# 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 import paddle.fluid.dygraph as dg import paddle.nn.functional as F 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()