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66 lines
2.3 KiB
66 lines
2.3 KiB
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle.fluid as fluid
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class TestGatherTreeOp(OpTest):
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def setUp(self):
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self.op_type = "gather_tree"
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max_length, batch_size, beam_size = 5, 2, 2
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ids = np.random.randint(
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0, high=10, size=(max_length, batch_size, beam_size))
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parents = np.random.randint(
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0, high=beam_size, size=(max_length, batch_size, beam_size))
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self.inputs = {"Ids": ids, "Parents": parents}
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self.outputs = {'Out': self.backtrace(ids, parents)}
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def test_check_output(self):
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self.check_output()
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@staticmethod
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def backtrace(ids, parents):
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out = np.zeros_like(ids)
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(max_length, batch_size, beam_size) = ids.shape
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for batch in range(batch_size):
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for beam in range(beam_size):
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out[max_length - 1, batch, beam] = ids[max_length - 1, batch,
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beam]
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parent = parents[max_length - 1, batch, beam]
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for step in range(max_length - 2, -1, -1):
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out[step, batch, beam] = ids[step, batch, parent]
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parent = parents[step, batch, parent]
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return out
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class TestGatherTreeOpAPI(unittest.TestCase):
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def test_case(self):
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ids = fluid.layers.data(
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name='ids', shape=[5, 2, 2], dtype='int64', append_batch_size=False)
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parents = fluid.layers.data(
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name='parents',
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shape=[5, 2, 2],
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dtype='int64',
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append_batch_size=False)
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final_sequences = fluid.layers.gather_tree(ids, parents)
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if __name__ == "__main__":
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unittest.main()
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