[operator < lookup_table_v2 > error]
Created by: cs-y
1）PaddlePaddle版本：1.6 2）CPU/GPU：cpu 3）系统环境：ubuntu18.04 4）Python版本号:3.7.4 python代码：
import math import sys import numpy as np import paddle import paddle.fluid as fluid import paddle.fluid.layers as layers import paddle.fluid.nets as nets
IS_SPARSE = True BATCH_SIZE = 256 PASS_NUM = 20
def get_usr_combined_features(): """network definition for user part""" USR_DICT_SIZE = paddle.dataset.movielens.max_user_id() + 1 uid = fluid.data(name='user_id', shape=[None], dtype='int64') usr_emb = fluid.embedding( input=uid, dtype='float32', size=[USR_DICT_SIZE, 32], param_attr='user_table', is_sparse=IS_SPARSE) usr_fc = layers.fc(input=usr_emb, size=32) USR_GENDER_DICT_SIZE = 2 usr_gender_id = fluid.data(name='gender_id', shape=[None], dtype='int64') usr_gender_emb = fluid.embedding( input=usr_gender_id, size=[USR_GENDER_DICT_SIZE, 16], param_attr='gender_table', is_sparse=IS_SPARSE) usr_gender_fc = layers.fc(input=usr_gender_emb, size=16) USR_AGE_DICT_SIZE = len(paddle.dataset.movielens.age_table) usr_age_id = fluid.data(name='age_id', shape=[None], dtype="int64") usr_age_emb = fluid.embedding( input=usr_age_id, size=[USR_AGE_DICT_SIZE, 16], is_sparse=IS_SPARSE, param_attr='age_table') usr_age_fc = layers.fc(input=usr_age_emb, size=16) USR_JOB_DICT_SIZE = paddle.dataset.movielens.max_job_id() + 1 usr_job_id = fluid.data(name='job_id', shape=[None], dtype="int64") usr_job_emb = fluid.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) concat_embed = layers.concat( input=[usr_fc, usr_gender_fc, usr_age_fc, usr_job_fc], axis=1) usr_combined_features = layers.fc(input=concat_embed, size=200, act="tanh")
return usr_combined_featuresdef get_mov_combined_features(): """network definition for item(movie) part""" MOV_DICT_SIZE = paddle.dataset.movielens.max_movie_id() + 1 mov_id = fluid.data(name='movie_id', shape=[None], dtype='int64') mov_emb = fluid.embedding( input=mov_id, dtype='float32', size=[MOV_DICT_SIZE, 32], param_attr='movie_table', is_sparse=IS_SPARSE) mov_fc = layers.fc(input=mov_emb, size=32) CATEGORY_DICT_SIZE = len(paddle.dataset.movielens.movie_categories()) category_id = fluid.data( name='category_id', shape=[None], dtype='int64', lod_level=1) mov_categories_emb = fluid.embedding( input=category_id, size=[CATEGORY_DICT_SIZE, 32], is_sparse=IS_SPARSE) mov_categories_hidden = layers.sequence_pool( input=mov_categories_emb, pool_type="sum") MOV_TITLE_DICT_SIZE = len(paddle.dataset.movielens.get_movie_title_dict()) mov_title_id = fluid.data( name='movie_title', shape=[None], dtype='int64', lod_level=1) mov_title_emb = fluid.embedding( input=mov_title_id, size=[MOV_TITLE_DICT_SIZE, 32], is_sparse=IS_SPARSE) mov_title_conv = nets.sequence_conv_pool( input=mov_title_emb, num_filters=32, filter_size=3, act="tanh", pool_type="sum") concat_embed = layers.concat( input=[mov_fc, mov_categories_hidden, mov_title_conv], axis=1) # print(concat_embed) mov_combined_features = layers.fc(input=concat_embed, size=200, act="tanh")
return mov_combined_featuresdef inference_program(): """the combined network""" usr_combined_features = get_usr_combined_features() mov_combined_features = get_mov_combined_features()
print("get_usr_combined_features:",usr_combined_features)
print("get_mov_combined_features:",mov_combined_features)
# place = fluid.CPUPlace()
# exe = fluid.Executor(place)
# exe.run(fluid.default_startup_program())
# results = exe.run(fluid.default_main_program(),
# fetch_list=[b], return_numpy=False)
# # results[0].set_lod([[0, 1, 200]])
# print("The data of the result: {}.".format(np.array(results[0])))
inference = layers.cos_sim(X=usr_combined_features, Y=mov_combined_features)
scale_infer = layers.scale(x=inference, scale=5.0)
return scale_inferdef test(): a = np.array([[1,2,3],[4,5,6],[7,8,9]], dtype="float32") b = fluid.layers.create_tensor(dtype="float32") fluid.layers.assign(a, b) place = fluid.CPUPlace() exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) results = exe.run(fluid.default_main_program(), fetch_list=[b], return_numpy=False) results[0].set_lod([[0, 1, 3]]) lod_tensor = results[0] print("The LoD of the result: {}.".format(lod_tensor.lod())) print("The array : {}.".format(np.array(lod_tensor)))
当我单独执行test()或者inference_program()时，可以运行成功。
当我同时运行 test() inference_program() 报错： Cache file /root/.cache/paddle/dataset/movielens/movielens%2Fml-1m.zip not found, downloading https://[==================================================] get_usr_combined_features: name: "fc_4.tmp_2" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP32 dims: -1 dims: 200 } lod_level: 0 } } persistable: false
get_mov_combined_features: name: "fc_6.tmp_2" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP32 dims: -1 dims: 200 } lod_level: 0 } } persistable: false
/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/executor.py:774: UserWarning: The following exception is not an EOF exception. "The following exception is not an EOF exception.") Traceback (most recent call last): File "recommender.py", line 138, in test() File "recommender.py", line 128, in test fetch_list=[b], return_numpy=False) File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/executor.py", line 775, in run six.reraise(*sys.exc_info()) File "/data/workspace/conda3/lib/python3.7/site-packages/six.py", line 693, in reraise raise value File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/executor.py", line 770, in run use_program_cache=use_program_cache) File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/executor.py", line 817, in _run_impl use_program_cache=use_program_cache) File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/executor.py", line 894, in _run_program fetch_var_name) paddle.fluid.core_avx.EnforceNotMet:
C++ Call Stacks (More useful to developers):
0 std::string paddle::platform::GetTraceBackString<std::string const&>(std::string const&, char const*, int) 1 paddle::platform::EnforceNotMet::EnforceNotMet(std::string const&, char const*, int) 2 paddle::framework::Tensor::check_memory_size() const 3 long const* paddle::framework::Tensor::data() const 4 paddle::operators::LookupTableV2Kernel::Compute(paddle::framework::ExecutionContext const&) const 5 std::Function_handler<void (paddle::framework::ExecutionContext const&), paddle::framework::OpKernelRegistrarFunctor<paddle::platform::CPUPlace, false, 0ul, paddle::operators::LookupTableV2Kernel, paddle::operators::LookupTableV2Kernel >::operator()(char const*, char const*, int) const::{lambda(paddle::framework::ExecutionContext const&)#1 (closed)}>::M_invoke(std::Any_data const&, paddle::framework::ExecutionContext const&) 6 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void, boost::detail::variant::void, boost::detail::variant::void, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&, paddle::framework::RuntimeContext*) const 7 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) const 8 paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, boost::variant<paddle::platform::CUDAPlace, paddle::platform::CPUPlace, paddle::platform::CUDAPinnedPlace, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_, boost::detail::variant::void_> const&) 9 paddle::framework::Executor::RunPreparedContext(paddle::framework::ExecutorPrepareContext*, paddle::framework::Scope*, bool, bool, bool) 10 paddle::framework::Executor::Run(paddle::framework::ProgramDesc const&, paddle::framework::Scope*, int, bool, bool, std::vector<std::string, std::allocatorstd::string > const&, bool)
Python Call Stacks (More useful to users):
File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/framework.py", line 2459, in append_op attrs=kwargs.get("attrs", None)) File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op return self.main_program.current_block().append_op(*args, **kwargs) File "/data/workspace/conda3/lib/python3.7/site-packages/paddle/fluid/input.py", line 268, in embedding 'padding_idx': padding_idx File "recommender.py", line 22, in get_usr_combined_features is_sparse=IS_SPARSE) File "recommender.py", line 93, in inference_program usr_combined_features = get_usr_combined_features() File "recommender.py", line 137, in inference_program()
Error Message Summary:
PaddleCheckError: holder_ should not be null Tensor holds no memory. Call Tensor::mutable_data first. at [/paddle/paddle/fluid/framework/tensor.cc:23] [operator < lookup_table_v2 > error]