nn | Minimal implementations of neural network architectures | Machine Learning library

by lab-ml Python Version: Current License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | nn Summary

nn is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. nn has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install nn' or download it from GitHub, PyPI.

This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, and the website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better. We are actively maintaining this repo and adding new implementations.

Support

Quality

Security

License

Reuse

Support

nn has a low active ecosystem.

It has 304 star(s) with 15 fork(s). There are 18 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nn is current.

Quality

nn has 0 bugs and 0 code smells.

Security

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

nn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nn is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

nn releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

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

nn saves you 19549 person hours of effort in developing the same functionality from scratch.

It has 38557 lines of code, 362 functions and 144 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of nn

Get all kandi verified functions for this library.

nn Key Features

No Key Features are available at this moment for nn.

nn Examples and Code Snippets

Creates a depthwise convolution input .

python

Lines of Code : 62

License : Non-SPDX (Apache License 2.0)

Copy

def depthwise_conv2d_native_backprop_input(  # pylint: disable=redefined-builtin,dangerous-default-value
    input_sizes,
    filter,
    out_backprop,
    strides,
    padding,
    data_format="NHWC",
    dilations=[1, 1, 1, 1],
    name=None):
  r"

Max pooling op .

python

Lines of Code : 54

License : Non-SPDX (Apache License 2.0)

Copy

def max_pool1d(input, ksize, strides, padding, data_format="NWC", name=None):
  """Performs the max pooling on the input.

  Note internally this op reshapes and uses the underlying 2d operation.

  Args:
    input: A 3-D `Tensor` of the format speci

Average pooling op .

python

Lines of Code : 37

License : Non-SPDX (Apache License 2.0)

Copy

def avg_pool3d(input, ksize, strides, padding, data_format="NDHWC", name=None):  # pylint: disable=redefined-builtin
  """Performs the average pooling on the input.

  Each entry in `output` is the mean of the corresponding size `ksize`
  window in `

Community Discussions

Trending Discussions on nn

Problem with FULLY_CONNECTED op in TF Lite

How to calculate the f1-score?

Extracting verbs except for the POStag from text with POS tag in R

Why does THREE.BoundingBoxHelper not display?

How to perform bicubic upsampling of image using pytorch?

Force BERT transformer to use CUDA

Is it possible to combine 2 neural networks?

UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach()

How and where can i freeze classifier layer?

Pytorch: Is it able to make a convolution module without bias have bias again?

QUESTION

Problem with FULLY_CONNECTED op in TF Lite

Asked 2021-Jun-15 at 13:22

I'd like to run a simple neural network model which uses Keras on a Rasperry microcontroller. I get a problem when I use a layer. The code is defined like this:

...

ANSWER

Answered 2021-May-25 at 01:08

I had the same problem, man. I want to transplant tflite to the development board of CEVA. There is no problem in compiling. In the process of running, there is also an error in AddBuiltin(full_connect). At present, the only possible situation I guess is that some devices can not support tflite.

Source https://stackoverflow.com/questions/67677228

QUESTION

How to calculate the f1-score?

Asked 2021-Jun-14 at 07:07

I have a pyTorch-code to train a model that should be able to detect placeholder-images among product-images. I didn't write the code by myself as I am very unexperienced with CNNs and Machine Learning.

My boss told me to calculate the f1-score for that model and i found out that the formula for that is ((precision * recall)/(precision + recall)) but I don't know how I get precision and recall. Is someone able to tell me how I can get those two parameters from that following code? (Sorry for the long piece of code, but I didn't really know what is necessary and what isn't)

...

ANSWER

Answered 2021-Jun-13 at 15:17

You can use sklearn to calculate f1_score

Source https://stackoverflow.com/questions/67959327

QUESTION

Extracting verbs except for the POStag from text with POS tag in R

Asked 2021-Jun-13 at 20:09

I am new in R. I tried to gather the verbs ("/VB","/VBD","/VBG","/VBN","/VBP","/VBZ") using "openNLP" package (Note that 'udpipe' does not work in my environment). I have a sentence mixed with the tag as below.

"Doing/VBG work/NN as/IN always/RB ./. playing/VBG soccer/NN is/VBZ good/JJ ./. I/PRP do/VBP that/IN"

How can I achieve the verbs without POS tags? The answer I am trying to get in this example is

"doing", "playing", "is", "do"

...

ANSWER

Answered 2021-Jun-13 at 20:09

your requested example:

Source https://stackoverflow.com/questions/67961637

QUESTION

Why does THREE.BoundingBoxHelper not display?

Asked 2021-Jun-13 at 13:55

I have previously managed to display the box, but here, where I have stripped everything down in order to experiment with expanding boxes by positioning collada models, the box won't show.

...

ANSWER

Answered 2021-Jun-13 at 13:55

First of all, BoundingBoxHelper is now BoxHelper. It seems you are using a very old release of three.js.

Besides, your collada() function is not synchronous. After executing collada("14",pobj); and collada("7",pobj); the assets are not yet loaded which means you are computing the bounding box for an empty group object.

I suggest you wait until the Collada models have been loaded via THREE.LoadingManager and then add the helper to your scene.

Alternatively, ensure to call helper.update() in your animation loop. This approach is wasteful however if the object is static and does not change. So it's probably better to use the onLoad() callback of a loading manager.

Source https://stackoverflow.com/questions/67957274

QUESTION

How to perform bicubic upsampling of image using pytorch?

Asked 2021-Jun-13 at 12:16

I have png image. I want to upsample it using bicubic interpolation. I found this function in pytorch:

...

ANSWER

Answered 2021-Jun-13 at 12:16

You can do this

Source https://stackoverflow.com/questions/67957965

QUESTION

Force BERT transformer to use CUDA

Asked 2021-Jun-13 at 09:57

I want to force the Huggingface transformer (BERT) to make use of CUDA. nvidia-smi showed that all my CPU cores were maxed out during the code execution, but my GPU was at 0% utilization. Unfortunately, I'm new to the Hugginface library as well as PyTorch and don't know where to place the CUDA attributes device = cuda:0 or .to(cuda:0).

The code below is basically a customized part from german sentiment BERT working example

...

ANSWER

Answered 2021-Jun-12 at 16:19

You can make the entire class inherit torch.nn.Module like so:

Source https://stackoverflow.com/questions/67948945

QUESTION

Is it possible to combine 2 neural networks?

Asked 2021-Jun-13 at 00:55

I have a NET like (exemple from here)

...

ANSWER

Answered 2021-Jun-07 at 14:26

The most naive way to do it would be to instantiate both models, sum the two predictions and compute the loss with it. This will backpropagate through both models:

Source https://stackoverflow.com/questions/67872719

QUESTION

UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach()

Asked 2021-Jun-12 at 23:00

I'm new on PyTorch and I'm trying to code with it so I have a function called OH which tack a number and return a vector like this

...

ANSWER

Answered 2021-Apr-30 at 23:19

the problem is that you are receiving a tensor on the act function on the Network and then save it as a tensor just remove the tensor in the action like this

Source https://stackoverflow.com/questions/67341208

QUESTION

How and where can i freeze classifier layer?

Asked 2021-Jun-12 at 20:29

If I need to freeze the output layer of this model which is doing the classification as I don't need it.

...

ANSWER

Answered 2021-Jun-11 at 15:33

You are confusing a few things here (I think)

Freezing layers

You freeze the layer if you don't want them to be trained (and don't want them to be part of the graph also).

Usually we freeze part of the network creating features, in your case it would be everything up to self.head.

After that, we usually only train bottleneck (self.head in this case) to fine-tune it for the task at hand.

In case of your model it would be:

Source https://stackoverflow.com/questions/67939448

QUESTION

Pytorch: Is it able to make a convolution module without bias have bias again?

Asked 2021-Jun-12 at 12:48

After instantiating a 2D convolution with conv = nn.Conv2d(8, 8, 3, bias=False), whose member bias should be None, is it able to give conv a legal bias again (whether with random initialization or determined values)?

I observed that bias in other default convolution modules is of the type Parameter, so I suspect there are extra procedures beyond simply conv.bias = torch.tensor(...) to make the new bias legal for conv.

...

ANSWER

Answered 2021-Jun-12 at 12:48

Yes, it is possible to set the bias of the conv layer after instantiating. You can use the nn.Parameter class to create bias parameter and assign to conv object's bias attribute.

To show this I have created a simple Conv2d layer and assigned zero to the weights and ones to bias.

Source https://stackoverflow.com/questions/67948404

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

Vulnerabilities

No vulnerabilities reported

Install nn

You can install using 'pip install nn' or download it from GitHub, PyPI.
You can use nn 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 .

Find more information at: