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147 lines
5.3 KiB
147 lines
5.3 KiB
# Copyright (c) 2020 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 paddle.fluid as fluid
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import paddle.fluid.core as core
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import os
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import unittest
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import paddle.fluid.layers as layers
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class TestDataFeed(unittest.TestCase):
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""" TestBaseCase(Merge PV) """
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def setUp(self):
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self.batch_size = 10
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self.pv_batch_size = 10
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self.enable_pv_merge = True
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self.merge_by_sid = True
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def set_data_config(self):
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self.dataset = fluid.DatasetFactory().create_dataset("BoxPSDataset")
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self.dataset.set_feed_type("PaddleBoxDataFeed")
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self.dataset.set_parse_logkey(True)
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self.dataset.set_thread(1)
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self.dataset.set_enable_pv_merge(self.enable_pv_merge)
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self.dataset.set_batch_size(self.batch_size)
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if self.enable_pv_merge:
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self.dataset.set_merge_by_sid(self.merge_by_sid)
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self.dataset.set_rank_offset("rank_offset")
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self.dataset.set_pv_batch_size(self.pv_batch_size)
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def test_pboxdatafeed(self):
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self.run_dataset(False)
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def test_pboxdatafeed(self):
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self.run_dataset(True)
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def run_dataset(self, is_cpu):
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x = fluid.layers.data(name='x', shape=[1], dtype='int64', lod_level=0)
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y = fluid.layers.data(name='y', shape=[1], dtype='int64', lod_level=0)
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rank_offset = fluid.layers.data(
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name="rank_offset",
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shape=[-1, 7],
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dtype="int32",
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lod_level=0,
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append_batch_size=False)
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emb_x, emb_y = fluid.contrib.layers._pull_box_extended_sparse(
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[x, y], size=2, extend_size=128)
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concat = layers.concat([emb_x[0], emb_x[1], emb_y[0], emb_y[1]], axis=1)
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fc = layers.fc(input=concat,
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name="fc",
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size=1,
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num_flatten_dims=1,
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bias_attr=False)
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loss = layers.reduce_mean(fc)
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place = fluid.CPUPlace() if is_cpu or not core.is_compiled_with_cuda(
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) else fluid.CUDAPlace(0)
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exe = fluid.Executor(place)
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with open("test_run_with_dump_a.txt", "w") as f:
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data = "1 1702f830eee19501ad7429505f714c1d 1 1 1 9\n"
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data += "1 1702f830eee19502ad7429505f714c1d 1 2 1 8\n"
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data += "1 1702f830eee19503ad7429505f714c1d 1 3 1 7\n"
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data += "1 1702f830eee0de01ad7429505f714c2d 1 4 1 6\n"
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data += "1 1702f830eee0df01ad7429505f714c3d 1 5 1 5\n"
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data += "1 1702f830eee0df02ad7429505f714c3d 1 6 1 4\n"
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f.write(data)
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with open("test_run_with_dump_b.txt", "w") as f:
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data = "1 1702f830fff22201ad7429505f715c1d 1 1 1 1\n"
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data += "1 1702f830fff22202ad7429505f715c1d 1 2 1 2\n"
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data += "1 1702f830fff22203ad7429505f715c1d 1 3 1 3\n"
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data += "1 1702f830fff22101ad7429505f714ccd 1 4 1 4\n"
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data += "1 1702f830fff22102ad7429505f714ccd 1 5 1 5\n"
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data += "1 1702f830fff22103ad7429505f714ccd 1 6 1 6\n"
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data += "1 1702f830fff22104ad7429505f714ccd 1 6 1 7\n"
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f.write(data)
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self.set_data_config()
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self.dataset.set_use_var([x, y])
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self.dataset.set_filelist(
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["test_run_with_dump_a.txt", "test_run_with_dump_b.txt"])
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optimizer = fluid.optimizer.SGD(learning_rate=0.5)
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optimizer = fluid.optimizer.PipelineOptimizer(
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optimizer,
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cut_list=[],
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place_list=[place],
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concurrency_list=[1],
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queue_size=1,
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sync_steps=-1)
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optimizer.minimize(loss)
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exe.run(fluid.default_startup_program())
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self.dataset.set_current_phase(1)
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self.dataset.load_into_memory()
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self.dataset.preprocess_instance()
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self.dataset.begin_pass()
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pv_num = self.dataset.get_pv_data_size()
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exe.train_from_dataset(
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program=fluid.default_main_program(),
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dataset=self.dataset,
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print_period=1)
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self.dataset.set_current_phase(0)
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self.dataset.postprocess_instance()
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exe.train_from_dataset(
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program=fluid.default_main_program(),
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dataset=self.dataset,
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print_period=1)
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self.dataset.end_pass(True)
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os.remove("test_run_with_dump_a.txt")
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os.remove("test_run_with_dump_b.txt")
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class TestDataFeed2(TestDataFeed):
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""" TestBaseCase(Merge PV not merge by sid) """
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def setUp(self):
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self.batch_size = 10
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self.pv_batch_size = 10
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self.enable_pv_merge = True
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self.merge_by_sid = False
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class TestDataFeed3(TestDataFeed):
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""" TestBaseCase(Not Merge PV) """
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def setUp(self):
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self.batch_size = 10
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self.pv_batch_size = 10
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self.enable_pv_merge = False
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if __name__ == '__main__':
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unittest.main()
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