# 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 class TestTopkOp(OpTest): def setUp(self): self.op_type = "top_k" k = 1 input = np.random.random((32, 84)).astype("float32") output = np.ndarray((32, k)) indices = np.ndarray((32, k)).astype("int64") self.inputs = {'X': input} self.attrs = {'k': k} for rowid in range(32): row = input[rowid] output[rowid] = np.sort(row)[-k:] indices[rowid] = row.argsort()[-k:] self.outputs = {'Out': output, 'Indices': indices} def test_check_output(self): self.check_output() class TestTopkOp3d(OpTest): def setUp(self): self.op_type = "top_k" k = 1 input = np.random.random((32, 2, 84)).astype("float32") input_flat_2d = input.reshape(64, 84) output = np.ndarray((64, k)) indices = np.ndarray((64, k)).astype("int64") # FIXME: should use 'X': input for a 3d input self.inputs = {'X': input_flat_2d} self.attrs = {'k': k} for rowid in range(64): row = input_flat_2d[rowid] output[rowid] = np.sort(row)[-k:] indices[rowid] = row.argsort()[-k:] self.outputs = {'Out': output, 'Indices': indices} def test_check_output(self): self.check_output() if __name__ == "__main__": unittest.main()