tokenizer | small library for converting tokenized PHP source code | Parser library
kandi X-RAY | tokenizer Summary
kandi X-RAY | tokenizer Summary
A small library for converting tokenized PHP source code into XML.
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Top functions reviewed by kandi - BETA
- Parses the given string .
- Fill blank tokens .
- Sets an offset .
- Serialize the source .
- Get token at given offset .
- Convert tokens to DOMDocument .
- Ensures a valid URI .
- Get value .
- Returns current line .
- Get the value as string .
tokenizer Key Features
tokenizer Examples and Code Snippets
import {makeTokenizer} from '@tokenizer/http';
import {fileTypeFromTokenizer} from 'file-type';
const audioTrackUrl = 'https://test-audio.netlify.com/Various%20Artists%20-%202009%20-%20netBloc%20Vol%2024_%20tiuqottigeloot%20%5BMP3-V2%5D/01%20-%20Dia
public static List streamTokenizerWithCustomConfiguration(Reader reader) throws IOException {
StreamTokenizer streamTokenizer = new StreamTokenizer(reader);
List tokens = new ArrayList<>();
streamTokenizer.wordChars('!'
public static List streamTokenizerWithDefaultConfiguration(Reader reader) throws IOException {
StreamTokenizer streamTokenizer = new StreamTokenizer(reader);
List tokens = new ArrayList<>();
int currentToken = streamTok
def get_translation_model_and_tokenizer(src_lang, dst_lang):
"""
Given the source and destination languages, returns the appropriate model
See the language codes here: https://developers.google.com/admin-sdk/directory/v1/languages
For the 3-c
Community Discussions
Trending Discussions on tokenizer
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 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
I have a custom tokenizer and want to use it for prediction in Production API. How do I save/download the tokenizer?
This is my code trying to save it:
...ANSWER
Answered 2021-Jun-12 at 09:28Here is the situation, using a simple file to disentangle the issue from irrelevant specificities like pickle, Tensorflow, and tokenizers:
QUESTION
ANSWER
Answered 2021-Jun-12 at 06:42The SpaCy tokenizer seems to cache each token in a map internally. Consequently, each new token increases the size of that map. Over time, more and more new tokens inevitably occur (although with decreasing speed, following Zipf's law). At some point, after having processed large numbers of texts, the token map will thus outgrow the available memory. With a large amount of available memory, of course this can be delayed for a very long time.
The solution I have chosen is to store the SpaCy model in a TTLCache and to reload it every hour, emptying the token map. This adds some extra computational cost for reloading the SpaCy model from, but that is almost negligible.
QUESTION
The following link shows how to add custom entity rule where the entities span more than one token. The code to do that is below:
...ANSWER
Answered 2021-Jun-09 at 17:49You need to define your own method to instantiate the entity ruler:
QUESTION
ANSWER
Answered 2021-Jun-10 at 03:09Application resources will become embedded resources by the time of deployment, so it is wise to start accessing them as if they were, right now. An embedded-resource must be accessed by URL rather than file. See the info. page for embedded resource for how to form the URL.
Thanks for your work, work with
getResource
. Here is the working code
QUESTION
Using tutorials here , I wrote the following codes:
...ANSWER
Answered 2021-Jun-09 at 14:19You can call tokenizer.decode
on the output of the tokenizer to get the words from its vocabulary under given indices:
QUESTION
I need texts like #tag1 quick brown fox #tag2 to be tokenized into #tag1
, quick
, brown
, fox
, #tag2
, so I can search this text on any of the patterns #tag1
, quick
, brown
, fox
, #tag2
where the symbol #
must be included in the search term. In my index mapping I have a text
type field (to search on quick
, brown
, fox
) with the keyword
type subfield (to search on #tag
), and when I use search term #tag
it gives me only the match on the first token #tag1
but not on #tag1
.
I think what I need is a tokenizer that will produce word boundary tokens that inlcude special chars. Can someone suggest a solution?
ANSWER
Answered 2021-Jun-08 at 16:38If you want to include #
in your search, you should use different analyzer than standard analyzer
because #
will be removed during analyze phase. You can use whitespace analyzer
to analyze your text field.
Also for search you can use wildcard pattern:
Query:
QUESTION
i've been trying to import spacy but everytime an error appears as a result. I used this line to install the package :
...ANSWER
Answered 2021-Jun-08 at 16:11The problem is that the file you are working in is named spacy.py
, which is interfering with the spacy module. So you should rename your file to something other than "spacy".
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