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- # 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 unittest
-
- import numpy as np
- from get_test_cover_info import (
- XPUOpTestWrapper,
- create_test_class,
- get_xpu_op_support_types,
- )
- from op_test import OpTest
- from op_test_xpu import XPUOpTest
-
- import paddle
-
- paddle.enable_static()
-
-
- 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 XPUTestHuberLossOp(XPUOpTestWrapper):
- def __init__(self):
- self.op_name = 'huber_loss'
- self.use_dynamic_create_class = False
-
- class TestHuberLossOp(XPUOpTest):
- def setUp(self):
- self.set_xpu()
- self.op_type = 'huber_loss'
- self.place = paddle.XPUPlace(0)
-
- self.init_dtype()
- self.set_inputs()
- self.set_attrs()
- self.set_outputs()
-
- def set_inputs(self):
- shape = self.set_shape()
- x = np.random.uniform(0, 1.0, shape).astype(self.dtype)
- y = np.random.uniform(0, 1.0, shape).astype(self.dtype)
- self.inputs = {
- 'X': OpTest.np_dtype_to_base_dtype(x),
- 'Y': OpTest.np_dtype_to_base_dtype(y),
- }
-
- def set_attrs(self):
- self.attrs = {'delta': 0.5}
-
- def set_outputs(self):
- delta = self.attrs['delta']
- shape = self.set_shape()
- residual = self.inputs['Y'] - self.inputs['X']
- loss = np.vectorize(huber_loss_forward)(residual, delta).astype(
- self.dtype
- )
- self.outputs = {'Residual': residual, 'Out': loss.reshape(shape)}
-
- def set_shape(self):
- return (100, 1)
-
- def set_xpu(self):
- self.__class__.use_xpu = True
-
- def init_dtype(self):
- self.dtype = self.in_type
-
- def test_check_output(self):
- self.check_output_with_place(self.place)
-
- def test_check_grad_normal(self):
- self.check_grad_with_place(self.place, ['X', 'Y'], 'Out')
-
- def test_check_grad_ignore_x(self):
- self.check_grad_with_place(
- self.place, ['Y'], 'Out', no_grad_set=set("residual")
- )
-
- def test_check_grad_ignore_y(self):
- self.check_grad_with_place(
- self.place, ['X'], 'Out', no_grad_set=set('residual')
- )
-
- class TestHuberLossOp1(TestHuberLossOp):
- def set_shape(self):
- return 640
-
- class TestHuberLossOp2(TestHuberLossOp):
- def set_shape(self):
- return (10, 10)
-
- class TestHuberLossOp3(TestHuberLossOp):
- def set_shape(self):
- return (10, 10, 1)
-
-
- support_types = get_xpu_op_support_types('huber_loss')
- for stype in support_types:
- create_test_class(globals(), XPUTestHuberLossOp, stype)
-
- if __name__ == '__main__':
- unittest.main()
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