# 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. from __future__ import print_function import unittest import numpy as np from op_test import OpTest import paddle.fluid as fluid from paddle.fluid import compiler, Program, program_guard def huber_loss_forward(val, delta): abs_val = abs(val) if abs_val <= delta: return 0.5 * val * val else: return delta * (abs_val - 0.5 * delta) class TestHuberLossOp(OpTest): def setUp(self): self.op_type = 'huber_loss' self.delta = 1.0 self.init_input() shape = self.set_shape() residual = self.inputs['Y'] - self.inputs['X'] loss = np.vectorize(huber_loss_forward)(residual, self.delta).astype('float32') self.attrs = {'delta': self.delta} self.outputs = {'Residual': residual, 'Out': loss.reshape(shape)} def init_input(self): shape = self.set_shape() self.inputs = { 'X': np.random.uniform(0, 1., shape).astype('float32'), 'Y': np.random.uniform(0, 1., shape).astype('float32'), } def set_shape(self): return (100, 1) def test_check_output(self): self.check_output() def test_check_grad_normal(self): self.check_grad(['X', 'Y'], 'Out') def test_check_grad_ingore_x(self): self.check_grad( ['Y'], 'Out', max_relative_error=0.008, no_grad_set=set("residual")) def test_check_grad_ingore_y(self): self.check_grad( ['X'], 'Out', max_relative_error=0.008, no_grad_set=set('residual')) def TestHuberLossOp1(TestHuberLossOp): def set_shape(self): return (64) def TestHuberLossOp2(TestHuberLossOp): def set_shape(self): return (6, 6) def TestHuberLossOp3(TestHuberLossOp): def set_shape(self): return (6, 6, 1) class TestHuberLossOpError(unittest.TestCase): def test_errors(self): with program_guard(Program(), Program()): # the input and label must be Variable xw = np.random.random((6, 6)).astype("float32") xr = fluid.data(name='xr', shape=[None, 6], dtype="float32") lw = np.random.random((6, 6)).astype("float32") lr = fluid.data(name='lr', shape=[None, 6], dtype="float32") delta = 1.0 self.assertRaises(TypeError, fluid.layers.huber_loss, xr, lw, delta) self.assertRaises(TypeError, fluid.layers.huber_loss, xw, lr, delta) # the dtype of input and label must be float32 or float64 xw2 = fluid.data(name='xw2', shape=[None, 6], dtype="int32") lw2 = fluid.data(name='lw2', shape=[None, 6], dtype="int32") self.assertRaises(TypeError, fluid.layers.huber_loss, xw2, lr, delta) self.assertRaises(TypeError, fluid.layers.huber_loss, xr, lw2, delta) if __name__ == '__main__': unittest.main()