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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 unittest
-
- import numpy as np
- from get_test_cover_info import (
- XPUOpTestWrapper,
- create_test_class,
- get_xpu_op_support_types,
- )
- from op_test_xpu import XPUOpTest
-
- import paddle
-
- paddle.enable_static()
-
-
- class XPUTestAccuracyOp(XPUOpTestWrapper):
- def __init__(self):
- self.op_name = 'accuracy'
- self.use_dynamic_create_class = False
-
- class TestXPUAccuracyOp(XPUOpTest):
- def setUp(self):
- self.op_type = "accuracy"
- self.init_dtype()
- n = 8192
- infer = np.random.random((n, 1)).astype(self.dtype)
- indices = np.random.randint(0, 2, (n, 1)).astype('int64')
- label = np.random.randint(0, 2, (n, 1)).astype('int64')
- self.inputs = {'Out': infer, 'Indices': indices, "Label": label}
- num_correct = 0
- for rowid in range(n):
- for ele in indices[rowid]:
- if ele == label[rowid]:
- num_correct += 1
- break
- self.outputs = {
- 'Accuracy': np.array(num_correct / float(n)).astype(self.dtype),
- 'Correct': np.array(num_correct).astype("int32"),
- 'Total': np.array(n).astype("int32"),
- }
- self.attrs = {'use_xpu': True}
-
- def init_dtype(self):
- self.dtype = self.in_type
-
- def test_check_output(self):
- if paddle.is_compiled_with_xpu():
- place = paddle.XPUPlace(0)
- self.check_output_with_place(place)
-
-
- support_types = get_xpu_op_support_types('accuracy')
- for stype in support_types:
- create_test_class(globals(), XPUTestAccuracyOp, stype)
-
- if __name__ == '__main__':
- unittest.main()
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