add paddle.std api (#23825)
* add paddle.std api test=develop * update test=develop * fix example code format test=developrevert-22778-infer_var_type
parent
f0e743f136
commit
f5fac6fdb2
@ -0,0 +1,80 @@
|
||||
# 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.
|
||||
|
||||
import unittest
|
||||
import numpy as np
|
||||
import paddle
|
||||
import paddle.fluid as fluid
|
||||
|
||||
|
||||
class TestStdLayer(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self._dtype = "float64"
|
||||
self._input = np.random.random([2, 3, 4, 5]).astype(self._dtype)
|
||||
|
||||
def static(self, axis=None, keepdim=False, unbiased=True):
|
||||
prog = fluid.Program()
|
||||
with fluid.program_guard(prog):
|
||||
data = fluid.data(
|
||||
name="data", dtype=self._dtype, shape=[None, 3, 4, 5])
|
||||
out = prog.current_block().create_var(
|
||||
dtype=self._dtype, shape=[2, 3, 4, 5])
|
||||
paddle.std(input=data,
|
||||
axis=axis,
|
||||
keepdim=keepdim,
|
||||
unbiased=unbiased,
|
||||
out=out)
|
||||
|
||||
exe = fluid.Executor(self._place)
|
||||
return exe.run(feed={"data": self._input},
|
||||
program=prog,
|
||||
fetch_list=[out])[0]
|
||||
|
||||
def dynamic(self, axis=None, keepdim=False, unbiased=True):
|
||||
with fluid.dygraph.guard(self._place):
|
||||
data = fluid.dygraph.to_variable(self._input)
|
||||
out = paddle.std(input=data,
|
||||
axis=axis,
|
||||
keepdim=keepdim,
|
||||
unbiased=unbiased)
|
||||
return out.numpy()
|
||||
|
||||
def numpy(self, axis=None, keepdim=False, unbiased=True):
|
||||
ddof = 1 if unbiased else 0
|
||||
axis = tuple(axis) if isinstance(axis, list) else axis
|
||||
return np.std(self._input, axis=axis, keepdims=keepdim, ddof=ddof)
|
||||
|
||||
def test_equal(self):
|
||||
places = []
|
||||
if fluid.core.is_compiled_with_cuda():
|
||||
places.append(fluid.CUDAPlace(0))
|
||||
for place in places:
|
||||
self._place = place
|
||||
self.assertTrue(np.allclose(self.numpy(), self.static()))
|
||||
self.assertTrue(
|
||||
np.allclose(
|
||||
self.numpy(axis=[0, 2]), self.dynamic(axis=[0, 2])))
|
||||
self.assertTrue(
|
||||
np.allclose(
|
||||
self.numpy(
|
||||
axis=[1, 3], keepdim=True),
|
||||
self.dynamic(
|
||||
axis=[1, 3], keepdim=True)))
|
||||
self.assertTrue(
|
||||
np.allclose(
|
||||
self.numpy(unbiased=False), self.dynamic(unbiased=False)))
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
Loading…
Reference in new issue