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

141 lines
5.2 KiB

# 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.
import paddle
import paddle.fluid as fluid
import unittest
import numpy as np
class TestAllcloseLayer(unittest.TestCase):
def allclose_check(self, use_cuda):
a = fluid.data(name="a", shape=[2], dtype='float32')
b = fluid.data(name="b", shape=[2], dtype='float32')
result = paddle.allclose(
a, b, rtol=1e-05, atol=1e-08, equal_nan=False, name="ignore_nan")
result_nan = paddle.allclose(
a, b, rtol=1e-05, atol=1e-08, equal_nan=True, name="equal_nan")
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
x = np.array([10000., 1e-07]).astype("float32")
y = np.array([10000.1, 1e-08]).astype("float32")
result_v, result_nan_v = exe.run(feed={'a': x,
'b': y},
fetch_list=[result, result_nan])
self.assertEqual(result_v[0], False)
self.assertEqual(result_nan_v[0], False)
x = np.array([10000., 1e-08]).astype("float32")
y = np.array([10000.1, 1e-09]).astype("float32")
result_v, result_nan_v = exe.run(feed={'a': x,
'b': y},
fetch_list=[result, result_nan])
self.assertEqual(result_v[0], True)
self.assertEqual(result_nan_v[0], True)
x = np.array([1.0, float('nan')]).astype("float32")
y = np.array([1.0, float('nan')]).astype("float32")
result_v, result_nan_v = exe.run(feed={'a': x,
'b': y},
fetch_list=[result, result_nan])
self.assertEqual(result_v[0], False)
self.assertEqual(result_nan_v[0], True)
def test_allclose_cpu(self):
main = fluid.Program()
startup = fluid.Program()
with fluid.unique_name.guard():
with fluid.program_guard(main, startup):
self.allclose_check(use_cuda=False)
def test_allclose_gpu(self):
if fluid.core.is_compiled_with_cuda():
main = fluid.Program()
startup = fluid.Program()
with fluid.unique_name.guard():
with fluid.program_guard(main, startup):
self.allclose_check(use_cuda=True)
def test_dygraph_mode(self):
x_1 = np.array([10000., 1e-07]).astype("float32")
y_1 = np.array([10000.1, 1e-08]).astype("float32")
x_2 = np.array([10000., 1e-08]).astype("float32")
y_2 = np.array([10000.1, 1e-09]).astype("float32")
x_3 = np.array([1.0, float('nan')]).astype("float32")
y_3 = np.array([1.0, float('nan')]).astype("float32")
with fluid.dygraph.guard():
x_v_1 = fluid.dygraph.to_variable(x_1)
y_v_1 = fluid.dygraph.to_variable(y_1)
ret_1 = paddle.allclose(
x_v_1,
y_v_1,
rtol=1e-05,
atol=1e-08,
equal_nan=False,
name='test_1')
self.assertEqual(ret_1.numpy()[0], False)
ret_1 = paddle.allclose(
x_v_1,
y_v_1,
rtol=1e-05,
atol=1e-08,
equal_nan=True,
name='test_2')
self.assertEqual(ret_1.numpy()[0], False)
x_v_2 = fluid.dygraph.to_variable(x_2)
y_v_2 = fluid.dygraph.to_variable(y_2)
ret_2 = paddle.allclose(
x_v_2,
y_v_2,
rtol=1e-05,
atol=1e-08,
equal_nan=False,
name='test_3')
self.assertEqual(ret_2.numpy()[0], True)
ret_2 = paddle.allclose(
x_v_2,
y_v_2,
rtol=1e-05,
atol=1e-08,
equal_nan=True,
name='test_4')
self.assertEqual(ret_2.numpy()[0], True)
x_v_3 = fluid.dygraph.to_variable(x_3)
y_v_3 = fluid.dygraph.to_variable(y_3)
ret_3 = paddle.allclose(
x_v_3,
y_v_3,
rtol=1e-05,
atol=1e-08,
equal_nan=False,
name='test_5')
self.assertEqual(ret_3.numpy()[0], False)
ret_3 = paddle.allclose(
x_v_3,
y_v_3,
rtol=1e-05,
atol=1e-08,
equal_nan=True,
name='test_6')
self.assertEqual(ret_3.numpy()[0], True)
if __name__ == "__main__":
unittest.main()