FAQ
Q: Does MindSpore Serving support hot update to avoid inference service interruption?
A: MindSpore Serving does not support hot update. You need to restart MindSpore Serving. You are advised to run multiple Serving services. When updating a model, restart some services to avoid service interruption.
Q: Does MindSpore Serving allow multiple workers to be started for one model to support multi-device and single-model concurrency?
A: After MindSpore Serving version 1.3, it supports the deployment of multiple copies of a model in multiple cards to achieve concurrent execution of multiple cards and single models. For details, please refer to Add Sample.
Q: How does the MindSpore Serving version match the MindSpore version?
A: MindSpore Serving matches MindSpore in the same version. For example, Serving 1.1.1
matches MindSpore 1.1.1
.
Q: What is the difference between using bash -p
method and bash -e
method when compiling?
A: MindSpore Serving build and running depend on MindSpore. Serving provides two build modes: 1. Use bash -p {python site-packages}/mindspore/lib
to specify an installed MindSpore path to avoid building MindSpore when building Serving. 2. Build Serving and the corresponding MindSpore. Serving passes the -e
, -V
, and -j
options to MindSpore.
For example, use bash -e ascend -V 910 -j32
in the Serving directory as follows:
Build MindSpore in the
third_party/mindspore
directory usingbash -e ascend -V 910 -j32
.Use the MindSpore build result as the Serving build dependency.
Q: What can I do if an error libmindspore.so: cannot open shared object file: No such file or directory
is reported during application running?
A: Check whether MindSpore that MindSpore Serving depends on is installed. In Serving 1.1, LD_LIBRARY_PATH
needs to be configured to explicitly specify the path of libmindspore.so
. libmindspore.so
is in the lib
directory of the MindSpore Python installation path. In Serving 1.2 or later, the path of libmindspore.so
does not need to be specified. Serving searches for and adds LD_LIBRARY_PATH
based on the MindSpore installation path, which does not need to be perceived by users.
Q:How to control the output of Serving log?
A:MindSpore Serving uses glog to output logs, for more details, please refer to Log-related Environment Variables and Configurations. On this basis, additional supplementary contents are as follows:
MS_SUBMODULE_LOG_v
This environment variable can also be used to control the log level of MindSpore Serving in addition to specifying the log level of each sub module of MindSpore C++.
We can use GLOG_v=2 MS_SUBMODULE_LOG_v=”{SERVING:1}” to set the log level of the Serving module to INFO, and the log level of other modules to WARNING.
Q: What can I do if an error libmindspore.so: cannot open shared object file: No such file or directory
is reported during application running?
A: Check whether MindSpore that MindSpore Serving depends on is installed. In Serving 1.1, LD_LIBRARY_PATH
needs to be configured to explicitly specify the path of libmindspore.so
. libmindspore.so
is in the lib
directory of the MindSpore Python installation path. In Serving 1.2 or later, the path of libmindspore.so
does not need to be specified. Serving searches for and adds LD_LIBRARY_PATH
based on the MindSpore installation path, which does not need to be perceived by users.
Q: Error ‘assertion failed: slice_buffer->length <= UINT32_MAX’ is reported when an extra large meesage is send through the MindSpore Serving gPRC Client.
Detailed error information:
test_serving_client_grpc.py::test_serving_grpc_pressure_big_message E0413 20:03:08.764913058 122601 byte_stream.cc:40] assertion failed: slice_buffer->length <= UINT32_MAX
Fatal Python error: Aborted
Current thread 0x0000ffffb4884010 (most recent call first):
File ".../python3.7/site-packages/grpc/_channel.py", line 909 in _blocking
File ".../python3.7/site-packages/grpc/_channel.py", line 922 in call
File ".../python3.7/site-packages/mindspore_serving/client/python/client.py", line 217 in infer
A: MindSpore Serving provides Python Client to encapsulate gRPC communication. According to the error information above, the message size exceeds 4GB(UINT32_MAX).
Further, MindSpore Serving sets the size of the message accepted by the server to 100MB by default. Parameter max_msg_mb_size
can be configured in def start_grpc_server(address, max_msg_mb_size=100, ssl_config=None)
and def start_restful_server(address, max_msg_mb_size=100, ssl_config=None)
interfaces to set the maximum message accepted by the server.
Parameter max_msg_mb_size
accepts an integer ranging from 1 to 512 to control the maximum size of a received message. If the message size exceeds the value, the client reports an error similar to the following, 104857600 indicates the default limit of 100MB on the server:
Received message larger than max (419429033 vs. 104857600)
RESOURCE_EXHAUSTED
(8, 'resource exhausted')
The maximum size of a message sent by the client is limited to 512MB. If the maximum size is exceeded, the client reports an error similar to the following:
Sent message larger than max (838858033 vs. 536870912)
RESOURCE_EXHAUSTED
(8, 'resource exhausted')