
x_var = dg.to_variable(x)
y_var = fluid.layers.erf(x_var)
y_test = y_var.numpy()
self.assertTrue(np.allclose(y_ref, y_test))
def test_case(self):
self._test_case(fluid.CPUPlace())
if fluid.is_compiled_with_cuda():
self._test_case(fluid.CUDAPlace(0))
def test_name(self):
with fluid.program_guard(fluid.Program()):
x = paddle.static.data('x', [3, 4])
y = paddle.erf(x, name='erf')
self.assertTrue('erf' in y.name)
if __name__ == '__main__':
unittest.main()