You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
70 lines
2.1 KiB
70 lines
2.1 KiB
# 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
|
|
import paddle.fluid.core as core
|
|
from op_test import OpTest
|
|
|
|
import random
|
|
|
|
|
|
class TestElementwiseModOp(OpTest):
|
|
def init_kernel_type(self):
|
|
self.use_mkldnn = False
|
|
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mod"
|
|
self.dtype = np.int32
|
|
self.axis = -1
|
|
self.init_dtype()
|
|
self.init_input_output()
|
|
self.init_kernel_type()
|
|
self.init_axis()
|
|
|
|
self.inputs = {
|
|
'X': OpTest.np_dtype_to_fluid_dtype(self.x),
|
|
'Y': OpTest.np_dtype_to_fluid_dtype(self.y)
|
|
}
|
|
self.attrs = {'axis': self.axis, 'use_mkldnn': self.use_mkldnn}
|
|
self.outputs = {'Out': self.out}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def init_input_output(self):
|
|
self.x = np.random.uniform(0, 10000, [10, 10]).astype(self.dtype)
|
|
self.y = np.random.uniform(0, 1000, [10, 10]).astype(self.dtype)
|
|
self.out = np.mod(self.x, self.y)
|
|
|
|
def init_dtype(self):
|
|
pass
|
|
|
|
def init_axis(self):
|
|
pass
|
|
|
|
|
|
class TestElementwiseModOp_scalar(TestElementwiseModOp):
|
|
def init_input_output(self):
|
|
scale_x = random.randint(0, 100000000)
|
|
scale_y = random.randint(1, 100000000)
|
|
self.x = (np.random.rand(2, 3, 4) * scale_x).astype(self.dtype)
|
|
self.y = (np.random.rand(1) * scale_y + 1).astype(self.dtype)
|
|
self.out = np.mod(self.x, self.y)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|