Rosetta | A Privacy-Preserving Framework Based on TensorFlow | Privacy library

 by   LatticeX-Foundation C++ Version: v1.0.0 License: LGPL-3.0

kandi X-RAY | Rosetta Summary

kandi X-RAY | Rosetta Summary

Rosetta is a C++ library typically used in Security, Privacy, Tensorflow applications. Rosetta has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has low support. You can download it from GitHub.

Rosetta is a privacy-preserving framework based on TensorFlow. It integrates with mainstream privacy-preserving computation technologies, including cryptography, federated learning and trusted execution environment. Rosetta aims to provide privacy-preserving solutions for artificial intelligence without requiring expertise in cryptography, federated learning and trusted execution environment. Rosetta reuses the APIs of TensorFlow and allows to transfer traditional TensorFlow codes into a privacy-preserving manner with minimal changes. E.g., just add the following line. The current version integrates the secure multi-party computation protocols for 3 parties. The underlying protocol is SecureNN. It is secure in the semi-honest model with honest majority. And we are integrating more MPC protocols continuously.
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            kandi-support Support

              Rosetta has a low active ecosystem.
              It has 525 star(s) with 111 fork(s). There are 29 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 2 open issues and 75 have been closed. On average issues are closed in 247 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Rosetta is v1.0.0

            kandi-Quality Quality

              Rosetta has 0 bugs and 0 code smells.

            kandi-Security Security

              Rosetta has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              Rosetta code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              Rosetta is licensed under the LGPL-3.0 License. This license is Weak Copyleft.
              Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

            kandi-Reuse Reuse

              Rosetta releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

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            Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Rosetta
            Get all kandi verified functions for this library.

            Rosetta Key Features

            No Key Features are available at this moment for Rosetta.

            Rosetta Examples and Code Snippets

            Create a side by side plot using imshow
            Pythondot img1Lines of Code : 10dot img1License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            fig, (ax1, ax2) = plt.subplots(1, 2)
            fig.suptitle('Horizontally stacked subplots')
            ax1.plot(x, y)
            ax2.plot(x, -y)
            
            fig, (ax1, ax2) = plt.subplots(1, 2)
            ax1.imshow(dprof[0, :, :], extent=[-l, l, -l, l], interpolation

            Community Discussions

            QUESTION

            Cypress.io on Apple Silicon M1 with Yarn – "Cypress failed to start. This may be due to a missing library or dependency."
            Asked 2022-Apr-03 at 03:49

            I try to use Cypress for tests. With Laravel and Yarn as a package (v8.3.1) on MacBook with Apple M1 chip. Installation was ok, but all I can see after cypress open is:

            ...

            ANSWER

            Answered 2021-Sep-08 at 06:46

            You can try installing it with the --force flag

            Source https://stackoverflow.com/questions/69097958

            QUESTION

            Why Python native on M1 Max is greatly slower than Python on old Intel i5?
            Asked 2022-Mar-29 at 03:35

            I just got my new MacBook Pro with M1 Max chip and am setting up Python. I've tried several combinational settings to test speed - now I'm quite confused. First put my questions here:

            • Why python run natively on M1 Max is greatly (~100%) slower than on my old MacBook Pro 2016 with Intel i5?
            • On M1 Max, why there isn't significant speed difference between native run (by miniforge) and run via Rosetta (by anaconda) - which is supposed to be slower ~20%?
            • On M1 Max and native run, why there isn't significant speed difference between conda installed Numpy and TensorFlow installed Numpy - which is supposed to be faster?
            • On M1 Max, why run in PyCharm IDE is constantly slower ~20% than run from terminal, which doesn't happen on my old Intel Mac.

            Evidence supporting my questions is as follows:

            Here are the settings I've tried:

            1. Python installed by

            • Miniforge-arm64, so that python is natively run on M1 Max Chip. (Check from Activity Monitor, Kind of python process is Apple).
            • Anaconda. Then python is run via Rosseta. (Check from Activity Monitor, Kind of python process is Intel).

            2. Numpy installed by

            • conda install numpy: numpy from original conda-forge channel, or pre-installed with anaconda.
            • Apple-TensorFlow: with python installed by miniforge, I directly install tensorflow, and numpy will also be installed. It's said that, numpy installed in this way is optimized for Apple M1 and will be faster. Here is the installation commands:
            ...

            ANSWER

            Answered 2021-Dec-06 at 05:53
            Possible Cause: Different BLAS Libraries

            Since the benchmark is running linear algebra routines, what is likely being tested here are the BLAS implementations. A default Anaconda distribution for osx-64 platform is going to come with Intel's MKL implementation; the osx-arm64 platform only has the generic Netlib BLAS and the OpenBLAS implementation options.

            For me (MacOS w/ Intel i9), I get the following benchmark results:

            BLAS Implmentation Mean Timing (s) mkl 0.95932 blis 1.72059 openblas 2.17023 netlib 5.72782

            So, I suspect the old MBP had MKL installed, and the M1 system is installing either Netlib or OpenBLAS. Maybe try figuring out whether Netlib or OpenBLAS are faster on M1, and keep the faster one.

            Specifying BLAS Implementation

            Here are specifically the different environments I tested:

            Source https://stackoverflow.com/questions/70240506

            QUESTION

            ImportError when importing psycopg2 on M1
            Asked 2022-Mar-23 at 22:05

            Has anyone gotten this error when importing psycopg2 after successful installation?

            ...

            ANSWER

            Answered 2022-Mar-23 at 02:21

            Using this line should fix it:

            Source https://stackoverflow.com/questions/71580859

            QUESTION

            arch x86_64 and arm64e is available but python3 is saying incompatible architecture on Mac M1
            Asked 2022-Mar-12 at 15:24

            I am trying to run this reading-text-in-the-wild on Mac M1. When I attempt to run this code

            ...

            ANSWER

            Answered 2022-Jan-17 at 17:39

            the package you are using is not compatible with the new mac hardware by the looks of it. You will need to run this using Rosetta 2, which is an apple system component.

            Source https://stackoverflow.com/questions/70723757

            QUESTION

            Cannot run debug Go using VSCode on Mac M1
            Asked 2022-Mar-07 at 13:30

            I found a topic that encounter the same problem (Can't debug Golang in vscode apple m1) but I'm not sure it's an old solution or not because I'm using the Go version

            ...

            ANSWER

            Answered 2021-Sep-27 at 22:37
            1. Ensure your VSCode uses the arm64 version. (it can use a different go version from the system)

            2. Run Go: install/update tools. It will rebuild all tools with the arm64 go version.

            Source https://stackoverflow.com/questions/69343900

            QUESTION

            Cannot Reparent even after Unmapping in X11
            Asked 2022-Mar-06 at 19:55

            I am working with X11 and want to perform a re-parent. I got an example hello world application from Rosetta Code in C. I made some modification to make it 2 windows.

            ...

            ANSWER

            Answered 2022-Mar-06 at 19:55

            I just reproduced that behavior on my Linux machine.

            The problem seems to be a timing problem between your program and the "Window manager".

            The "Window manager" is the program which is responsible for drawing the title bar and maybe borders at the windows. The "Window manager" works like this:

            Whenever a window is mapped on the root window, the "Window manager" is notified by X11. The "Window manager" creates an "outer window" that contains the title bar and the border. Then it reparents the window so the window becomes a child window of the "outer window".

            Example:

            If the "Window manager" handles some window after being mapped, it becomes a child window of the "outer window"; for this reason, any window that is not a child window of an "outer window" is obviously not handled by the "Window manager" if it is mapped.

            ... at least in the "normal case".

            For this reason, the "Window manager" does not care about windows that are un-mapped on the root window (but only about windows that are un-mapped from an "outer window").

            Normally, the "Window manager" behaves like this:

            Source https://stackoverflow.com/questions/71372964

            QUESTION

            Unable to start a Cloud Run container on M1 Macbook
            Asked 2022-Feb-10 at 21:10

            I haven't installed Rosetta on my M1 Macbook. Have Docker and all deps installed and this even worked a few times but not sure what caused this error suddenly:

            ...

            ANSWER

            Answered 2022-Feb-10 at 21:10

            I can confirm that the gcr.io/google.com/cloudsdktool/cloud-sdk:slim image used in your Dockerfile is an x86_64 image, which is incompatible with an ARM64-based M1 Mac. Since CloudSDK does not currently have any ARM64-based images, creating your own base image with CloudSDK will be necessary. The steps to do that are:

            1. Update the line in your Dockerfile pointing to gcr.io/google.com/cloudsdktool/cloud-sdk:slim to a new base image (debian:buster-slim for example)
            2. Install the CloudSDK tooling onto the image. It should look something like this in your Dockerfile:

            Source https://stackoverflow.com/questions/70902923

            QUESTION

            GO VSCode debugger not working on Apple with M1 Chip
            Asked 2022-Jan-28 at 09:07

            I can run the go files, but I can't debug them in vscode.

            Error: "Failed to launch: could not launch process: can not run under Rosetta, check that the installed build of Go is right for your CPU architecture"

            ...

            ANSWER

            Answered 2021-Oct-15 at 19:50

            I ran into this as well after an upgrade to an Apple with an M1. There are several steps toward diagnosing the root cause of the issue. The first is to check the version of Go you've got installed.

            Source https://stackoverflow.com/questions/69589662

            QUESTION

            How can I create a script to switch between my ARM conda and x84 conda?
            Asked 2022-Jan-17 at 04:25

            I am on an apple silicon M1 MacBook Pro. I would like to have a native ARM python environment, and an environment that runs on x86 architecture with rosetta 2. I have installed two mini forge distributions, both in the home directory: miniforge3 for the native ARM installation and miniforge3_x86_64 for the x86 installation.

            ...

            ANSWER

            Answered 2022-Jan-17 at 04:25

            So far, the best solution I've found is to start the terminal with Rosetta 2, then run a function I have saved in .zshrc to initialize the correct conda installation so that I can use the correct architecture for my needs depending on the situation.

            My current solution is the following function named x86:

            Source https://stackoverflow.com/questions/70524577

            QUESTION

            What does M1 mac optimization process for an application mean?
            Asked 2021-Dec-10 at 20:38

            You know the ARM-based M1 chips that are used in modern mac computers. On those macs, some number of software are ran through the layer called Rosetta (Discord, Steam), some natively, directly through M1 (Slack, IntelliJ) and some actually doesn't work in either way (Virtual Box). Huge list holding the status can be found here.

            Apps that can be ran only with Rosetta are not yet M1 optimized, their developers have to optimize it, it takes some time to do so. But what does it mean to optimize it? What the process looks like? I'm quite sure that they don't rewrite the whole application code to another language (like Swift), because Jetbrains was able to M1 optimize their apps quite quickly. On the other hand, Discord is not yet optimized, same for Unity game engine (it's in beta though).

            ...

            ANSWER

            Answered 2021-Dec-10 at 20:38

            At bottom, it just means that the compiler's backend was configured to emit ARM64 instructions for the program instead of (or in-addition to) x86-64 instructions.

            This means that certain x86-64 specific functionality instruction can no longer be used, unless equivalent ARM instructions are used instead.

            This usually isn't much of a problem though, because most macOS software is typically written at a higher level of abstraction, using system-provided frameworks.

            For example, using CoreImage to manipulate images abstracts you from the details of the CPU and GPU. In such cases, Apple does the heavy lifting of porting over their frameworks. All you have to do as an application developer is to check a box that says "target ARM64".

            Source https://stackoverflow.com/questions/70310035

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install Rosetta

            For now, Rosetta runs on Ubuntu 18.04, and is based on TensorFlow 1.14 with CPUs (Windows OS is not currently supported yet). You can install Rosetta as follows. First, please check that your local system meets our base environment requirement. Then install the native TensorFlow with the following codes. Note that you could also install it from source code, check here for details. And then build and install Rosetta with our all-in-one script as follows. Before running your program, you should configure with your network topology so that a distributed network can be established for parties to communicate with each other. You could use an example to check everything runs OK. Please refer to Deployment Guide for the detailed steps of installation, configuration and deployment of Rosetta.
            To help you start with your first workable program with Rosetta easily, our Tutorials will lead you to this fantastic world. In this detailed tutorials, we will assist you learn the basic concepts about Rosetta, then show you how to use the interfaces that we provide by easy-to-understand examples, and finally help you build a workable privacy-preserving machine learning model on real-world datasets. Hopefully, this tutorial, and more other examples in Examples, will whet your appetite to dive in knowing more about this privacy-preserving framework.

            Support

            Rosetta is an open source project developed under the LPGLv3 license and maintained by LatticeX Foundation. Contributions from individuals and organizations are all welcome. Before beginning, please take a look at our contributing guidelines. Our project adheres to code of conduct. By participating in our community, you are expected to uphold this code. You could also open an issue by clicking here.
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            https://github.com/LatticeX-Foundation/Rosetta.git

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            gh repo clone LatticeX-Foundation/Rosetta

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            git@github.com:LatticeX-Foundation/Rosetta.git

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