Hug | A tiny java bytecode manipulation library | Bytecode library
kandi X-RAY | Hug Summary
kandi X-RAY | Hug Summary
Hug is a very small and compact library which can be used for bytecode manipulation. Hug is very abstract and very, very low level. A basic set of utility classes is delivered and can be used to do specific operations easier. (renaming a method, remapping a class etc).
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Top functions reviewed by kandi - BETA
- Create a new constant
- Create a constant
- Creates a new constant name and type
- Creates a new constant
- Adds a UTF - 8 constant
- Returns the raw byte code representation of this class
- Writes this class to the given output stream
- Creates a float
- Returns a string representation of the constant
- Puts a string into the byte vector
- Returns the super - class name of this class
- Put a byte array into this vector
- Put 2 bytes in the byte vector
- Put a byte and value into the vector
- Creates a new integer constant
- Creates a new double
- Initializes this class
- Set the class name
- Set the superclass name
- Create a new invoke dynamic constant
- Creates a method handle
- Creates an interface method ref
- New fieldref
- Converts an InputStream to a byte array
- Put a short into this vector
Hug Key Features
Hug Examples and Code Snippets
Lines of Code : 94
License : No License
Copy# filename: versioning_example.py
"""A simple example of a hug API call with versioning"""
import hug
@hug.get('/echo', versions=1)
def echo(text):
return text
@hug.get('/echo', versions=range(2, 5))
def echo(text):
return "Echo: {text}".f @hug.type(chain=True, extend=hug.types.number, accept_context=True)
def check_if_near_the_right_number(value, context):
the_only_right_number = context['the_only_right_number']
if value not in [
the_only_right_number - 1,
the_ hug -nd -f {file} #nd flag tells hug not to generate documentation on 404
@hug.not_found()
def not_found_handler():
return "Not Found"
@hug.not_found(versions=1)
def not_found_handler():
return ""
@hug.not_found(versions=2)
def not_found_h Community Discussions
Trending Discussions on Hug
QUESTION
What is the loss function used in Trainer from the Transformers library of Hugging Face?
I am trying to fine tine a BERT model using the Trainer class from the Transformers library of Hugging Face.
In their documentation, they mention that one can specify a customized loss function by overriding the compute_loss method in the class. However, if I do not do the method override and use the Trainer to fine tine a BERT model directly for sentiment classification, what is the default loss function being use? Is it the categorical crossentropy? Thanks!
ANSWER
Answered 2022-Mar-23 at 10:12It depends!
Especially given your relatively vague setup description, it is not clear what loss will be used. But to start from the beginning, let's first check how the default compute_loss() function in the Trainer class looks like.
You can find the corresponding function here, if you want to have a look for yourself (current version at time of writing is 4.17). The actual loss that will be returned with default parameters is taken from the model's output values:
loss = outputs["loss"] if isinstance(outputs, dict) else outputs[0]
which means that the model itself is (by default) responsible for computing some sort of loss and returning it in outputs.
Following this, we can then look into the actual model definitions for BERT (source: here, and in particular check out the model that will be used in your Sentiment Analysis task (I assume a BertForSequenceClassification model.
The code relevant for defining a loss function looks like this:
QUESTION
I am new to hugging face and want to adopt the same Transformer architecture as done in ViT for image classification to my domain. I thus need to change the input shape and the augmentations done.
From the snippet from huggingface:
...ANSWER
Answered 2022-Mar-15 at 13:20In your case, I would recommend looking at the source code here and tracing the called classes. For example to get the layers of the Embeddings class, you can run:
QUESTION
I have the following HStack:
...ANSWER
Answered 2022-Mar-09 at 04:29try something like this to put "...the "Test text" on the left, space in the middle and the segment control on the right.":
QUESTION
Summary: I have seemingly hit a limitation in Figma when trying to make the columns behave akin to a CSS grid system. I would like to know if I have misunderstood Figma's built in capabilities, if there is a plug-in that solves the problem, if I have to create one Figma frame per CSS breakpoint (undesirable), or if there are other solutions.
Background: As an interaction/ UX designer, I would like to specify the responsiveness of a web based application, so that the front end developers know how the interface should appear at all browser widths. They implement in a CSS-based grid system similar to Bootstrap
So far, I failed in achieving what I want, and the most knowledgeable UX'ers in the company think I have hit a limitation in Figma's capabilities, but they are not certain.
Basically, what I want is this basic responsiveness, but column based. But as shown in this video, none of my experiments work.
I wonder if it boils down to this: If a Figma child element has:
- horisontal constraint set to “Scale” and
- vertical constraint set to “Hug contents”
Then the parent element cannot have:
- vertical constraint set to “Hug contents”
Is this is a known limitation in Figma? If yes, are there plugins that solve this problem, or is it outside Figma's scope to offer this type of alignment with CSS-based grid systems? Obviously, it would be very beneficial if the solution also supports breakpoints.
P.S. I have asked which SE site that was most suitable for this question, and SO was the suggested site. The question was closed on UX.SE.
...ANSWER
Answered 2022-Mar-01 at 08:08No, according to an answer on Figma's own forum, Figma's columns cannot behave akin to a CSS grid system, even though “several threads [have] requested [this] evolution”.
QUESTION
Currently I am working on Named Entity Recognition in the medical domain using Camembert, precisely using the model: TFCamembert.
However I have some problems with the fine-tuning of the model for my task as I am using a private dataset not available on Hugging Face.
The data is divided into text files and annotation files. The text file contains for example:
...ANSWER
Answered 2022-Feb-11 at 11:04Try transforming your data into the correct format, before feeding it to model.fit:
QUESTION
I would like to add a section header to a UICollectionView which contains two lables to show a title and a info description. Both labels can show multi line texts and the header size should be automatically adopted to the label content.
TL;DR
Auto layout seems to fails when the label font is changed the appearance() proxy. Is there solution to solve this?
Complete description
This is how I set up the header view in IB:
As one can see, IB reports a problem. This is a "Content Priority Ambiguity" which can easily be solved by setting the Vertical Content Hugging Priority of InfoLabel to 250.
The header view is than added in the ViewController and referenceSizeForHeaderInSection is used to setup the size:
ANSWER
Answered 2022-Feb-05 at 13:23Here is one approach:
QUESTION
I have this grid CSS
...ANSWER
Answered 2022-Jan-19 at 12:23Use auto instead of 1fr and the same justify-content will work like with flexbox:
QUESTION
when i use the st.cache decorator to cash hugging-face transformer model i get
Unhashable TypeError
this is the code
...ANSWER
Answered 2021-Dec-08 at 13:02This worked for me:
QUESTION
This question is the same with How can I check a confusion_matrix after fine-tuning with custom datasets?, on Data Science Stack Exchange.
BackgroundI would like to check a confusion_matrix, including precision, recall, and f1-score like below after fine-tuning with custom datasets.
Fine tuning process and the task are Sequence Classification with IMDb Reviews on the Fine-tuning with custom datasets tutorial on Hugging face.
After finishing the fine-tune with Trainer, how can I check a confusion_matrix in this case?
An image of confusion_matrix, including precision, recall, and f1-score original site: just for example output image
...ANSWER
Answered 2021-Nov-24 at 13:26What you could do in this situation is to iterate on the validation set(or on the test set for that matter) and manually create a list of y_true and y_pred.
QUESTION
Rather than passing the fastify instance to every function, how can I pass it at a top level only once so its available to all functions in the controller?
ANSWER
Answered 2021-Nov-09 at 23:04The answer is a simple, mechanical refactoring using closures:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Hug
You can use Hug like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Hug component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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