Torch | Illuminate component in non-Laravel applications

by mattstauffer PHP Version: Current License: MIT

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

kandi X-RAY | Torch Summary

Torch is a PHP library. Torch has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Torch is a project to provide instructions and examples for using Illuminate components as standalone components in non-Laravel applications. The current master branch shows how to use Illuminate's 8.0 components. Note: If you are working with an older project, you might have more success using the 5.5 components or the 5.1 components or the 4.2 components.

Support

Quality

Security

License

Reuse

Support

Torch has a medium active ecosystem.

It has 1764 star(s) with 206 fork(s). There are 70 watchers for this library.

It had no major release in the last 6 months.

There are 10 open issues and 76 have been closed. On average issues are closed in 395 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Torch is current.

Quality

Torch has 0 bugs and 0 code smells.

Security

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

Torch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Torch 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

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

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

Torch saves you 724 person hours of effort in developing the same functionality from scratch.

It has 1672 lines of code, 103 functions and 57 files.

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

Top functions reviewed by kandi - BETA

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

Initialize the capsule .
Show the list of users
Get the current environment .
Handle a request .
Get select fields .
Fire the job .
Render the home page .
Verify username and password .
Send the notification .
Render the given page .

Get all kandi verified functions for this library.

Torch Key Features

No Key Features are available at this moment for Torch.

Torch Examples and Code Snippets

No Code Snippets are available at this moment for Torch.

Community Discussions

Trending Discussions on Torch

I'm using bert pre-trained model for question and answering. It's returning correct result but with lot of spaces between the text

unable to mmap 1024 bytes - Cannot allocate memory - even though there is more than enough ram

How to calculate the f1-score?

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?

No module named 'torch'

QUESTION

I'm using bert pre-trained model for question and answering. It's returning correct result but with lot of spaces between the text

Asked 2021-Jun-15 at 17:14

I'm using bert pre-trained model for question and answering. It's returning correct result but with lot of spaces between the text

The code is below :

...

ANSWER

Answered 2021-Jun-15 at 17:14

You can just use the tokenizer decode function:

Source https://stackoverflow.com/questions/67990545

QUESTION

unable to mmap 1024 bytes - Cannot allocate memory - even though there is more than enough ram

Asked 2021-Jun-14 at 11:16

I'm currently working on a seminar paper on nlp, summarization of sourcecode function documentation. I've therefore created my own dataset with ca. 64000 samples (37453 is the size of the training dataset) and I want to fine tune the BART model. I use for this the package simpletransformers which is based on the huggingface package. My dataset is a pandas dataframe. An example of my dataset:

My code:

...

ANSWER

Answered 2021-Jun-08 at 08:27

While I do not know how to deal with this problem directly, I had a somewhat similar issue(and solved). The difference is:

I use fairseq
I can run my code on google colab with 1 GPU
Got RuntimeError: unable to mmap 280 bytes from file : Cannot allocate memory (12) immediately when I tried to run it on multiple GPUs.

From the other people's code, I found that he uses python -m torch.distributed.launch -- ... to run fairseq-train, and I added it to my bash script and the RuntimeError is gone and training is going.

So I guess if you can run with 21000 samples, you may use torch.distributed to make whole data into small batches and distribute them to several workers.

Source https://stackoverflow.com/questions/67876741

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

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

QUESTION

No module named 'torch'

Asked 2021-Jun-12 at 04:25

I'm trying to solve this Error: ModuleNotFoundError: No module named 'torch' I did the installation of Pytorch using this command: conda install pytorch -c pytorch but when I import torch I got the message above.

...

ANSWER

Answered 2021-Jun-09 at 20:40

Do you have two Python versions installed on your machine?

The error says it could not find the module, maybe it was installed in another version. If that is the case, try to open your python folder where conda.exe is located and run directly especifying that conda file.

Source https://stackoverflow.com/questions/67911289

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

Vulnerabilities

No vulnerabilities reported

Install Torch

You can download it from GitHub.
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