Update version to 0.3.0

Author: RobertLucian

README.md

@@ -60,7 +60,7 @@ Some of Nucleus's features include:
 <!-- UPDATE THIS VERSION ON EACH RELEASE (it's better than using "master") -->
 
 ```bash
-pip install git+https://github.com/cortexlabs/nucleus.git@0.2.2
+pip install git+https://github.com/cortexlabs/nucleus.git@0.3.0
 ```
 
 ## Example usage
@@ -1136,7 +1136,7 @@ class Handler:
     # define any handler methods for HTTP/gRPC workloads here
 ```
 
-When explicit model paths are specified in the Python handler's Nucleus configuration, Nucleus provides a `model_client` to your Handler's constructor. `model_client` is an instance of [ModelClient](https://github.com/cortexlabs/nucleus/tree/master/src/cortex/cortex_internal/lib/client/python.py) that is used to load model(s) (it calls the `load_model()` method of your handler, which must be defined when using explicit model paths). It should be saved as an instance variable in your handler class, and your handler method should call `model_client.get_model()` to load your model for inference. Preprocessing of the JSON/gRPC payload and postprocessing of predictions can be implemented in your handler method as well.
+When explicit model paths are specified in the Python handler's Nucleus configuration, Nucleus provides a `model_client` to your Handler's constructor. `model_client` is an instance of [ModelClient](https://github.com/cortexlabs/nucleus/tree/0.3/src/cortex/cortex_internal/lib/client/python.py) that is used to load model(s) (it calls the `load_model()` method of your handler, which must be defined when using explicit model paths). It should be saved as an instance variable in your handler class, and your handler method should call `model_client.get_model()` to load your model for inference. Preprocessing of the JSON/gRPC payload and postprocessing of predictions can be implemented in your handler method as well.
 
 When multiple models are defined using the Handler's `multi_model_reloading` field, the `model_client.get_model()` method expects an argument `model_name` which must hold the name of the model that you want to load (for example: `self.client.get_model("text-generator")`). There is also an optional second argument to specify the model version.
 
@@ -1310,7 +1310,7 @@ class Handler:
     # define any handler methods for HTTP/gRPC workloads here
 ```
 
-Nucleus provides a `tensorflow_client` to your Handler's constructor. `tensorflow_client` is an instance of [TensorFlowClient](https://github.com/cortexlabs/nucleus/tree/master/src/cortex/cortex_internal/lib/client/tensorflow.py) that manages a connection to a TensorFlow Serving container to make predictions using your model. It should be saved as an instance variable in your Handler class, and your handler method should call `tensorflow_client.predict()` to make an inference with your exported TensorFlow model. Preprocessing of the JSON payload and postprocessing of predictions can be implemented in your handler method as well.
+Nucleus provides a `tensorflow_client` to your Handler's constructor. `tensorflow_client` is an instance of [TensorFlowClient](https://github.com/cortexlabs/nucleus/tree/0.3/src/cortex/cortex_internal/lib/client/tensorflow.py) that manages a connection to a TensorFlow Serving container to make predictions using your model. It should be saved as an instance variable in your Handler class, and your handler method should call `tensorflow_client.predict()` to make an inference with your exported TensorFlow model. Preprocessing of the JSON payload and postprocessing of predictions can be implemented in your handler method as well.
 
 When multiple models are defined using the Handler's `models` field, the `tensorflow_client.predict()` method expects a second argument `model_name` which must hold the name of the model that you want to use for inference (for example: `self.client.predict(payload, "text-generator")`). There is also an optional third argument to specify the model version.
 

nucleus/templates/handler.Dockerfile

@@ -1,6 +1,6 @@
 # to replace when building the dockerfile
 FROM $BASE_IMAGE
-ENV CORTEX_MODEL_SERVER_VERSION=master
+ENV CORTEX_MODEL_SERVER_VERSION=0.3.0
 
 RUN apt-get update -qq && apt-get install -y -q \
         build-essential \

nucleus/templates/tfs.Dockerfile

@@ -1,2 +1,2 @@
 FROM $BASE_IMAGE
-ENV CORTEX_MODEL_SERVER_VERSION=master
+ENV CORTEX_MODEL_SERVER_VERSION=0.3.0

setup.py

@@ -14,7 +14,7 @@
 
 import setuptools
 
-CORTEX_MODEL_SERVER_VERSION = "master"
+CORTEX_MODEL_SERVER_VERSION = "0.3.0"
 
 with open("requirements.txt") as fp:
     install_requires = fp.read()

src/cortex/cortex_internal/consts.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 
 SINGLE_MODEL_NAME = "_cortex_default"
-MODEL_SERVER_VERSION = "master"
+MODEL_SERVER_VERSION = "0.3.0"

src/cortex/setup.py

@@ -17,7 +17,7 @@
 import pkg_resources
 from setuptools import setup, find_packages
 
-CORTEX_MODEL_SERVER_VERSION = "master"
+CORTEX_MODEL_SERVER_VERSION = "0.3.0"
 
 with pathlib.Path("cortex_internal.requirements.txt").open() as requirements_txt:
     install_requires = [