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[bitnami/tensorflow-resnet] Release 2.14.1-debian-11-r6 (#55196)
Signed-off-by: Bitnami Containers <bitnami-bot@vmware.com>
This commit is contained in:
@@ -7,10 +7,10 @@ ARG TARGETARCH
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LABEL com.vmware.cp.artifact.flavor="sha256:1e1b4657a77f0d47e9220f0c37b9bf7802581b93214fff7d1bd2364c8bf22e8e" \
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org.opencontainers.image.base.name="docker.io/bitnami/minideb:bullseye" \
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org.opencontainers.image.created="2023-12-26T14:01:04Z" \
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org.opencontainers.image.created="2024-01-20T05:18:20Z" \
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org.opencontainers.image.description="Application packaged by VMware, Inc" \
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org.opencontainers.image.licenses="Apache-2.0" \
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org.opencontainers.image.ref.name="2.14.1-debian-11-r5" \
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org.opencontainers.image.ref.name="2.14.1-debian-11-r6" \
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org.opencontainers.image.title="tensorflow-resnet" \
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org.opencontainers.image.vendor="VMware, Inc." \
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org.opencontainers.image.version="2.14.1"
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@@ -40,6 +40,7 @@ RUN mkdir -p /tmp/bitnami/pkg/cache/ ; cd /tmp/bitnami/pkg/cache/ ; \
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RUN apt-get update && apt-get upgrade -y && \
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apt-get clean && rm -rf /var/lib/apt/lists /var/cache/apt/archives
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RUN chmod g+rwX /opt/bitnami
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RUN find / -perm /6000 -type f -exec chmod a-s {} \; || true
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RUN mkdir /.local && chmod g+rwX /.local
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COPY rootfs /
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@@ -1,25 +0,0 @@
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# Copyright VMware, Inc.
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# SPDX-License-Identifier: APACHE-2.0
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version: "2"
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services:
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tensorflow-serving:
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image: docker.io/bitnami/tensorflow-serving:2
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ports:
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- 8500:8500
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- 8501:8501
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volumes:
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- "tensorflow_serving_data:/bitnami"
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- "/tmp/model-data:/bitnami/model-data"
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tensorflow-resnet:
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image: docker.io/bitnami/tensorflow-resnet:2
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depends_on:
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- tensorflow-serving
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volumes:
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- "tensorflow_resnet_data:/bitnami"
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- "/tmp/model-data:/bitnami/model-data"
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volumes:
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tensorflow_serving_data:
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driver: local
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tensorflow_resnet_data:
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driver: local
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@@ -10,7 +10,7 @@ fi
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script=$1
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exit_code="${2:-96}"
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fail_if_not_present="${3:-y}"
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fail_if_not_present="${3:-n}"
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if test -f "$script"; then
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sh $script
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@@ -18,13 +18,6 @@ curl -o resnet_50_classification_1.tar.gz https://storage.googleapis.com/tfhub-m
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tar xzf resnet_50_classification_1.tar.gz -C 1
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```
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### Docker Compose
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```console
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curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/tensorflow-resnet/docker-compose.yml > docker-compose.yml
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docker-compose up -d
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```
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## Why use Bitnami Images?
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* Bitnami closely tracks upstream source changes and promptly publishes new versions of this image using our automated systems.
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@@ -50,27 +43,16 @@ Subscribe to project updates by watching the [bitnami/containers GitHub repo](ht
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## Prerequisites
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To run this application you need Docker Engine 1.10.0. Docker Compose is recommended with a version 1.6.0 or later.
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To run this application you need Docker Engine 1.10.0.
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## How to use this image
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### Run TensorFlow ResNet client with TensorFlow Serving
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Running TensorFlow ResNet client with the TensorFlow Serving server is the recommended way. You can either use docker-compose or run the containers manually.
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#### Run the application using Docker Compose
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The main folder of this repository contains a functional [`docker-compose.yml`](https://github.com/bitnami/containers/blob/main/bitnami/tensorflow-resnet/docker-compose.yml) file. Run the application using it as shown below:
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```console
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curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/tensorflow-resnet/docker-compose.yml > docker-compose.yml
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docker-compose up -d
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```
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Running TensorFlow ResNet client with the TensorFlow Serving server is the recommended way.
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#### Run the application manually
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If you want to run the application manually instead of using docker-compose, these are the basic steps you need to run:
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1. Create a new network for the application and the database:
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```console
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@@ -103,8 +85,7 @@ Bitnami provides up-to-date versions of Tensorflow-Serving and TensorFlow ResNet
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2. Stop your container
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* For docker-compose: `$ docker-compose stop tensorflow-resnet`
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* For manual execution: `$ docker stop tensorflow-resnet`
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* `$ docker stop tensorflow-resnet`
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3. Take a snapshot of the application state
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@@ -118,13 +99,11 @@ You can use these snapshots to restore the application state should the upgrade
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1. Remove the currently running container
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* For docker-compose: `$ docker-compose rm tensorflow-resnet`
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* For manual execution: `$ docker rm tensorflow-resnet`
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* `$ docker rm tensorflow-resnet`
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2. Run the new image
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* For docker-compose: `$ docker-compose up tensorflow-resnet`
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* For manual execution (mount the directories if needed): `docker run --name tensorflow-resnet bitnami/tensorflow-resnet:latest`
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* Mount the directories if needed: `docker run --name tensorflow-resnet bitnami/tensorflow-resnet:latest`
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## Configuration
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@@ -162,11 +141,21 @@ Once you have deployed both the TensorFlow Serving and TensorFlow ResNet contain
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Tensorflow Resnet can be customized by specifying environment variables on the first run. The following environment values are provided to custom Tensorflow:
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* `TF_RESNET_SERVING_PORT_NUMBER`: TensorFlow Serving Port. Default: **8500**
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* `TF_RESNET_SERVING_HOST`: TensorFlow Serving server name. Default: **tensorflow-serving**
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#### Customizable environment variables
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| Name | Description | Default Value |
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|---------------------------------|--------------------------------|----------------------|
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| `TF_RESNET_SERVING_PORT_NUMBER` | Tensorflow serving port number | `8500` |
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| `TF_RESNET_SERVING_HOST` | Tensorflow serving host name | `tensorflow-serving` |
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#### Read-only environment variables
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## Notable Changes
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### Starting January 16, 2024
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* The `docker-compose.yaml` file has been removed, as it was solely intended for internal testing purposes.
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### 2.4.1-debian-10-r87
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* The container initialization logic is now using bash.
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