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.
103 lines
3.2 KiB
103 lines
3.2 KiB
# Copyright (c) 2020 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 six
|
|
import paddle.fluid as fluid
|
|
import paddle.fluid.core as core
|
|
from paddle.fluid import Program, program_guard
|
|
from op_test import OpTest, skip_check_grad_ci
|
|
|
|
|
|
class TestMishOpError(unittest.TestCase):
|
|
def test_errors(self):
|
|
with program_guard(Program()):
|
|
# The input type must be Variable.
|
|
self.assertRaises(TypeError, fluid.layers.mish, 0.1, 20)
|
|
# The input dtype must be float16, float32, float64.
|
|
x_int32 = fluid.data(name='x_int32', shape=[12, 10], dtype='int32')
|
|
self.assertRaises(TypeError, fluid.layers.mish, x_int32, 20)
|
|
# support the input dtype is float32
|
|
x_fp16 = fluid.layers.data(
|
|
name='x_fp16', shape=[12, 10], dtype='float32')
|
|
fluid.layers.mish(x_fp16, threshold=20)
|
|
|
|
|
|
class MishTest(OpTest):
|
|
def setUp(self):
|
|
self.init_dtype()
|
|
self.init_input_shape()
|
|
self.init_input_range()
|
|
self.init_threshold()
|
|
self.op_type = "mish"
|
|
|
|
x_np = np.random.uniform(self.x_range[0], self.x_range[1],
|
|
self.x_shape).astype(self.dtype)
|
|
self.inputs = {'X': x_np}
|
|
|
|
softplus = x_np * (x_np > self.threshold) + np.exp(x_np) * \
|
|
(x_np < -self.threshold) + np.log(np.exp(x_np) + 1.) * \
|
|
(x_np >= -self.threshold) * (x_np <= self.threshold)
|
|
out_np = x_np * np.tanh(softplus)
|
|
|
|
self.outputs = {'Out': out_np}
|
|
self.attrs = {'threshold': self.threshold}
|
|
|
|
def init_dtype(self):
|
|
self.dtype = 'float32'
|
|
|
|
def init_input_shape(self):
|
|
self.x_shape = (10, 12)
|
|
|
|
def init_input_range(self):
|
|
self.x_range = [-1, 1]
|
|
|
|
def init_threshold(self):
|
|
self.threshold = 5.
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['X'], 'Out')
|
|
|
|
|
|
class MishTestUpperThresh(MishTest):
|
|
def init_input_range(self):
|
|
self.x_range = [6, 7]
|
|
|
|
|
|
class MishTestLowerThresh(MishTest):
|
|
def init_input_range(self):
|
|
self.x_range = [-7, -6]
|
|
|
|
|
|
# mish op contain calculation like: tanh, exp, log, while tanh
|
|
# may have diff on CPUPlace(see test_activation_op.py::TestTanh),
|
|
# especially when abs(x) is a large value, only check input value
|
|
# in range [-1, 1] for float64 here.
|
|
class MishTestFP64(MishTest):
|
|
def init_dtype(self):
|
|
self.dtype = 'float64'
|
|
|
|
def init_input_range(self):
|
|
self.x_range = [-1, 1]
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|