transformer | Transform raw input data into consistent data transfer | Dataset library
kandi X-RAY | transformer Summary
kandi X-RAY | transformer Summary
Transform raw input data into consistent data transfer objects.
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- Return a new collection with only the attributes that are allowed
- Is the attributes changed .
- Checks if the default values should be skipped .
- Checks if the assertion attributes are valid .
- Set an attribute .
- Test whether attributes are present in attributes .
- It is used to check if the collection has missing keys .
- It can return all values .
- It is not null attributes from intersect .
- Get the bar bar .
transformer Key Features
transformer Examples and Code Snippets
Community Discussions
Trending Discussions on transformer
QUESTION
I am not sure how to extract multiple pages from a search result using Pythons Wikipedia plugin. Some advice would be appreciated.
My code so far:
...ANSWER
Answered 2021-Jun-15 at 13:10You have done the hard part, the results are already in the results
variable.
But the results need parsing by the wiki.page()
nethod, which only takes one argument.
The solution? Use a loop to parse all results one by one.
The easiest way will be using for loops, but the list comprehension method is the best.
Replace the last two lines with the following:
QUESTION
I am following this tutorial here: https://huggingface.co/transformers/training.html - though, I am coming across an error, and I think the tutorial is missing an import, but i do not know which.
These are my current imports:
...ANSWER
Answered 2021-Jun-14 at 15:08The error states that you do not have a variable called sentences
in the scope. I believe the tutorial presumes you already have a list of sentences and are tokenizing it.
Have a look at the documentation The first argument can be either a string or list of string or list of list of strings.
QUESTION
I have a REST API which receives a POST request from a client application.
...ANSWER
Answered 2021-Jun-14 at 14:28Your current flow does not return a value, you are simply logging the message.
A terminating .log()
ends the flow.
Delete the .log()
element so the result of the transform will automatically be routed back to the gateway.
Or add a .bridge()
(a bridge to nowhere) after the log and it will bridge the output to the reply channel.
QUESTION
I have the following XML file from which I am trying to remove the whole AuditTrailEntry node if the EventType matched start or assign. I've seen a similar case here on stackoverflow but the solution just doesn't work for me, I always get an error - NOT_FOUND_ERR: Raised if oldChild is not a child of this node. Do you have an idea how to solve this?
...ANSWER
Answered 2021-Jun-11 at 23:26Using XPath, things becomes much easier:
QUESTION
I would like to know if it is possible to automatically assign values to added fields of type:
- datetime
- entity
Thanks for your help
...ANSWER
Answered 2021-Jun-14 at 12:48From what i can see, you have some form and you want to plug 3 data to the form on submit.
Depending on your database configuration, you can do 3 different way:
The best one is to use the mapping
Your evaluation have those 3 fields:
- date
- user
- player
Then just add them to the original builder as hidden field whith default value what you have:
QUESTION
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 08:27While 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.
QUESTION
I have a very simple program that just produces a JTable that is populated via a predetermined ResultSet, it works fine inside the ide, (intelliJ). It only has the one sqlite dependency.
I'm trying to get an standalone executable jar out of it that spits out the same table.
I did the project on gradle as that was the most common result when looking up fat jars.
The guides did not work at all but i did eventually end up on here.
Gradle fat jar does not contain libraries
running "gradle uberJar" on the terminal did produce a jar but it doesn't run when double clicked and running the jar on the cmd line produces:
no main manifest attribute, in dbtest-1.0-SNAPSHOT-uber.jar
here is the gradle build text:
...ANSWER
Answered 2021-Jun-12 at 23:04You can add a manifest to your task since it is type Jar. Specifying an entrypoint with the Main-Class attribute should make your Jar executable.
QUESTION
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 16:19You can make the entire class inherit torch.nn.Module
like so:
QUESTION
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 15:33You are confusing a few things here (I think)
Freezing layersYou 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:
QUESTION
A similar question is already asked, but the answer did not help me solve my problem: Sklearn components in pipeline is not fitted even if the whole pipeline is?
I'm trying to use multiple pipelines to preprocess my data with a One Hot Encoder for categorical and numerical data (as suggested in this blog).
Here is my code, and even though my classifier produces 78% accuracy, I can't figure out why I cannot plot the decision-tree I'm training and what can help me fix the problem. Here is the code snippet:
...ANSWER
Answered 2021-Jun-11 at 22:09You cannot use the export_text
function on the whole pipeline as it only accepts Decision Tree objects, i.e. DecisionTreeClassifier
or DecisionTreeRegressor
. Only pass the fitted estimator of your pipeline and it will work:
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