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107 lines
3.5 KiB
107 lines
3.5 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle.fluid as fluid
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from paddle.fluid import compiler, Program, program_guard
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def huber_loss_forward(val, delta):
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abs_val = abs(val)
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if abs_val <= delta:
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return 0.5 * val * val
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else:
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return delta * (abs_val - 0.5 * delta)
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class TestHuberLossOp(OpTest):
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def setUp(self):
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self.op_type = 'huber_loss'
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self.delta = 1.0
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self.init_input()
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shape = self.set_shape()
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residual = self.inputs['Y'] - self.inputs['X']
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loss = np.vectorize(huber_loss_forward)(residual,
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self.delta).astype('float32')
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self.attrs = {'delta': self.delta}
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self.outputs = {'Residual': residual, 'Out': loss.reshape(shape)}
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def init_input(self):
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shape = self.set_shape()
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self.inputs = {
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'X': np.random.uniform(0, 1., shape).astype('float32'),
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'Y': np.random.uniform(0, 1., shape).astype('float32'),
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}
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def set_shape(self):
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return (100, 1)
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def test_check_output(self):
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self.check_output()
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def test_check_grad_normal(self):
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self.check_grad(['X', 'Y'], 'Out')
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def test_check_grad_ingore_x(self):
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self.check_grad(
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['Y'], 'Out', max_relative_error=0.008, no_grad_set=set("residual"))
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def test_check_grad_ingore_y(self):
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self.check_grad(
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['X'], 'Out', max_relative_error=0.008, no_grad_set=set('residual'))
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def TestHuberLossOp1(TestHuberLossOp):
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def set_shape(self):
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return (64)
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def TestHuberLossOp2(TestHuberLossOp):
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def set_shape(self):
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return (6, 6)
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def TestHuberLossOp2(TestHuberLossOp):
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def set_shape(self):
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return (6, 6, 1)
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class TestHuberLossOpError(unittest.TestCase):
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def test_errors(self):
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with program_guard(Program(), Program()):
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# the input and label must be Variable
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xw = np.random.random((6, 6)).astype("float32")
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xr = fluid.data(name='xr', shape=[None, 6], dtype="float32")
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lw = np.random.random((6, 6)).astype("float32")
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lr = fluid.data(name='lr', shape=[None, 6], dtype="float32")
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delta = 1.0
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self.assertRaises(TypeError, fluid.layers.huber_loss, xr, lw, delta)
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self.assertRaises(TypeError, fluid.layers.huber_loss, xw, lr, delta)
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# the dtype of input and label must be float32 or float64
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xw2 = fluid.data(name='xw2', shape=[None, 6], dtype="int32")
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lw2 = fluid.data(name='lw2', shape=[None, 6], dtype="int32")
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self.assertRaises(TypeError, fluid.layers.huber_loss, xw2, lr,
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delta)
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self.assertRaises(TypeError, fluid.layers.huber_loss, xr, lw2,
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delta)
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if __name__ == '__main__':
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unittest.main()
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