PaddlePaddle使用ml-1m数据集数据在训练时出现非法指令

原创于 2019-02-27 10:16:50 发布 · 463 阅读

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本文描述了在使用PaddlePaddle的embedding层时遇到的非法指令错误，详细解释了错误原因，并提供了修正代码，确保词向量大小与数据集匹配，避免训练过程中的异常终止。

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关键字：非法指令，embedding
问题描述：使用ml-1m数据集训练个性化推荐模型，使用ml-1m数据集中的数据转换成词向量，然后训练时出现非法指令的错误。
报错信息：

<ipython-input-8-71a7f986f7ba> in train(use_cuda, train_program, params_dirname)
     39         event_handler=event_handler,
     40         reader=train_reader,
---> 41         feed_order=feed_order)

/opt/conda/envs/py35-paddle1.0.0/lib/python3.5/site-packages/paddle/fluid/contrib/trainer.py in train(self, num_epochs, event_handler, reader, feed_order)
    403         else:
    404             self._train_by_executor(num_epochs, event_handler, reader,
--> 405                                     feed_order)
    406 
    407     def test(self, reader, feed_order):

/opt/conda/envs/py35-paddle1.0.0/lib/python3.5/site-packages/paddle/fluid/contrib/trainer.py in _train_by_executor(self, num_epochs, event_handler, reader, feed_order)
    481             exe = executor.Executor(self.place)
    482             reader = feeder.decorate_reader(reader, multi_devices=False)
--> 483             self._train_by_any_executor(event_handler, exe, num_epochs, reader)
    484 
    485     def _train_by_any_executor(self, event_handler, exe, num_epochs, reader):

/opt/conda/envs/py35-paddle1.0.0/lib/python3.5/site-packages/paddle/fluid/contrib/trainer.py in _train_by_any_executor(self, event_handler, exe, num_epochs, reader)
    510                                       fetch_list=[
    511                                           var.name
--> 512                                           for var in self.train_func_outputs
    513                                       ])
    514                 else:

/opt/conda/envs/py35-paddle1.0.0/lib/python3.5/site-packages/paddle/fluid/executor.py in run(self, program, feed, fetch_list, feed_var_name, fetch_var_name, scope, return_numpy, use_program_cache)
    468 
    469         self._feed_data(program, feed, feed_var_name, scope)
--> 470         self.executor.run(program.desc, scope, 0, True, True)
    471         outs = self._fetch_data(fetch_list, fetch_var_name, scope)
    472         if return_numpy:

EnforceNotMet: an illegal instruction was encountered at [/paddle/paddle/fluid/platform/device_context.cc:230]
PaddlePaddle Call Stacks:

问题复现：通过paddle.dataset.movielens.max_job_id接口获取最大的工作类型ID，然后把获得的值作为fluid.layers.embedding接口参数size的值传进去，最好使用这些词向量构建成一个网络进行训练，在训练的时候就出现非法指令错误。错误代码如下：

USR_JOB_DICT_SIZE = paddle.dataset.movielens.max_job_id()
usr_job_id = layers.data(name='job_id', shape=[1], dtype="int64")
usr_job_emb = layers.embedding(
    input=usr_job_id,
    size=[USR_JOB_DICT_SIZE, 16],
    param_attr='job_table',
    is_sparse=IS_SPARSE)
usr_job_fc = layers.fc(input=usr_job_emb, size=16)

解决问题：通过paddle.dataset.movielens.max_job_id的接口获得的是最大的工作类型ID，工作类型的ID是从0开始标号的，所以最大的工作类型ID再加上1才是工作类型的数量，上面的错误就是工作类别数量少了1个。正确代码如下：

USR_JOB_DICT_SIZE = paddle.dataset.movielens.max_job_id() + 1
usr_job_id = layers.data(name='job_id', shape=[1], dtype="int64")
usr_job_emb = layers.embedding(
    input=usr_job_id,
    size=[USR_JOB_DICT_SIZE, 16],
    param_attr='job_table',
    is_sparse=IS_SPARSE)
usr_job_fc = layers.fc(input=usr_job_emb, size=16)