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Paddle/python/paddle/fluid/tests/unittests/test_label_smooth_functiona...

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# 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 numpy as np
import paddle
from paddle import fluid, nn
import paddle.fluid.dygraph as dg
import paddle.nn.functional as F
import paddle.fluid.initializer as I
import unittest
class LabelSmoothTestCase(unittest.TestCase):
def __init__(self,
methodName='runTest',
label_shape=(20, 1),
prior_dist=None,
epsilon=0.1,
dtype="float32"):
super(LabelSmoothTestCase, self).__init__(methodName)
self.label_shape = label_shape
self.prior_dist = prior_dist
self.dtype = dtype
self.epsilon = epsilon
def setUp(self):
self.label = np.random.randn(*(self.label_shape)).astype(self.dtype)
def fluid_layer(self, place):
paddle.enable_static()
main = fluid.Program()
start = fluid.Program()
with fluid.unique_name.guard():
with fluid.program_guard(main, start):
label_var = fluid.data(
"input", self.label_shape, dtype=self.dtype)
y_var = fluid.layers.label_smooth(
label_var,
prior_dist=self.prior_dist,
epsilon=self.epsilon,
dtype=self.dtype)
feed_dict = {"input": self.label}
exe = fluid.Executor(place)
exe.run(start)
y_np, = exe.run(main, feed=feed_dict, fetch_list=[y_var])
return y_np
def functional(self, place):
paddle.enable_static()
main = fluid.Program()
start = fluid.Program()
with fluid.unique_name.guard():
with fluid.program_guard(main, start):
label_var = fluid.data(
"input", self.label_shape, dtype=self.dtype)
y_var = F.label_smooth(
label_var, prior_dist=self.prior_dist, epsilon=self.epsilon)
feed_dict = {"input": self.label}
exe = fluid.Executor(place)
exe.run(start)
y_np, = exe.run(main, feed=feed_dict, fetch_list=[y_var])
return y_np
def paddle_dygraph_layer(self):
paddle.disable_static()
label_var = dg.to_variable(self.label)
y_var = F.label_smooth(
label_var, prior_dist=self.prior_dist, epsilon=self.epsilon)
y_np = y_var.numpy()
return y_np
def _test_equivalence(self, place):
place = fluid.CPUPlace()
result1 = self.fluid_layer(place)
result2 = self.functional(place)
result3 = self.paddle_dygraph_layer()
np.testing.assert_array_almost_equal(result1, result2)
np.testing.assert_array_almost_equal(result2, result3)
def runTest(self):
place = fluid.CPUPlace()
self._test_equivalence(place)
if fluid.core.is_compiled_with_cuda():
place = fluid.CUDAPlace(0)
self._test_equivalence(place)
class LabelSmoothErrorTestCase(LabelSmoothTestCase):
def runTest(self):
place = fluid.CPUPlace()
with dg.guard(place):
with self.assertRaises(ValueError):
self.paddle_dygraph_layer()
def add_cases(suite):
suite.addTest(LabelSmoothTestCase(methodName='runTest'))
suite.addTest(
LabelSmoothTestCase(
methodName='runTest', label_shape=[2, 3, 1]))
def add_error_cases(suite):
suite.addTest(LabelSmoothErrorTestCase(methodName='runTest', epsilon=2))
def load_tests(loader, standard_tests, pattern):
suite = unittest.TestSuite()
add_cases(suite)
add_error_cases(suite)
return suite
if __name__ == '__main__':
unittest.main()