qnn | This is supported by Li Qiuchi and Waby

 by   wabyking Python Version: Current License: No License

kandi X-RAY | qnn Summary

kandi X-RAY | qnn Summary

qnn is a Python library. qnn has no bugs, it has no vulnerabilities and it has low support. However qnn build file is not available. You can download it from GitHub.

This is supported by Li Qiuchi (李秋池) and Waby.
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            kandi-support Support

              qnn has a low active ecosystem.
              It has 99 star(s) with 26 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 1 open issues and 4 have been closed. On average issues are closed in 217 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of qnn is current.

            kandi-Quality Quality

              qnn has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              qnn does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              qnn releases are not available. You will need to build from source code and install.
              qnn has no build file. You will be need to create the build yourself to build the component from source.
              qnn saves you 1798 person hours of effort in developing the same functionality from scratch.
              It has 3973 lines of code, 370 functions and 68 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed qnn and discovered the below as its top functions. This is intended to give you an instant insight into qnn implemented functionality, and help decide if they suit your requirements.
            • Run the model
            • Generate data
            • Calculate the matching score
            • Create embedding
            • Process training data
            • Convert a list into a numpy array
            • Get the results of a test
            • Calculate the objective function
            • Perform multi - perspective expansion
            • Cosine between two tensors
            • Calculate the cosentive matching
            • Process word embedding
            • Generate a lookup table
            • Generates a function that returns a random k - th function
            • Get the alphabet
            • Load data from file
            • Generate lookup table
            • Compute the rank - tange loss
            • Convert a list of lists to a numpy array
            • Get the results of the test
            • Parse config file
            • Calculate the score of a prediction
            • Generate sentence data
            • Calculate recurrent unit
            • Create a single embedding
            • Calculate the recall function
            • Callback function called when an option is called
            • Calculate the NDCD distribution
            • Compute word embedding
            • Parse grid parameters
            • The ablation layer
            Get all kandi verified functions for this library.

            qnn Key Features

            No Key Features are available at this moment for qnn.

            qnn Examples and Code Snippets

            No Code Snippets are available at this moment for qnn.

            Community Discussions

            QUESTION

            Quantum Neural Networks - Noise Models
            Asked 2021-Aug-09 at 12:35

            Surveying the QML module in Qiskit for a quantum neural network project and wondering if there is support to add noise models and run noisy simulations?

            Going through this tutorial and wondering how one would define a noise model in the argument of qnn.forward when doing a batched forward pass.

            ...

            ANSWER

            Answered 2021-Aug-09 at 11:40

            You can create a noisy simulator like in the snippet below and then use it when you create a QuantumInstance:

            Source https://stackoverflow.com/questions/68709800

            QUESTION

            Trying to provide a value into variable that is a function
            Asked 2020-Oct-03 at 09:05

            I'm trying to figure out how to provide a string value into this function and can't solve my problem. I have an array and a function that checks if value is included in the array.

            It looks like this:

            ...

            ANSWER

            Answered 2020-Oct-03 at 09:05

            You should be defined findSentence function.

            Source https://stackoverflow.com/questions/64182473

            QUESTION

            Expected object of device type cuda but got device type cpu for argument #2 'mat2' in call to _th_mm
            Asked 2020-Jul-14 at 07:46

            I recently have access to a GPU and have tried to run my code but there is an error. I've read about adding .cuda() to the layers could help but I have ran similar code without the "qml" part and it worked just fine without changing the layer (with cuda I mean). For the sake of brevity, I only added the class for the neural network and the entire loop of the code. The missing part of the code is for other aspects. But if there is a need for the rest of the code, I would be happy to include everything.

            Code:

            ...

            ANSWER

            Answered 2020-Jul-14 at 07:46

            The solution is that the python package "pennylane" doesn't yet have the resources built out to work on GPUs. Since Pennylane is a relatively new package, this is something they plan to build out in the future.

            Source https://stackoverflow.com/questions/62780158

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

            Vulnerabilities

            No vulnerabilities reported

            Install qnn

            You can download it from GitHub.
            You can use qnn like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            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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            gh repo clone wabyking/qnn

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            git@github.com:wabyking/qnn.git

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