serving-utils 0.10.0

Some utilities for tensorflow serving

serving-utils

Some python utilities when using tensorflow-serving.

Installation

Prepare an environment with python version >= 3.6

From PYPI: 1. Manually install tensorflow CPU or GPU version. 2. pip install serving-utils

From Github repository: 1. git clone [e-mail]:Yoctol/serving-utils.git 2. Manually install tensorflow CPU or GPU version. 3. make install

Usage

1. Saver and Loader ```python import tensorflow as tf

from serving_utils.saver import Saver from serving_utils.loader import Loader

saver = Saver( session=tf.Session(graph=your_graph), output_dir=’/path/to/serving’, signature_def_map={ ‘predict’: tf.saved_model.signature_def_utils.predict_signature_def( inputs={‘input’: tf.Tensor…}, outputs={‘output’: tf.Tensor…}, ) }, freeze=True, # (default: True) Frozen graph will be saved if True. ) saver.save()

loader = Loader( path=’/path/to/serving’, # version=1, # if not specified, use the latest version ) new_sess = tf.Session()

loader.load(new_sess) # load the saved model into new session ```

2. Client ```python from serving_utils import Client client = Client(host=”localhost”, port=8500, n_trys=3) client.predict( {‘input’: np.ones(1, 10)}, output_names=[‘output’], model_signature_name=’predict’, )

or async

await client.async_predict(…) ```

3. Freeze graph ```python from serving_utils.freeze_graph import freeze_graph, create_session_from_graphdef

frozen_graph_def = freeze_graph(session, output_op_names) new_session = create_session_from_graphdef(frozen_graph_def)

## Test

Run the following commands:

make lint make test

## Dev

make install-dev

### Protos

python -m grpc_tools.protoc -I. –python_out=. –python_grpc_out=. –grpc_python_out=. serving_utils/protos/*.proto ```