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 git@github.com:Yoctol/serving-utils.git 2. Manually install tensorflow CPU or GPU version. 3. make install
Usage
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 ```
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(…) ```
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 ```
1 maintainer
Metadata
1 maintainer
Release files for serving-utils 0.10.0
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