Tensorflow-Lambda-Layer | Lets you import Tensorflow Keras from an AWS lambda | Serverless library
kandi X-RAY | Tensorflow-Lambda-Layer Summary
kandi X-RAY | Tensorflow-Lambda-Layer Summary
Tensorflow-Lambda-Layer is a Shell library typically used in Serverless, Tensorflow applications. Tensorflow-Lambda-Layer has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
It's a lambda layer that includes Tensorflow, Keras, and Numpy. You can use it to deploy serverless machine learning models. Serverless is especially nice for when you want to serve a model that will be accessed infrequently, without paying for an always-on ec2 instance. If you're a single developer or small org and all you want to do is show off your binary classifier, it's usually possible to stay within the free tier limits if you set things up right. And even if you're larger, serverless brings a lot of benefits, like transparent scaling and the ability to mostly ignore the hardware. The problem is, some packages (like Tensorflow) end up hard to use. This repo is an attempt to alleviate that problem.
It's a lambda layer that includes Tensorflow, Keras, and Numpy. You can use it to deploy serverless machine learning models. Serverless is especially nice for when you want to serve a model that will be accessed infrequently, without paying for an always-on ec2 instance. If you're a single developer or small org and all you want to do is show off your binary classifier, it's usually possible to stay within the free tier limits if you set things up right. And even if you're larger, serverless brings a lot of benefits, like transparent scaling and the ability to mostly ignore the hardware. The problem is, some packages (like Tensorflow) end up hard to use. This repo is an attempt to alleviate that problem.
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Quality
Security
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Tensorflow-Lambda-Layer has a low active ecosystem.
It has 82 star(s) with 11 fork(s). There are 8 watchers for this library.
It had no major release in the last 12 months.
There are 8 open issues and 6 have been closed. On average issues are closed in 0 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Tensorflow-Lambda-Layer is v1.8.0-2
Quality
Tensorflow-Lambda-Layer has 0 bugs and 0 code smells.
Security
Tensorflow-Lambda-Layer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Tensorflow-Lambda-Layer code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Tensorflow-Lambda-Layer is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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Tensorflow-Lambda-Layer releases are available to install and integrate.
Installation instructions are available. Examples and code snippets are not available.
It has 6 lines of code, 0 functions and 1 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Tensorflow-Lambda-Layer
Tensorflow-Lambda-Layer Key Features
No Key Features are available at this moment for Tensorflow-Lambda-Layer.
Tensorflow-Lambda-Layer Examples and Code Snippets
No Code Snippets are available at this moment for Tensorflow-Lambda-Layer.
Community Discussions
Trending Discussions on Tensorflow-Lambda-Layer
QUESTION
Multiple Inputs to Lambda Layer Tensorflow
Asked 2021-Sep-17 at 17:44
I'm trying to make an extremely simple example of an adder (adding together two scaler tensors) within a lambda layer in keras/tensorflow. Here is my minimal example:
...ANSWER
Answered 2021-Sep-17 at 17:44After some further debugging, I have solved the issue. The issue is because I have not included a batch dimension when calling the model.predict function.
Changing the predict line above to:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Tensorflow-Lambda-Layer
The code involved in generating these layers is all included in src and build_targets. The code is a collection of shell scripts that constructs, uploads, and publishes the lambda zipfiles. It reads AWS credentials from $HOME/.aws, and spawns an instance to actually run the build process (note: does not shut it off automatically).
requirements.txt: The pip packages to install
description.txt: The description that will be attached to the published layer
hook.sh: Extra commands that run as the last phase of the build step
test.py: A python file that should trigger an access of every file used by the library in the course of its execution
requirements.txt: The pip packages to install
description.txt: The description that will be attached to the published layer
hook.sh: Extra commands that run as the last phase of the build step
test.py: A python file that should trigger an access of every file used by the library in the course of its execution
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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