# 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 op_test import OpTest class TestSequenceScatterOp(OpTest): def init_lod(self): return [[3, 5, 4]] def setUp(self): self.test_gc = True self.op_type = "sequence_scatter" X_data = np.random.uniform(0.1, 1.0, [3, 6]).astype('float32') Ids_data = np.array([[0], [1], [2], [5], [4], [3], [0], [1], [3], [2], [5], [4]]).astype('int64') Ids_lod = self.init_lod() Updates_data = np.random.uniform(0.1, 1.0, [12, 1]).astype('float32') Updates_lod = Ids_lod Out_data = np.copy(X_data) offset = 0 for i in range(3): Out_data[i][Ids_data[offset:(offset + Ids_lod[0][ i])]] += Updates_data[offset:(offset + Ids_lod[0][i])] offset += Ids_lod[0][i] self.inputs = { 'X': X_data, 'Ids': (Ids_data, Ids_lod), 'Updates': (Updates_data, Updates_lod) } self.outputs = {'Out': Out_data} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['Updates'], 'Out', in_place=True) class TestSequenceScatterOpSeqLen0(TestSequenceScatterOp): def init_lod(self): return [[6, 0, 6]] class TestSequenceScatterOpSeqLen0Case1(TestSequenceScatterOp): def init_lod(self): return [[0, 6, 6]] class TestSequenceScatterOpSeqLen0Case2(TestSequenceScatterOp): def init_lod(self): return [[6, 6, 0]] if __name__ == "__main__": unittest.main()