not able to start server

[majidhamzavi]

Prerequisites

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• Are you running the latest bert-as-service?
• Did you follow the installation and the usage instructions in README.md?
• Did you check the FAQ list in README.md?
• Did you perform a cursory search on existing issues?

System information

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• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
• TensorFlow installed from (source or binary):
• TensorFlow version:
• Python version:
• bert-as-service version:
• GPU model and memory:
• CPU model and memory:

---

Description

Please replace YOUR_SERVER_ARGS and YOUR_CLIENT_ARGS accordingly. You can also write your own description for reproducing the issue.

I'm using this command to start the server:

bert-serving-start YOUR_SERVER_ARGS

/opt/anaconda3/lib/python3.8/site-packages/bert_serving/server/helper.py:175: UserWarning: Tensorflow 2.3.0 is not tested! It may or may not work. Feel free to submit an issue at https://github.com/hanxiao/bert-as-service/issues/
warnings.warn('Tensorflow %s is not tested! It may or may not work. '
usage: /opt/anaconda3/bin/bert-serving-start -model_dir /uncased_L-12_H-768_A-12/ -num_worker=2 -max_seq_len 50
ARG VALUE

---

       ckpt_name = bert_model.ckpt
     config_name = bert_config.json
            cors = *
             cpu = False
      device_map = []
   do_lower_case = True

fixed_embed_length = False
fp16 = False
gpu_memory_fraction = 0.5
graph_tmp_dir = None
http_max_connect = 10
http_port = None
mask_cls_sep = False
max_batch_size = 256
max_seq_len = 50
model_dir = /uncased_L-12_H-768_A-12/
no_position_embeddings = False
no_special_token = False
num_worker = 2
pooling_layer = [-2]
pooling_strategy = REDUCE_MEAN
port = 5555
port_out = 5556
prefetch_size = 10
priority_batch_size = 16
show_tokens_to_client = False
tuned_model_dir = None
verbose = False
xla = False

I:VENTILATOR:[__i:__i: 67]:freeze, optimize and export graph, could take a while...
/opt/anaconda3/lib/python3.8/site-packages/bert_serving/server/helper.py:175: UserWarning: Tensorflow 2.3.0 is not tested! It may or may not work. Feel free to submit an issue at https://github.com/hanxiao/bert-as-service/issues/
warnings.warn('Tensorflow %s is not tested! It may or may not work. '
E:GRAPHOPT:[gra:opt:154]:fail to optimize the graph!
Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.8/site-packages/bert_serving/server/graph.py", line 42, in optimize_graph
tf = import_tf(verbose=args.verbose)
File "/opt/anaconda3/lib/python3.8/site-packages/bert_serving/server/helper.py", line 186, in import_tf
tf.logging.set_verbosity(tf.logging.DEBUG if verbose else tf.logging.ERROR)
AttributeError: module 'tensorflow' has no attribute 'logging'
Traceback (most recent call last):
File "/opt/anaconda3/bin/bert-serving-start", line 8, in
sys.exit(main())
File "/opt/anaconda3/lib/python3.8/site-packages/bert_serving/server/cli/init.py", line 4, in main
with BertServer(get_run_args()) as server:
File "/opt/anaconda3/lib/python3.8/site-packages/bert_serving/server/init.py", line 71, in init
self.graph_path, self.bert_config = pool.apply(optimize_graph, (self.args,))
TypeError: cannot unpack non-iterable NoneType object

Then this issue shows up:

...

[majidhamzavi]

Hi there,
I have a problem with the starting server. It gives actually two errors, one with the "tf.logging" and the other one as "TypeError: cannot unpack non-iterable NoneType object".
Thanks

[oakieoaktree]

Similar issue here, seems to be very tricky dependencies management.

Suggested fix seems generally to be to downgrade to tensorflow>=1.10.

However older tensorflow<=2.0 seems not to be supported with Python 3.8.:

Python 3.8 support requires TensorFlow 2.2

Is tensorflow>=2.2 support planned for bert-serving-server?

[skro123]

我将tensorflow 1.15降到1.10，解决问题了。