sentence-similarity | 问题句子相似度计算,即给定客服里用户描述的两句话,用算法来判断是否表示了相同的语义。 | Predictive Analytics library
kandi X-RAY | sentence-similarity Summary
kandi X-RAY | sentence-similarity Summary
问题句子相似度计算,即给定客服里用户描述的两句话,用算法来判断是否表示了相同的语义。
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Top functions reviewed by kandi - BETA
- Train the model
- Build a BSTM model
- Draw the training and validation
- Create a base network
- Exponential distance
- Select the best length of the train
- Build data from training
- Load pretrained embedding
- Convert a sequence of data to train features
- Load the train data table
- Build an embedding matrix
- Train word2vec model
sentence-similarity Key Features
sentence-similarity Examples and Code Snippets
Community Discussions
Trending Discussions on sentence-similarity
QUESTION
this is my first question on Stackoverflow, so if I missed somehting please point it out to me. I have a Problem with my Lambda layer using keras and tensorflow 1. In this Lambda layer I am taking a 100-dimensional glove Vector as Input and compute cosine similarity to 8 other vectors (I converted to Tensors previously). As ouput I want the eight resulting cosine similarities as a Tensor (I thought this is necessary in tensorflow?).
My Problem now is that the shape of the resulting Tensor obviously is (8, 1), but actually I think I Need the Output shape (None, 8). Otherwise it will not match the subsequent layer in my Network which is the Output layer and should Output six class probabilities.
This is the Code for my custom function I feed into the Lambda layer and took from Sentence similarity using keras:
...ANSWER
Answered 2020-Apr-02 at 00:00Simply change your cosine computation to a vectorized operation,
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Install sentence-similarity
You can use sentence-similarity like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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