torchsample | Level Training , Data Augmentation | Machine Learning library

by ncullen93 Python Version: v0.1.3 License: Non-SPDX

X-Ray Key Features Code Snippets(1)Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | torchsample Summary

torchsample is a Python library typically used in Manufacturing, Utilities, Energy, Utilities, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. torchsample has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However torchsample has a Non-SPDX License. You can download it from GitHub.

High-Level Training, Data Augmentation, and Utilities for Pytorch

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Quality

Security

License

Reuse

Support

torchsample has a medium active ecosystem.

It has 1817 star(s) with 303 fork(s). There are 59 watchers for this library.

It had no major release in the last 12 months.

There are 47 open issues and 42 have been closed. On average issues are closed in 74 days. There are 11 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of torchsample is v0.1.3

Quality

torchsample has 0 bugs and 0 code smells.

Security

torchsample has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

torchsample code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

torchsample has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

torchsample releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed torchsample and discovered the below as its top functions. This is intended to give you an instant insight into torchsample implemented functionality, and help decide if they suit your requirements.

Train the model
Return the number of inputs and targets
Adds a loss function to the loss function
Get the value of the regularizers
Fit the model
Evaluate a loader
Extract num_inputs and targets from a loader
Folds a batch affine
Batch trilinear interpolation
Called when an epoch is finished
Process transform argument
Apply the th transformation to a 3D matrix
Predict targets
Fine a 2D affine
Process co - transform argument
Finds inputs and targets and targets
Apply a transformation to a 3D matrix
Create train and test dataset
Add a co - transform to the co - transform
Add an input transform
Add a new target transform
Predict from a given loader
Load the tensor
Compile the model
Return a summary for each module
Split the DataFrame by a given column

Get all kandi verified functions for this library.

torchsample Key Features

No Key Features are available at this moment for torchsample.

torchsample Examples and Code Snippets

Deep Plastic Surgery,Usage:

Python

Lines of Code : 2

License : No License

Copy

git clone https://github.com/TAMU-VITA/DeepPS.git
cd DeepPS/src

Community Discussions

Trending Discussions on torchsample

Implementing Early Stopping in Pytorch without Torchsample

numpy array type not supported?

ValueError: only one element tensors can be converted to Python scalars

Can't parse arguments (deep learning tutorial using pytorch)

QUESTION

Implementing Early Stopping in Pytorch without Torchsample

Asked 2021-Aug-25 at 21:07

As a Pytorch newbie (coming from tensorflow), I am unsure of how to implement Early Stopping. My research has led me discover that pytorch does not have a native way to so this. I have also discovered torchsample, but am unable to install it in my conda environment for whatever reason. Is there a simple way to go about applying early stopping without it? Here is my current setup:

...

ANSWER

Answered 2021-Aug-25 at 21:07

A basic way to do this is to keep track of the best validation loss obtained so far.

You can have a variable best_loss = 0 initialized before your loop over epochs (or you could do other things like best loss per epoch, etc.).

After each validation pass then do:

Source https://stackoverflow.com/questions/68929471

QUESTION

numpy array type not supported?

Asked 2020-Jul-24 at 14:58

I'm trying to copy a model I was able to follow and run through a tutorial, but this time with my own data.

I was able to convert my own MRI images to numpy arrays in the same dimensions as the arrays the tutorial data is.

I tried replacing the numpy arrays in my tutorial with my own arrays and writing my own fictional csv file for normal or abnormal (case, not case).

However when I run it, I get:

...

ANSWER

Answered 2020-Jul-24 at 14:58

You can redefining the variable with astype

Source https://stackoverflow.com/questions/63075914

QUESTION

ValueError: only one element tensors can be converted to Python scalars

Asked 2020-Jul-19 at 10:06

I'm following this tutorial.

I'm at the last part where we combine the models in a regression.

I'm coding this in jupyter as follows:

...

ANSWER

Answered 2020-Jul-19 at 09:49

Only a tensor that contains a single value can be converted to a scalar with item(), try printing the contents of prediction, I imagine this is a vector of probabilities indicating which label is most likely. Using argmax on prediction will give you your actual predicted label (assuming your labels are 0-n).

Source https://stackoverflow.com/questions/62978582

QUESTION

Can't parse arguments (deep learning tutorial using pytorch)

Asked 2020-Jul-15 at 00:30

I'm following this tutorial.

The first scripts run fine and I have a "data" folder in the folder of my scripts containing the MRI data downloaded from MRnet.

However when it comes to the "train" script I get an error. Here's the full script and the error (using jupyter notebook):

...

ANSWER

Answered 2020-Jul-15 at 00:30

I will guess.

ArgumentParser was created to get arguments when you run it in console/terminal not Juputer

Source https://stackoverflow.com/questions/62904639

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

Vulnerabilities

No vulnerabilities reported

Install torchsample

You can download it from GitHub.
You can use torchsample 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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