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A flexible, high-performance serving system for machine learning models

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I can't use s3 (minio) with TensorFlow serving version (2.8->2.9) on Docker. It gets an error: ```bash Failed to start the server. Error: UNIMPLEMENTED: File system scheme 's3' not implemented...

stat:awaiting tensorflower
type:bug

## Bug Report ### System information - **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**: Linux - **TensorFlow Serving installed from (source or binary)**: docker image - **TensorFlow Serving version**:...

stat:awaiting response
type:bug

### System information - OS: * Windows 11, 21H2, build 22000.856 * WSL2, Ubuntu 22.04 -- allocated 8Gb in .wslconfig - TF Serving installed using docker, version 2.9.1 - Hardware:...

stat:awaiting tensorflower
type:bug

…rs/http_server.cc and all net_http files accordingly. Also, removed everything from net_http/client except test_client to make room for new client API and basic implementation as specified in pull request #1912

## Feature Request ### Describe the problem the feature is intended to solve I have thousands of models to be served, but quite a big part of these models are...

type:feature
stat:awaiting tensorflower
needs prio
type:performance

I have seen through both documentation and API documentation for save and many other functions related to model building but I could not find enough documentation about building a model...

type:docs
stat:awaiting tensorflower

There exist two configuration parameters in TensorFlow serving to utilize CPU called `tensorflow_intra_op_parallelism` and `tensorflow_inter_op_parallelism` which tuning them can have great impact on the model server performance (throughput, latency). I...

type:docs
stat:awaiting response

### System information - **OS Platform and Distribution (Linux Ubuntu 16.04)**: - **TensorFlow Serving installed from (source and binary)**: - **TensorFlow Serving version is 2.5.2**: ### Describe the problem 1....

stat:awaiting response
type:bug

I'm trying to server my Object Detection model via TF Serving and I'm unable to get results on the client side script. ![Screenshot from 2022-09-15 12-49-31](https://user-images.githubusercontent.com/54833067/190340410-47384faf-ef32-4632-8873-ff19fd843728.png) I'm running this in...

stat:awaiting response
type:support

Updating link for GPU docker file from "https://github.com/tensorflow/serving/blob/master/tensorflow_serving/tools/docker/Dockerfile.devel-gpu" to "https://github.com/tensorflow/serving/blob/master/tensorflow_serving/tools/docker/Dockerfile.gpu". Reference Issue: https://github.com/tensorflow/serving/issues/2053