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code-search
Code & Text Embedding with UniXcoder
author: Jael Gu
Description
A code search operator takes a text string of programming language or natural language as an input and returns an embedding vector in ndarray which captures the input's core semantic elements. This operator is implemented with pre-trained UniXcoder models from Huggingface Transformers.
Code Example
Use the pre-trained model "microsoft/unixcoder-base" to generate text embeddings for given text description "return max value" and code "def max(a,b): if a>b: return a else return b".
Write the pipeline:
import towhee
(
towhee.dc(['find max value', 'def max(a,b): if a>b: return a else return b'])
.code_search.unixcoder(model_name='microsoft/unixcoder-base')
)
Write a same pipeline with explicit inputs/outputs name specifications:
import towhee
(
towhee.dc['text'](['return max value', 'def max(a,b): if a>b: return a else return b'])
.code_search.unixcoder['text', 'embedding']()
.show()
)
Factory Constructor
Create the operator via the following factory method:
code_search.unixcoder(model_name="microsoft/unixcoder-base")
Parameters:
model_name: str
The model name in string. The default model name is "microsoft/unixcoder-base".
device: str
The device to run model inference. The default value is None, which enables GPU if cuda is available.
Supported model names:
- microsoft/unixcoder-base
Interface
The operator takes a piece of text in string as input. It loads tokenizer and pre-trained model using model name. and then return an embedding in ndarray.
call(txt)
Parameters:
txt: str
The text string in programming language or natural language.
Returns:
numpy.ndarray
The text embedding generated by model, in shape of (dim,).
save_model(format="pytorch", path="default")
Save model to local with specified format.
Parameters:
format: str
The format of saved model, defaults to "pytorch".
format: path
The path where model is saved to. By default, it will save model to the operator directory.
supported_model_names(format=None)
Get a list of all supported model names or supported model names for specified model format.
Parameters:
format: str
The model format such as "pytorch", "torchscript". The default value is None, which will return all supported model names.
Jael Gu
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README.md |
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__init__.py |
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requirements.txt |
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result.png |
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unixcoder.py |
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