# 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 six import numpy as np from op_test import OpTest class TestSequenceUnpadOp(OpTest): def init(self): self.length = [2, 3, 4] self.x_shape = (3, 5) self.dtype = "float32" def compute(self): assert len(self.length) == self.x_shape[0] x = np.random.random(self.x_shape).astype(self.dtype) out_lod = [self.length] out = x[0, 0:self.length[0]] for i in six.moves.xrange(1, x.shape[0]): out = np.append(out, x[i, 0:self.length[i]], axis=0) out_shape = (sum(self.length), ) if len(self.x_shape) == 2: out_shape = out_shape + (1, ) else: out_shape = out_shape + self.x_shape[2:] self.inputs = { 'X': x, 'Length': np.array(self.length).astype('int64').reshape(-1, 1) } self.outputs = {'Out': (out.reshape(out_shape), out_lod)} def setUp(self): self.op_type = 'sequence_unpad' self.init() self.compute() def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") class TestSequenceUnpadOp2(TestSequenceUnpadOp): def init(self): self.length = [2, 3, 4] self.x_shape = (3, 5, 4, 3) self.dtype = "float32" class TestSequenceUnpadOp3(TestSequenceUnpadOp): def init(self): self.length = [5, 2, 3, 4] self.x_shape = (4, 5, 3, 3, 6) self.dtype = "float64" if __name__ == '__main__': unittest.main()