# Copyright (c) 2019 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 import paddle.fluid as fluid from paddle.fluid.framework import program_guard, Program class TestGatherTreeOp(OpTest): def setUp(self): self.op_type = "gather_tree" max_length, batch_size, beam_size = 5, 2, 2 ids = np.random.randint( 0, high=10, size=(max_length, batch_size, beam_size)) parents = np.random.randint( 0, high=beam_size, size=(max_length, batch_size, beam_size)) self.inputs = {"Ids": ids, "Parents": parents} self.outputs = {'Out': self.backtrace(ids, parents)} def test_check_output(self): self.check_output() @staticmethod def backtrace(ids, parents): out = np.zeros_like(ids) (max_length, batch_size, beam_size) = ids.shape for batch in range(batch_size): for beam in range(beam_size): out[max_length - 1, batch, beam] = ids[max_length - 1, batch, beam] parent = parents[max_length - 1, batch, beam] for step in range(max_length - 2, -1, -1): out[step, batch, beam] = ids[step, batch, parent] parent = parents[step, batch, parent] return out class TestGatherTreeOpAPI(unittest.TestCase): def test_case(self): ids = fluid.layers.data( name='ids', shape=[5, 2, 2], dtype='int64', append_batch_size=False) parents = fluid.layers.data( name='parents', shape=[5, 2, 2], dtype='int64', append_batch_size=False) final_sequences = fluid.layers.gather_tree(ids, parents) class TestGatherTreeOpError(unittest.TestCase): def test_errors(self): with program_guard(Program(), Program()): ids = fluid.layers.data( name='ids', shape=[5, 2, 2], dtype='int64', append_batch_size=False) parents = fluid.layers.data( name='parents', shape=[5, 2, 2], dtype='int64', append_batch_size=False) def test_Variable_ids(): # the input type must be Variable np_ids = np.random.random((5, 2, 2), dtype='int64') fluid.layers.gather_tree(np_ids, parents) self.assertRaises(TypeError, test_Variable_ids) def test_Variable_parents(): # the input type must be Variable np_parents = np.random.random((5, 2, 2), dtype='int64') fluid.layers.gather_tree(ids, np_parents) self.assertRaises(TypeError, test_Variable_parents) def test_type_ids(): # dtype must be int32 or int64 bad_ids = fluid.layers.data( name='bad_ids', shape=[5, 2, 2], dtype='float32', append_batch_size=False) fluid.layers.gather_tree(bad_ids, parents) self.assertRaises(TypeError, test_type_ids) def test_type_parents(): # dtype must be int32 or int64 bad_parents = fluid.layers.data( name='bad_parents', shape=[5, 2, 2], dtype='float32', append_batch_size=False) fluid.layers.gather_tree(ids, bad_parents) self.assertRaises(TypeError, test_type_parents) if __name__ == "__main__": unittest.main()