# 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()