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Paddle/python/paddle/fluid/tests/unittests/test_beam_search_op.py

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3.3 KiB

# 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 logging
from paddle.fluid.op import Operator, DynamicRecurrentOp
import paddle.fluid.core as core
import unittest
import numpy as np
def create_tensor(scope, name, np_data):
tensor = scope.var(name).get_tensor()
tensor.set(np_data, core.CPUPlace())
return tensor
class BeamSearchOpTester(unittest.TestCase):
"""unittest of beam_search_op"""
def setUp(self):
self.scope = core.Scope()
self._create_ids()
self._create_pre_scores()
self._create_scores()
self._create_pre_ids()
self.scope.var('selected_ids')
self.scope.var('selected_scores')
self.scope.var('parent_idx')
def test_run(self):
op = Operator(
'beam_search',
pre_ids='pre_ids',
pre_scores='pre_scores',
ids='ids',
scores='scores',
selected_ids='selected_ids',
selected_scores='selected_scores',
parent_idx='parent_idx',
level=0,
beam_size=2,
end_id=0, )
op.run(self.scope, core.CPUPlace())
selected_ids = self.scope.find_var("selected_ids").get_tensor()
selected_scores = self.scope.find_var("selected_scores").get_tensor()
parent_idx = self.scope.find_var("parent_idx").get_tensor()
self.assertTrue(
np.allclose(
np.array(selected_ids), np.array([4, 2, 3, 8])[:, np.newaxis]))
self.assertTrue(
np.allclose(
np.array(selected_scores),
np.array([0.5, 0.6, 0.9, 0.7])[:, np.newaxis]))
self.assertEqual(selected_ids.lod(), [[0, 2, 4], [0, 1, 2, 3, 4]])
self.assertTrue(
np.allclose(np.array(parent_idx), np.array([0, 1, 2, 3])))
def _create_pre_ids(self):
np_data = np.array([[1, 2, 3, 4]], dtype='int64')
tensor = create_tensor(self.scope, 'pre_ids', np_data)
def _create_pre_scores(self):
np_data = np.array([[0.1, 0.2, 0.3, 0.4]], dtype='float32')
tensor = create_tensor(self.scope, 'pre_scores', np_data)
def _create_ids(self):
self.lod = [[0, 2, 4], [0, 1, 2, 3, 4]]
np_data = np.array(
[[4, 2, 5], [2, 1, 3], [3, 5, 2], [8, 2, 1]], dtype='int64')
tensor = create_tensor(self.scope, "ids", np_data)
tensor.set_lod(self.lod)
def _create_scores(self):
np_data = np.array(
[
[0.5, 0.3, 0.2],
[0.6, 0.3, 0.1],
[0.9, 0.5, 0.1],
[0.7, 0.5, 0.1],
],
dtype='float32')
tensor = create_tensor(self.scope, "scores", np_data)
tensor.set_lod(self.lod)
if __name__ == '__main__':
unittest.main()