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Generic and easy-to-use serving service for machine learning models

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Usually systems which are in production require, loading of new versions on run-time and even unloading previous versions of model. Is there any way to achieve same using this framework...

错误如下: Traceback (most recent call last): File "example.py", line 8, in model.train(ckpt_dir='ckpt') File "/home/zy/ORGAN/ORGAN-master/organ/__init__.py", line 738, in train self.pretrain() File "/home/zy/ORGAN/ORGAN-master/organ/__init__.py", line 663, in pretrain _, g_loss, g_pred = self.generator.pretrain_step(self.sess,batch)...

The error I got: File "/usr/local/lib/python3.8/site-packages/flask/app.py", line 2447, in wsgi_app response = self.full_dispatch_request() File "/usr/local/lib/python3.8/site-packages/flask/app.py", line 1952, in full_dispatch_request rv = self.handle_user_exception(e) File "/usr/local/lib/python3.8/site-packages/flask_cors/extension.py", line 165, in wrapped_function return cors_after_request(app.make_response(f(*args,...

Traceback (most recent call last): File "/usr/local/bin/simple_tensorflow_serving", line 11, in load_entry_point('simple-tensorflow-serving==0.6.6', 'console_scripts', 'simple_tensorflow_serving')() File "/usr/local/lib/python2.7/site-packages/pkg_resources/__init__.py", line 487, in load_entry_point Create path to host static files: static return get_distribution(dist).load_entry_point(group, name) File...

Hi, How to run TFserving GPU image with http basic auth enabled? https://github.com/tobegit3hub/simple_tensorflow_serving/blob/master/Dockerfile.latest-gpu uses simple_tensorflow_serving: `CMD ["simple_tensorflow_serving", "--port=8500", "--model_config_file=./examples/model_config_file.json"]` which don't have any auth related settings: https://github.com/tobegit3hub/simple_tensorflow_serving/blob/master/simple_tensorflow_serving/command.py

I was trying to use your Docker, however there seems to be a problem. For example, when trying to run the docker with the following command, it fails with an...

Traceback (most recent call last): File "c:\users\anand\appdata\local\continuum\anaconda3\envs\venv\lib\runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "c:\users\anand\appdata\local\continuum\anaconda3\envs\venv\lib\runpy.py", line 85, in _run_code exec(code, run_globals) File "C:\Users\anand\AppData\Local\Continuum\anaconda3\envs\venv\Scripts\simple_tensorflow_serving.exe\__main__.py", line 5, in File "c:\users\anand\appdata\local\continuum\anaconda3\envs\venv\lib\site-packages\simple_tensorflow_serving\server.py", line 236,...

Is there a feature of batch merge calculation to improve GPU utilization? There is a batch merge in tensorflow-serving, which is very helpful for development and deployment. thanks

Thank you for your work and sharing.I want to ask a question, when will this project support grpc?@tobegit3hub

ynamic library libcublas.so.10.0 2019-12-11 13:50:47.813434: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0 2019-12-11 13:50:47.813444: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0 2019-12-11 13:50:47.813452: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0...